HUMAN FACTORS REQUIREMENTS FOR REAL-TIME MOTORIST INFORMATION DISPLAYS

VOL. 10 HUMAN FACTORS EVALUATION;'OF TRAFFIC STATE DESCRIPTOR VARIABLES

@]

C. L. Dudek R. D. Huchingson

R. J. Koppa M. L. Edwards

CONRAO [. DUDEK

[f@[p®[fU from the Texas A&M

RESEARCH FOUNDATION College Station, Texas

Texas Transportation Institute Texas A&M University

College Station, Texas 77843

Prepared for

I

Federal Highway Administration Offices of Research and Development

Contract No. DOT-11-8505

February 1978

1. Report No. 2. Government Accession No.

FHWA-RD-78-14 4. Title and Subtitle

HUMAN FACTORS REQUIREMENTS FOR REAL-TIME MOTORIST INFORMATION DISPLAYS Vol. 10 - Human Factors Evaluation of Traffic State

Technical Keport Uocumentat1on rage

3. Recipient's Cotalog No.

5. Report Date

February 1978 6. Performing Organization Code

,_.,.. ______ D_e_s_c_r_i.L-oto_r_V-'a_;.r_i....;;a;.;_b_l_e-'-s __________ _, 8. Performing Organization Report No. 7 · Author

1s> C. L. Dudek, R. D. Huchingson, R. J. Koppa,

and M. L. Edwards 9. Performing Organization Name and Address

Texas Transportation Institute Texas A&M University

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DOT-FH-11-8505 College Station, Texas 77843 13. TypeafReportandPeriodCovered

12. Sponsoring Agency Name and Address--------------- Final Report U.S. Department of Transportation (June 1974-February 1978) Federal Highway Administration Office of Research, Traffic Systems Division Washington, D.C. 20590

14. Sponsoring Agency Code

15. Supplementary Notes

FHWA Contract Manager: Truman M. Mast (HRS-31)

16. Abstract

This document summarizes the laboratory research findings in eight topic areas dealing with message design criteria associated with traffic state descriptors. Several of the studies were replicated in different regions of the United States. The research objectives dealt with issues of content, format and associated understanding of messages. Among the issues explored were minimum traffic state information requir~ments; traffic state descriptors; traffic state coding; location and length of congestion; lane blockage descriptors; incident types; and temporal information. The results of these studies have been incorporated into the Design Guide (Volume 1).

17. Key Words Traffic State Variables, Human Factors Design Criteria, Driver Expectan­cies, Lane Blockage, Temporal Information, Real-Time Motorist Information, Freeway Operations, Traffic Management

18. Distribution Statement

No restrictions. This document is available to the public through the National Technical Information Service, Springfield, Virginia 22151

19. Security Clauif. (of this report) 20. Security Classif. (of this poge) 21· No. of Pages 22. Price

Unclassified Unclassified Form DOT F 1700.7 <S-72! Reproduction of completed poge authorized

PREFACE

This document is part of a seventeen-volume report entitled, Human

Factors Requirements For Real-Time Motorist Information Displays. Titles of

all volumes are shown below.

FHWA-RD Volume Number Title

1 78-5 Design Guide

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

78-6

78-7

78-8

78-9

78-10

78-11

78-12

78-13

78-14

78-15

78-16

78-17

78-18

78-19

78-20

78-21

State of the Art: Messages and Displays in Freeway Corri­dors

Summary of Systems in the United States

Bibliography and Selected Annotations: Visual Systems

Bibliography and Selected Annotations: Audio Systems

Questionnaire Survey of Motorist Route Selection Criteria

Analysis of Driver Requirements for Intercity Trips

Analysis of Driver Requirements for Intracity Trips

A Study of Physical Design Requirements for Motorist Infor­mation Matrix Signs

Human Factors Evaluation of Traffic State Descriptor Variables ·

Human Factors Evaluation of Route Diversion and Guidance Variables

Supplement to Traffic State Descriptors and Route Diversion and Guidance Studies

Human Factors Evaluation of Audio and Mixed Modal Variables

Point Diversion for Special Events Field Studies

Freeway Incident Management Field Studies

Feasibility of Audio Signing Techniques

Driver Response to Diversionary Information

ii

ACKNOWLEDGMENTS

The authors would like to express their appreciaUon to the numerous individuals who significantly participated in the conduct of the studies reported in this Volume. While the responsibility for the content of this report rests solely with the authors, a large share of the credit belongs to those individuals who assisted in the research.

TTI staff members Quinn Brackett, Mike Bergman, Graeme Weaver, and Don Woods provided valuable assistance in developing the detailed experimental designs.

Graeme Weaver organized and conducted the regional studies in Houston, St. Paul, and Los Angeles. He was assisted by William Stockton, John Mounce, and Donald Andersen.

Roger McNees, assisted by Norma Keener, coordinated subject scheduling and spent many hours on the telephone to insure that the subjects would show on time for the laboratory studies.

Johnny Hobbs and his associates produced within very short time schedules the detailed and excellent artwork for the slides used in the studies. Jim Bradley and Terre 11 Robertson photographed the visual displays.

Quinn Brackett, Dennis Seal, Donald Harrison, Carol Adams, Oscar Egly, Steve Richards, Roger McNees, and Donald Hatcher spent exhaustive hours reducing and analyzing data.

Larry Ringer provided statistical advice throughout the project.

Special acknowledgment is due Truman Mast, FHWA Contract Manager~ for his invaluable counsel, advice, and guidance throughout this project. Dr. Mast worked very closely with the research staff and was always available to share his ideas and offer constructive critique adding more depth and dimension to the research project. His associates, particularly Jim Ballas and Joe Peters, are recognized for their technical consultation and construc­tive criticism. Or. John Eicher provided FHWA administrative support. Acknowledgment is also made to Lawrence D. Powers, Lyle Saxton, and Samuel Tignor who, together with Tr~man Mast and John Eicher, were instrumental in organizing the FHWA research program on real-time motorist information displays.

The contributions of several organizations in Houston, St. Paul, and Los Angeles are acknowledged. The authors are grateful to the following organizations for allowing TTI to administer selected studies to their employees and to the many individuals within these organizations who donated their time in coordinating the studies and the warm reception given to the TTI staff members who conducted the regional studies:

iii

Houston

Anderson Clayton Company - Mr. E. A. Tribe

Defense Contract Administration Services - Col. Lautzenheiser Mrs. Alma Gomez

Entex

Exxon Company USA

First City National Bank

Getty Oil Company

Gulf Oil Company USA

Los Angeles

- Mr. John Waltz

- Miss Mary Partridge

- Mr. D. Mifflin Ms. Alice Butler

- Mr. Ken Crouch Mr. W. W. Myers

- Mr. W. K, Read, Jr.

Automobile Club of Southern California - Mr. Paul Fowler

St. Paul

Minnesota Mining and Manufacturing Company (3M) Mr. John Landen

Mr. John Houghnon Mr. Ray Halverson Mr. Rob Kasson Mr. Sid Leahy Mr. William Witherspoon Mr. Doug Wachs

The authors appreciate the invaluable contribution made by Sherrie Rowland, Rosette Marshall, and Sally Bowden, whose excellent typing skills were instrumental in completing this manuscript. Donald Hatcher coordinated the preparation of the final manuscript.

iv

TABLE OF CONTENTS

Chapter

I. INTRODUCTION ..... .

p~

1

Project Objectives .. 1

Report Scope. . . . . 2

II. TASK B ORGANIZATIONAL STRUCTURE, PROCEDURES, AND FACILITIES. . 6

Introduction. . . . . 6

Experimental Designs. 6

Stimulus Materials. . 7

Local Studies . . .

Regional Studies.

. . . . . •.

Subject Demographic Data.

III. TASK B STUDY TECHNIQUES ..

1. Progranuned Text ..

2. Selective Interrogation Method ..

3. Sign Building Technique ..

4. Psychological Scaling ..

5. Localized Questionnaires.

6. Open-End Questions of Meaning ..

7. Likert-Scaling Methods. . ..•

7

15

19.

20

20

21

22

• • • • 23

• • • • • • 23

24

. • . . . 25

8. Probe Questi ans . . . . 25

9. Unnecessary Infonnation Assessment. . . . . 25

10. Performance Studies of Message Understanding. 26

11. Ranking Complete Messages . . . . . . 26

12. Card Sorting. . . . . . . . . 27

v

TABLE OF CONTENTS (continued)

Chapter

IV. TOPIC AREA A - MINIMUM TRAFFIC STATE INFORMATION REQUIREMENTS ....... . 29

Study 1 - Information Requested by the Unfamiliar Driver. 35

Study 2 - Effect of Driver Familiarity . . . 44

Study 3 - Effect of Traffic Problem Severity 52

V. TOPIC AREA B - TRAFFIC STATE DESCRIPTORS . . 63

VI.

Study 1 - Number of Discriminable Traffic States

Study 2 - Descriptors for Extreme Traffic States

Study 3 - Verbal Descriptors of Level Service

Study 4 - Verbal Descriptors of Level Service - Follow-up

TOPIC AREA C - TRAFFIC STATE CODING . . . . Study 1 - Preliminary Screening of Traffic State Coding

65

70

77

86

113

Methods . . . . . . . . 115

Study 2 - Traffic State Coding Methods 124

VII. TOPIC AREA D - LOCATION AND LENGTH OF CONGESTION 132

Study 1 - Descriptors for Congestion Location - Non-commuters . . . . . . . . . . 135

Study 2 - Descriptors for Congestion Location -Corrrnuters . . . . . . . . . . 147

VIII. TOPIC AREA E - LANE BLOCKAGE (CLOSURE) AND AVAILABILITY DESCRIPTORS . . . . . . . . . . . . . 162

Study 1 - Verbal and Coding Methods - Understanding of and Preferences for Messages (Part 1) 164

Study 1 - Verbal and Coding Methods - Understanding of and Preferences for Messages (Part 2) 178

Study 1 - Verbal and Coding Methods - Understanding of and Preferences for Messages (Part 3) 182

vi

TABLE OF CONTENTS (continued)

Chapter Page

Study 1 - Verbal and Coding Methods - Understanding of anq Preferences for Messages (Part 4) . 184

Study 2 - Verbal and Coding Methods - Understanding of Signs . . . . . . . . . . . . . . . . 185

Study 3 - Verbal and Coding Methods - Follow-up Study . · 194

Study 4 - Ori ver Interpretation of 11 Bl ocked 11 Versus 11 Closed 11 Messages 202

IX. TOPIC AREA F - INCIDENT TYPES . . . . . . . . 211

Study 1 - Categorization of Verbal Messages . 216

Study 2 - Priority of Incident Information 229

X. TOPIC AREA G-A - TEMPORAL INFORMATION PREFERENCES IN RELATION TO OTHER INFORMATION ON A CHANGEABLE MESSAGE

. SIGN . . . . . . . 236

XI. TOPIC AREA G - TEMPORAL INFORMATION . . 261

Study 1 - Expressed Need for Temporal Information 264

Study 2 - Delay Duration and Diversion

Study 3 - Time Saved and Diversion . .

Study 4 - Major and Minor Accidents and Delay

Study 5 - Meaning of Delay ........ .

Study 6 - Modes of Presenting Temporal Information

APPENDIX A

APPENDIX B

APPENDIX C .

APPENDIX D

APPENDIX E

vii

269

277

282

286

291

301

303

316

326

334

I. INTRODUCTION

Project Objectives

The primary objectives of this research project were to:

1. develop, evaluate, and make design reconmendations for real-time

driver information displays to be used on freeways and alternative

routes, and

2. make the recommendations available in the form of a design guide that

can be used by practicing traffic engineers.

The research was concerned with information displays used to induce route

diversion and traffic management in a freeway corridor when freeway incidents

occur. Both visual and auditory displays were studied. Primary consideration

was on the human factors aspects of the displays with primary emphasis on the

following visual and auditory information message display variables:

1. Content

2. Format

3. Quantity

4. Redundancy

5. Placement

Other display variables such as color and size of fixed and dynamic visual

sign components and voice quality and syntax variables for auditory displays

were to be examined and recommended.

A systems analysis (1..!..._g_) conducted in Task A of the research project

identified several driver information needs while traveling in a freeway corri­

dor when freeway incidents occur. The analysis, coupled with a thorough state­

of-the-art review (l, .1) and a questionnaire survey (§_), resulted in several

1

display design questions that required further analysis. These design issues,

discussed in Reference l, formed the basis for the human factors laboratory

experimental program designed and conducted in Task B.

Report Scope

The Task B laboratory experimental program was structured into four spe-

cific areas of investigation:

1. D-Series Dynamic Displays

2. T-Series Traffic State Descriptors

3. R-Series Route Diversion and Guidance

4. A&M-Series Audio and Mixed Mode

Each area of investigation is documented in a separate report.

The reports documenting the Traffic State Descriptor and Route Diversion

and Guidance studies are presented according to topic areas, each to~ic area

covers up to seven separate studies depending on the nature of the investiga­

tion. The following topic areas are addressed:

Topic Area

A - Minimum Traffic State Information Requirements

B - Traffic State Descriptors

C - Traffic State Coding

D - Location and Length of Congestion

E - Lane Blockage (Closure) and Availability Descriptors

F - Incident Types

G-A - Temporal Information Preferences in Relation to Other Information on a Changeable Message Sign

G - Temporal Information

H - Advanced Warning Signs for Point Diversion

2

Topic Area

I - Major Point Diversion Sign Coding

J - Format and Other Issues

K - Secondary Verbal Message Regarding Route Assurance

L - Alternate Route Descriptors

M - Route Guidance to Multiple Destinations

N - Guidance to Major Generators

0 - Local Descriptors

P - Bypass Route Guide Signs (Forgiving Sign)

This report (Volume 10) discusses Topic Areas A through G. Topic Areas

H through Pare presented in Volume 11, entitled, "Human Factors Evaluation of

Route Diversion and Guidance Variables."

The order in which the topic areas are presented in the two reports do

not necessarily imply the order in which the studies were conducted. The topic

areas have been arranged into what the authors believe is a logical sequencing

of topics in an attempt to enhance readability and understanding of the material

covered in the research.

Because of the enormous amount of research presented in this report and

Volume 11, an attempt is made to concentrate on the results, interpretations,

and conclusions to enhance the readability. Experimental designs and approaches

are addressed only to the extent that the reader can better understand the

experiments and evaluate the results. Details of laboratory instructions and

stimulus materials are presented for the interested reader as a separate docu­

ment in Volume 12, entitled, "Supplement to Traffic State Descriptors and

Route Diversion and Guidance Studies."

3

The results of the Dynamic Displays (D-Series) studies concerned with psy­

chophysical signing design issues, particularly with respect to matrix signs,

are presented in Volume 9, entitled, 11 A Study of Physical Design Requirements

for Motorist Information Matrix Signs. 11

Research addressing Audio and Mixed Mode {A&M Series) issues is presented

in Volume 13.

4

REFERENCES

1. Dudek, C. L., Huchingson, R. D., Ratcliff, R.H., and Mayer, G. J. Human Factors Requirements For Real-Time Motorist Information Displays, Vol. 7 - Analysis of Driver Requirements for Intercity Trips. Texas Transportation Institute, Report No. FHWA-RD-78-11, February 1978.

2. Carvell, J. D. and Whitson, R. H. Human Factors Requirements For Real­Time Motorist Information Displays, Vol. 8 - Analysis of Driver Require­ments for Intracity Trips. Texas Transportation Institute, Report No. FHWA-RD-78-12, February 1978.

3. Dudek, C. L. Human Factors Requirements For Real-Time Motorist Informa­tion Displays, Vol. 2 - State-of-the-Art: Messages and Displays in Freeway Corridors. Texas Transportation Institute, Report No. FHWA-RD-78-6, February 1978.

4. Dudek, C. L. Human Factors Requirements For Real-Time Motorist Informa­tion Displays, Vol. 3 - Summary of Systems in the United States. Texas Transportation Institute, Report No. FHWA-RD-78-7, February 1978.

5. McNees, R. W. and Huchingson, R. D. Human Factors Requirements For Real­Time Motorist Information Displays, Vol. 6 - Questionnaire Survey of Motorist Route Selection Criteria. Texas Transportation Institute,. Report No. FHWA-RD-78-10, February 1978.

5

Introduction

II. TASK B ORGANIZATIONAL STRUCTURE, PROCEDURES, AND FACILITIES

The magnitude of the multifaceted and-complex research project constrained

by short time conmitments required special emphasis be placed on the management

and administration of the human factors laboratory studies. Initially, some

35 experiments were conceptualized, which eventually expanded to approximately

70. Many of the experiments were interrelated; therefore. it was necessary to

review the results of several studies before progressing to follow-up studies.

Also, decisions had to be made concerning the selection of experiments that

would be conducted regionally. Procedures for the system of quality control

for developing the experimental designs and conducting the experiments are out-

1 ined in Appendix A and briefly discussed in the following sections.

Experimental Designs

The initial 35 experiments were conceptualized and formulated into four

specific and logical areas of research:

1. D-Series Dynamic Displays

2. T-Series Traffic State Descriptors

3. R-Series Route Diversion and Guidance

4. A&M Series Audio and Mixed Mode

The conceptualized experiments were documented in considerable detail and

included, as a minimum, the following:

1. Title

2. Objectives

3. Facility to be used

6

4. Independent variables

5. Criterion variables

Members of the project staff were organized into four Study Teams to

develop detailed experimental designs in each of the study areas (T-, R-, D-,

and A&M-Series). At least four staff members were assigned to each study area

to insure a proper blending of human factors, traffic engineering, and statis­

tical expertise. A Study Leader, appointed to each study area, was responsible

for directing the group's activities to insure the experimental designs achieve

study objectives and time schedules.

Stimulus Materials

Following approval of an experimental design, a Slide Coordinator worked

with the artists, draftsmen, and photographers to prepare the visual aids.

Local Studies

Local studies refer to the experiments conducted in the Bryan-College

Station area. Most of the local studies were conducted in the human factors

laboratory and supplemented with studies conducted in local shopping centers

and with instrumented vehicle experiments.

Laboratory Facilities The human factors laboratory is located on the Texas

A&M University campus. The laboratory is equipped with environmental controls

for heat, cold, and humidity which was kept at a both constant and pleasant

temperature all through the studies. Lighting and noise levels were also kept

constant by means of control devices and materials provided in the lab room

structure itself. These included rheostat lighting, lamps, acoustic floors

and walls, etc. The environmental chamber was equipped with a special

7

double glass wall for projection purposes, which separated the subject room

from the operator-facility room. Tables with desk lamps for all subjects and

a desk for dispensing and storing data was also provided. Depending on the

nature of the particular experiment, different pieces of equipment were intro­

duced to accommodate that experiment to insure the controlled presentation and

administration of the tests. The utilization of this facility thus allowed

for the creation of a standardized locale and environment for conducting all

local laboratory research.

The presentation for various studies conducted in the laboratory was accom­

plished using a media master system with programmable audio/visual capabilities

using cassette taoe decks as its operative means. This system has 2-track

recording heads set in stereo to present various visual and/or audio stimuli.

During the studies, programming was achi,eved by recording the voice communica­

tion (instructions, etc.) segment on one track and the impulses for operating

the equipment (film projectors, slide projectors, on-off, advance slides, tape

stop, etc.) on the other track. Also, the answer and weighing factors for tests

could be programmed. Depending on the nature of the study, different combina­

tions of media were used, yet all of these insured programmed, constant stimu-

1 us-response type procedures for control. These combinations included

voice/slides, voice/film/slides, and voice only. For some studies, the multi­

media system's answer and weighing factor memory was used in order that the

operator could attain consistent and accurate values when needed. In those

instances where control of viewing time was desired, special function units

were build and connected to the system to handle various combination needs.

These units provided for a constant, controlled inter-stimulus level where

8

equal intervals of time for the presentation of two or more stimuli could be

constant throughout for each combination of stimuli.·

A movie film projector and slide projectors of the "Carousel" type were

used to present the visual portion of the studies. The light intensity adjust­

ments of these units were kept constant throughout the studies for controlled

presentation. Voice presentation equipment consisted of a small amplifier/mixer

connected to a speaker enclosure in the subject room and a monitor speaker in

the operator's room. The monitor permitted the adjustment of a constant, regu­

lated sound level required to relay experiment directions and other pertinent

infonnation before, during, qnd after each study. For projection purposes, a

large mirror was used to redirect the image of the slides onto the double glass

wall into the subject room. The optimal mirror angle was obtained and then the

mirror was locked into position in order to maintain a constant projection

angle for all subjects viewing the visual presentation. When the nature of the

study demanded gathering interval data, such as reaction times and/or multiple

choice answers on a time scale, a digital display timer, along with special

extension rods equipped with push button reaction time boxes, were introduced.

These pieces of equipment were programmed to permit a constant inter-stimulus

interval to insure controlled administration and response.

A schematic of the laboratory Mediamaster system is presented in Figure 1.

Photographs of the laboratory equipment are shown-in Figure 2.

Instrumented Vehicle - The instrumented vehicle was developed and constructed

to be employed in those studies where it was important to be able to measure

the impact of individual signs (or signing systems) on driver performance.

Presentation capabilities exist for both auditory and visual materials to the

driver much in the manner they might be presented on the roadway.

9

SUBJECT

RESPONDERS

(30 MAXIMUM J

PROJECTION SCREEN

FILMSTRIP PROJECTOR

MOTION PROJECTOR

SLIDE PROJECTOR

FIGURE 1 .., SCHEMATIC OF MEDI~MASTER SYSTEM

10

PROJECTOR CONTROL

BOX

Console and Subject Responders

Slide and Movie Projectors Rear-projection Screen Interconnected with Console

Figure 2 - Mediamaster Equipment

11

Since the instrumented vehicle was used primarily in the audio and mixed

mode studies, details of the vehicle are presented in Volume 13. It should be

pointed out that selected mixed mode studies addressed specific aspects of

visual trailblazer designs.

Subjects - Subjects for the local laboratory studies were recruited from the

Bryan-College Station area. A pool of more than 340 drivers was assembled

during the course of the studies. A Subject Coordinator was assigned to develop

a list of volunteer subjects for each study in accordance with a predetermined

distribution matrix of demographic data, and to contact and schedule subjects

to insure appropriate sample sizes and demographic distributions. Studies were

primarily conducted during the week at scheduled times, both during working

hours and after 5:00 pm. Subjects were reimbursed at a rate of $7.50 per hour.

University employees either volunteered their time or reimbursement was made

to the specific departments within the University system.

Table B-1 in Appendix B represents a percentage distribution of education

completed by urban and rural residents 18 years of age or older classified by

sex and age adopted from the United States Statistical Abstract, U. S. Bureau

of Census, Washington, D. C. Similar data are presented in Table B-2 for

urban dwellers. Utilizi_ng the data in the above two tables, ~djusted to

reflect the license driver ratio of 55 percent male and 45 percent female

(Ref: Highway Statistics, U. S. Department of Transportation, Washington,

D. C., 1973, p. 55), resulted in demographic percentage distributions shown in

Table 1. These data formed the basis for the subject sample used in the local

laboratory studies.

12

TABLE 1

PERCENT OF DRIVERS 18 YEARS OF AGE AND OLDER COMPLETING EDUCATION LEVEL SHOWN*

MALES Aqe Groups Elementary H1qh School rolleqe

1-3 4 1-3 4 or more

18-24 ~ 6 4 2 l 25-34 1 2 . 4 2 2 35-44 1 2 3 1 1

45-54 2 2 3 1 1 55-64 2 1 2 1 1 over 64 4 1 1 1 0

Total Males 13 14 17 8 6

FEMALES

18-24 2 4 3 2 0

25-34 1 1 3 1 1

35-44 1 l 3 1 l 45-54 2 l 2 1 1 55-64 2 1 1 l 0

over 64 3 l l 0 0

Total Females 11 9 13 6 3

GRAND TOTAL 24 23 30 14 /9

1ota1s

16 11 8

9

7 7

58

11 7 7 7 5 5

42

100

*Adopted from United States Statistical Abstract, U. S. Bureau of the Census, Washington, D. C., U. S. Printing Office, 1971, and Highway Statistics, U. S. Department of Transportation, Washington, D. C., U. S. Printing Office, 1973.

13

Although scheduling problems did not always permit 100 percent compliance,

every effort was made to approximate the demographic distributions shown in

Table 1 as much as practicable for t~e laboratory studies. Recruiting subjects

in shopping centers for a few selected studies reported herein, presented prob­

lems not encountered in the laboratory studies. Many subjects resisted inquir­

ies concerning demographic data, particularly with respect to age and education.

Given a choice of either obtaining data within a reasonable time period or

extending the studies over several weeks just to get demographic information,

the decision was made to forgo demographic inquiries. However, both male and

female subjects in approximately equal numbers, did volunteer and the inferred

ages did approximate the target sampling distribution.

Laboratory Procedures - For a majority of the studies, a generalized procedure

for preparing the 11 block 11 of studies to be given was followed. In a typical

instance, Monday afternoon would be designated as the recording and sequencing

period for the studies to be recorded and programmed. The day would end with

a "run through 11 of that block by the technicians of the lab. Tuesday would be

set aside for a formal "dry run" for the Study Leaders and Project Supervisors.

Here, usually, sequencing of the studies, minor changes to audio instruc­

tions, visual aids, and answer forms would be discussed. Wednesday would be

set aside for changes needed and the final re-running of the block for consis­

tency and timing of administration. Either Wednesday afternoon or Thursday

would mark the first runs with subjects, with the block sequence continuing on

through the following week, or until the required number of subjects was

attained.

14

The subjects, upon first reporting for a "block" of studies, would fill

out thr.e·e forms: a consent form, a driver i nfonnation survey form, and an

employment status form. With consecutive appointments, the survey form was

omitted, but each appointment required the filling out of the other two forms.

After conµleting the necessary paperwork, the subjects would be directed into

the laboratory to await further instructions from the operator-technician.

There were approximately 15 blocks of experiments, each conducted over a

two-week period in the T and R Series. Each block consisted df three to five

experiments which were timed in advance to insure that they did not exceed an

administration time of 50 minutes, including breaks between experiments,

instructions, etc.

The composition of each block of experiments was carefully reviewed to

avoid fatigue or boredom by scheduling different types of tasks. The variable

of possible transfer of training was also considered in subject assingment to

experiments so that subjects' instructions on one experiment would not affect

his responses on another experiment.

Regional Studies

General - Sign message interpretation is influenced to a certain degree by

custom and semantics. Since the objective was to define messages that are

applicable on a national scale, it was necessary to determine to what degree

message content, display mode, and word association were influenced by geo­

graphical location within the United States.

Traffic descriptors (T-Series), route diversion messages (R-Series), and

to .a limited degree, the audio and mixed mode {A&M-Series) and dynamic

15

displays (D-Series) that emerged from the human factors laboratory studies

showing high potential for further evaluation, were selected for evaluation on

a regional basis. From these studies, it would be possible to identify those

messages that would be applicable nation-wide and those that would be usable in

concept, but would require replacement of certain individual elements by terms

that were geographically unitjue. An example is cited. The roadway parallel

to a controlled access facility can be described by several terms--service

road, frontage road, access road, feeder street, and others. To correctly

communicate with a driver when presenting information regarding the use of this

roadway, it is necessary to refer to it by the descriptor by which it is com­

monly known.

The regional studies were conducted to ascertain anomalies such as the one

cited above and, in addition, to provide replications of the TAMU laboratory

findings to increase confidence in their generality and to permit development

of design criteria which would be acceptable as national norms.

The studies composed of selected experiments from the T, R, A&M, and D­

Series studies were conducted in Houston, St. Paul, and Los Angeles.

Subjects - Subjects were recruited in the Houston area by contacting personnel

directors of several business firms and soliciting their cooperation by allow­

ing the research staff to present to the employees, o~ the business premises

and during working hours, a series of slide-tape studies for evaluation. The

City of Houston Traffic Department provided information regarding companies

who had been extremely cooperative in evaluation studies of several Houston

transportation action plans. Written requests for assistance stating the study

objectives and specific information regarding subject selection criteria and

16

the type and duration of the evaluation presentations, were sent to the person­

nel directors of these finns. Follow-up personal meetings were held with those

finns responding affirmatively. The Houston companies participating in the

regional study are listed below:

Anderson Clayton Company

Defense Contract Administration Services

Entex

Exxon Company USA

First City National Bank

Getty Oil Company

Gulf Oil Company USA

The Minnesota Mining and Manufacturing Company (3-M) volunteered to provide

approximately 300 employees during working hours within a one week period at

the St. Paul office complex to whom the regional studies could be administered.

The slide-tape presentations were presented in one-hour blocks, four sessions

per day.

The Los Angeles regional study subjects were recruited from two sources.

The Automobile Club of Southern California supplied approximately 60 employees

to whom the slide-tape presentations were administered after working hours.

The subjects were compensated for their time by TTI. In addition, TTI contracted

with the Preview House, Los Angeles, to recruit additional subjects. The firm

specializes in evaluating commercial displays, such as television and movie

commercials and other mass-media marketing activities, and normally has over

300 subjects available each worknight. Slide-tape presentations were adminis­

tered to more than 200 subjects at the Preview House in one-hour blocks (approx­

imately 20 subjects per block) during a week.

17

It was desired that subjects evaluating the message displays be represen­

tative of the national driving population. The U. S. statistical abstract

(1971) information was used to categorize driver percentages according to age

distribution, sex, and educational background. Subjects were selected on these

bases as much as practicable to comprise a study session. Additional require­

ments were that each subject must be a licensed driver and preferable one who

drove on freeways.

Blocks of subjects ranging from approximately 15 to 40 subjects were

assembled to evaluate the message displays.

Procedure - One-hour study blocks consisting of individual experiments were

constructed. Some of the individual experiments (studies) included highly

structured audio-visual presentations of sign messages in which the subject

answered specific questions on an answer sheet. Other studies involved state­

ments of preference for several factors within a sign message. Also, some

experiments required that subjects construct a sign message to present infor­

mation for a given circumstance. In still others, subjects were required to

specify terminology for certain roadway elements or operational occurrences.

Care was taken to avoid constructing study blocks that would contain experi­

ments in which the results would be biased by a learning process.

Where possible, each experiment was introduced by a taped set of instruc­

tions. All slide sequences were synchronized to the taped messages so that a

presentation to any subject group was identical in wording, delivery character­

istics and timing.

Each subject was presented a pre-assembled answer booklet containing the

answer forms for the studies within the one-hour block. The subjects were

18

instructed to progress through the booklet only as directed by the study leader

or by the taped instructions. Each subject provided specific information con­

cerning his (her) age, educational background, driving experience, and famil­

iarity with freeway driving. No names, addresses, or other traceable informa­

tion was requested -- each booklet was assigned a code number for filing pur­

poses.

The answer forms and the experiments were designed such that each subject

could answer the questions or complete the appropriate answer form during the

slide-tape presentation.

Subject Demographic Data ·

Demographic data for the subjects participating in study Topic Areas A

through G are shown in Appendix Table 8-3.

19

III. TASK B STUDY TECHNIQUES

Several laboratory study techniques for examining various aspects of real­

time displays were employed during the conduct of Task B.. In addition to clas­

sical approaches, TTI also developed and implemented some innovative techniques.

The study techniques are highlighted in this section, as it is felt that they

offer a quick reference to the reader since they can be successfully employed

in future work in this general area. In addition, since each of the study

techniques are used in more than one experiment, this summary will minimize

repetition within the body of the report. The following innovative techniques

were developed by TTI during the course of the research:

1. Programmed Text

Although the use of the programmed text is not unique with respect to its

application to training, it has not been used previously as a mechanism for

conducting research in the area of route guidance. One of the basic problems

in conducting research in this area is developing and operating a stimulus

presentation system (usually an instrumented vehicle) in an efficient manner.

Not only are these approaches costly from a fiscal standpoint, they are inef­

ficient from a subject standpoint, as well. Only one subject can be run at a

time, and a significant amount of time is required to run a given subject.

To combat these problems, a programmed text was developed which contained

all signs a motorist would see when following a given route. Utilizing this

technique, an entire network of signs and associated road systems could be

designed and simulated utilizing only photographs of roadway sections with

indirect signs superimposed over the photograph.

20

Each page contains a set of instructions directing the subject to turn to

a particular page, depending on whether his decision was to turn either left or

right, or continue straight. A score is obtained from the subject's recording

of the pages he reviewed in tracing his path through the booklet. In this man­

ner, both the route he (or she) took and the probable nature of the error at

various decision points, can be determined. There are numerous advantages to

this approach from a practical standpoint, in that it is relatively inexpensive

to construct an experimental signing system for study. Additionally, a subject

can be started anywhere in the systeM with a given goal and his resulting path

determined. Another advantage is that one can determine if route diversion

signing systems i·nterfere with the route selection of drivers who enter the

system at some point other than its origin.

2. Selective Interrogation Method

One of the basic problems in conducting research in the area of information

requirements is identifying those requirements without providing more informa­

tion than the subject actually needs to make some decision. For example, if a

subject is provided with five units of information and asked to select out those

he does not require, he will tend to select more information than he actually

requires, simply because it is available to him. This tendency to select more

informaiton than is a.ctually required can create some difficulty in highway

signing, where both size of sign (in number of characters) and viewing time are

limited.

In the Selective Interrogation technique, a subject is presented with a

standardized scenario (constructed by the experimenter) which describes both

the location of the subject's vehicle in the traffic stream and all pertinent

21

traffic conditions surrounding it. A subject is then placed in this environ­

ment and instructed to ask any questions felt appropriate about conditions in

this environment, as 1 ong as it can be answered with a "yes" or "no". Fo 11 ow­

ing this question, the experimenter, using the pre-constructed scenario, will

answer that question. Once the question is answered, the experimenter queries

the subject to determine if he has enough information to make a decision

to remain on the roadway he is on, or exit. If the subject's response is

"no", another question is allowed. If his response is "yes", the decision

is noted and the interview is terminated.

Utilizing this approach, it is possible to identify (at least tentatively)

the minimum information requirements of the driver, both in number of units

of i nforma ti on and type, in a s tanda rdi zed 1 aboratory setting.

3. Sign Building Technique

One of the primary variables studied during the conduct of this effort

was sign language formatting (preference for content, message sequences, and

message length). As would be expected, there are a number of ways of investi­

gating these variables. An approach typically used is the construction of

candidate signs containing all possible combinations of some number of pre­

determined sign language units and having each of these signs rated on some

criterion by a pool of subjects (paired comparisons take even longer to conduct).

One difficulty with this approach is that it requires the construction and

testing of some signs that were not highly rated.

In order to avoid this, as well as some other methodological difficulties,

a technique was divised wherein each candidate message element (word) was

placed on one card and subjects were allowed to work through this deck,

22

selecting only those words they felt were needed to conmunicate to them what

they needed to know in a particular situation. Following this selection, sub­

jects then arranged these units such as to compose the sign in any manner

deemed appropriate. In this manner, agreement among subjects in preferring a

self-constructed sign format could be determined and used as a criterion to

select the optimum format for signing a specific objective. The technique also

provided an indication of preferred message elements and number of elements.

4. Psychological Scaling

In attempting to determine if a particular verbal expression constituted

a more severe state of traffic than other expressions, subjects were given one

of three pictures of traffic on a freeway and were asked if the expression

described a worse, or better, state of traffic than that pictured. The tech­

nique not only permitted scaling words in terms of the 11 severity 11 implied, but

also provided an index of the specificity/ambiguity dimension. The latter came

from the consistency with which subjects assigned an expression to a particular

category.

Thfs was the second generation of scaling techniques used. Initially,

several (6} pictures were used and subjects were to match the words with ther

six levels of traffic states shown. This method was unsatisfactory because

subjects tended to assign nearly all words to the extreme pictures. The first­

discussed method avoided this by subjects seeing only one picture.

5. Localized Questionnaires

Often the familiarity of the driver with an area may influence his choice

of the way he wants information presented. For example, the conmuter may pre-

fer fami 1 i ar freeway names, while the visitor prefers interstate numbers he

has used from his map. 23

One study was to determine whether daily commuters would prefer a location

of congestion described by distance in miles or by the cross-street at which

the congestion occurred. The build-a-sign method described above could be

used to see which words were selected, but the problem was how to get local

subjects to think in the same manner as commuters from a large city. With

build-a-sign, one was limited to using a familiar cross-street name and a fic­

titious one, and telling the subject he was in Bryan or in some other city.

By and large, local subjects responded the same way (distance).

However, when commuters from Los Angeles were used as subjects and they

were asked to think about their trip to and from work, they preferred cross­

street names. It was also found they knew all, or nearly all, the major exits

by name and could relate to these better than distance in miles or fractions,

thereof.

The questionnaire tested their ability to recall a familiar route, and the

investigators used a map of Los Angeles to check the correctness of their

naming exits in order, as well as estimating distances along the route.

6. Open-End Questiions of Meaning

From the standpoint of scoring, investigators might be tempted to present

a series of slides (e.g., coded messages) and ask the subject to check which of

several things the message means to him. The problem is that the meaning is

suggested to him in the alternatives given. Also, there may be a transfer of

training from a message easily understood, to one which might not have been,

had he not seen the easily understood message first.

A solution to these two problems was to present each subject with only

one message and ask him what it would mean to him if he saw this sign on the

24

freeway. He receives no clues from other messages. Neither is he given a

checklist. He must generate the answer from the message itself much as a

visitor to a city seeing the sign for the first time.

7. Likert-Scaling Methods

Another approach to studying meaning involves giving the subjects several

different possible meanings and having them indicate on a 5-point Likert scale

their degree of agreement with the meanings given. In this case, the meanings

are all given, but the subject must be more discriminating than a simple 11yes 11

or 11 no 11 response. Although lf:!SS effective than the open-ended question, it is

quicker to administer when time is at a premium and it is easier to score.

The technique has also been applied to other scaling problems, such as how much

delay a subject would tolerate before diverting.

8. Probe Questions

Sometimes direct questions of preference between messages were asked, such

as, 11 Whi ch of the following messages would most 1 i kely convince you to get off

of a freeway?" However, the subject must be critical because the next question

asked for a reason for the decision made. Also, the inverse question, "Which

would be least likely to induce diversion?" also was followed by a request for

a reason.

9. Unnecessary Information Assessment

A direct method of assessing unnecessary information in a signed message

involved having the subjects cross out any information which they felt could

be omitted without loss of meaning. This technique allowed the subjects direct

control in indicating sources of unnecessary information.

25

10. Performance Studies of Message Understanding

Sometimes the issue of understanding a message can be better approached

by presenting a series of slides to subjects with each slide showing a sign,

such as if he were driving down the freeway. His task is to indicate if he

would continue or divert at the next exit, given the signing information.

Since many subjects would routinely follow the sign's message, it has been

found useful to have subjects commit themselves in advance as to which of the

two routes they plan to take (such as a bypass, or through the city route).

This is realistic, since most drivers also plan their routes in advance.

Upon seeing a sign which suggests a different way from that planned. the

"clearness 11 of the message is an issue. Wi 11 he go a different way from that

initially stated, or will he continue as planned, assuming the message is irrele­

vant.

This technique may be criticized for requiring a public commitment to a

route, rather than a private or unstated commitment, as in real life. However,

the technique of detennining in advance which route the driver planned to take

is essential. If the driver had planned to go in the direction indicated by

the sign, the message's effect on the driver is unknown. But if he had planned

a different route, then the signed message clearly influenced a change in route

planning.

Measures of decision reaction time have also been used as an indirect

measure of the degree of confusion induced by the sign's message.

11. Ranking Complete Messages

One of the weaknesses of the Sign Building Technique is that sometimes the

best combinations of words are not immediately apparent.. If there are too many

26

candidate words, the subject's choice may not be based upon a consideration of

all the better circumstances.

Under these circumstances, complete word messages may be given and the

subjects simply rank them from best to worse. Analyses of the preferred mes­

sages can tell the preferred content or.message elements and can reveal confus­

ing formats as well.

12. Card Sorting

A technique was employed to determine how people group messages together

conceptually, i.e., how they abstract properties of diverse messages and assign

them to unnamed categories on the basis of common properties.

Subjects were given a deck of cards, each with a word or expressi"on des­

cribing an incident. They were instructed to place the cards into stacks, all

of which contained some common property. Subjects were told to use as many

stacks as they needed. It was possible to determine the average number of

categories subjects employed in classifying all of the incident words.

After the card sorting was completed, subjects were asked to give a title

to each category. In so doing, they revealed the property which the various

words shared in their judgment.

The major problem with the method in situations where. there are long lists

of words is the variety of subject responses (titles for categories). The

investigator must then judge whether various titles are equivalent. Unless

several independent judgments are used, the categories may reflect the investi­

gator's judgments. The instructions may also unwittingly provide subjects a

criteria for classification. For example, instructions to classify, in terms

of "how the incident affects the driver" could result in categorizing in terms

27

of whether he would slow down, detour, continue, etc. Actually, the practical

interest lies in determining whether or not an abstract noun or expression such

as "moving vehicle" or 11 accident 11 should be substituted on a sign for various

specific instances of these expressions. The card sort method may be less

effective than more direct questioning in arriving at these types of answers.

28

IV. TOPIC AREA A - MINIMUM TRAFFIC STATE INFORMATION REQUIREMENTS

Objectives

The primary objective of this topic area was to identify the minimum

information requirements of the driver with respect to traffic state des­

criptors displayed on a freeway. More specifically, these studies attempted

to:

(a) Identify critical classes of traffic state information.

(b) Identify the number of "bits" of traffic state information required

before making a decision.

(c) Determine the sequencing of traffic state information.

(d) Identify differences between familiar and unfamiliar drivers

information requirements.

(e) Determine if severity of the traffic problem affects number and

types of traffic state information requested.

Background

An important concern in the development and implementation of any signing

system is the identification of traffic state information a driver feels he

requires to make decisions (for example, to take some alternate route). A

number of studies were conducted during Task B which made the assumption that

a particular type of information was needed by the driver and then proceeded

to investigate the better ways of communicating that type of information.

However, it became apparent that the driver could well be overloaded with

information which was irrelevant for his making a diversion decision. Perhaps,

29

it would be well to see how many of these types of information were called for

in the unlimited questions by drivers. If there was agreement on the types and

amount of information needed, this would reduce the amount of information that

would need to be displayed on a changeable message sign (CMS).

A more structured approach to assessment of driver needs is to present

the infonnation and ask if drivers would want that type of infonnation.

This approach invites an affirmative response. The information would be 11 nice 11,

yet it might well be information the driver would never think of himself.

In the present study, a ~on-directive approach was utilized. The approach

allowed the subject to express his infonnational needs, with respect to a

"problem ahead" on the freeway, in the fonn of unprompted questions. He was

given free reign to ask as many or as few as he needed prior to making a

decision to continue or to divert. In this manner, the subjects establish a

priority and sum total of infonnational needs with respect to the freeway

conditions. The advantage of this approach is that the driver would have no

"uncertainty" about freeway conditions which would affect his diversion decision.

Therefore, the display of any other freeway information at that moment would be

irrelevant.

Method

A number of studies were conducted utilizing this same basic concept.

However, a convnon method was employed nn each of these studies with few ex­

ceptions. The following details the general methodology.

Subjects were placed in a position (through verbal instructions) of being

on a freeway during off peak ~onditions. They were instructed that a sign

ahead was convnunicating to them that there was trouble on their route (the

nature of the problem was not disclosed) and that they were as yet not close

30

enough to read the message the sign was displaying. They were then told that

the interviewer was going to be a substitute for the sign and that they could

ask him any question about the freeway problem that could be answered with a

"yes" or 11no. 11 The interviewer answered each question 11yes 11 or "no" according

to a predetermined data base (discussed below) and he then asked jf the sub­

ject had enough information to make a decision about whether to leave the

freeway or to remain. If the person said he had enouqh information, the inter­

viewer asked what the decision was and the interview was terminated. If the

answer was "no", the subject was allowed to ask another question, as long as

it could be answered with a "yes" or "no". This basic procedure was continued

until each subject had enough information to make some determination ~bout

remaining on the freeway or leaving it for another route.

An informational base, or scenario, was developed for each of the several

studies conducted utilizing this approach. This scenario was used by the ex­

perimenters as a guide for responding to questions presented by the subject.

Use of this scenario served to insure that all answers to questions were

standardized to the extent possible, thus minimizing any experimenter bias

that might result otherwise.

The questions having an affirmative reply from the experimenter in Studies

1 and 2 are presented in Figure A-1. The answers given described a traffic

situation of considerable severity. Since the severity of the problem could

influence both the number and types of questions asked, Study 3 was conducted

to investigate the subjects pattern of responses with milder traffic conditions.

To determine if driver information requirements varied as a function of

the type of incident, four separate incidents were employed: 1) accident,

2) roadwork, 3) congestion, and 4) icy bridge.

31

Individual subjects were assigned by the experimenter to one of the

incident categories at random prior to their participating in the study.

The actual interview with these subjects proceeded in the following

manner. If the first question asked by a subject was related to the nature

of the problem ahead (incident) he (or she) was told yes, and the nature of

the incident was revealed. Thus, if a given subject was in the accident cat­

egory and asked {on the first question) 11 Is there roadwork ahead?" he was

told 11 no, there is an accident." The interview then proceeded in the manner

described previously. If the subject never asked the nature of the incident,

this information was never revealed to him.

Although it was predetermined exactly the kinds of infonnation which

would be given (Figure A-1), it was anticipated that few subjects would actually

guess the correct answers to the quantitative variables - distances, delay times,

traffic speeds, and route numbers. Therefore, whenever a subject asked any

question at all regarding a particular topic, he was told the true state of

affairs. For example, if he asked if traffic was moving on the freeway, he was

told traffic was traveling at 10 mph or less.

In this manner it was possible to transmit useful information such as

might be presented on a CMS without requiring that the subject himself correctly

anticipate the exact state of affairs. Without this procedure he might be

misled by a negative answer to a question which was almost but not quite correct.

The scenario depicted in Figure A-1 allowed for the possibility subjects

might ask questions regarding where they might exit and the bypass routes around

the indicent. However, the instructions were designed to solicit questions

32

Figure A-1

Scenario of Traffic Condition or Guidance Questions Resulting in an Affirmative Answer

Question

Type of Incident (One incident only given regardless of which incident posed in question. See Text.)

Congestion Level - Heavy Incident Location - 2 miles ahead Congestion Length - 1 mile

Amount of Delay - 20 minutes Traffic Speed - 10 mph or less Lanes Blocked - 2 · Lanes Open - 1

Can I bypass incident? Will the next exit get me to the bypass? Is the next exit within 2 miles? Will I be guided along the bypass? Is the bypass route an undivided 2 or 3

lane street? Is the bypass route a state highway? Is the traffic on the bypass route light? Does the bypass route rejoin the Gulf

Freeway { I-45)?

Answer

Accident Roadwork Icy Bridge Congestion

Yes Yes Yes

Yes Yes Yes Yes

Yes Yes Yes (1.5 miles) Yes

Yes Yes {S. H. 3 south) Yes

Yes (at F. M. 528 or NASA 1)

Note: Few subjects actually asked quantitative questions. The procedure was whenever they asked a question in a topic area, the correct information was given to them.

33

regarding traffic state variables since this was the objective of the study.

Subjects were asked what they wished to know about the 11 freeway ahead 11 given

there was a problem. Therefore, they were not encouraged to inquire about

exit locations or how to bypass incident. Traffic state information pertinent

to a diversion decision was the focus of the questioning.

34

Study 1 - Infonnation Requested by the Unfamiliar Driver

Objective

The objective of the first study was to determine the amount and types

of traffic state information required by the unfamiliar driver to make a

decision whether to leave the freeway.

Method

The procedure employed was as described in the previous section. The

112 subjects were residents of the Bryan/College Station area. Fifty-eight

subjects responded individually in the laboratory and 54 answered individually

at a local shopping center. The incident problem was keyed to a Houston loca­

tion wi 1th which it was assumed most of the subjects were unfamiliar (see

Volume 12 for instructions).

Results and Discussion

· Of initial interest was the frequency with which type of incident ques­

tions were asked, e.g., how many drivers' initial question related to 11what

was happening ahead''. Table A-1 presents. l) questions asked, classified into

topic areas, 2) the total frequency with which a question was asked, and 3)

the frequencies with which questions were asked as a first, second, third,

etc. question. (The order in which information was sought by the subjects is

flow charted in Figures C-1 and C-2 in Appendix C.)

· As can be seen, a question regarding the nature of the incident ahead

was most often the que~tion asked first. In fact 48 (or 43 percent) of the

subjects asked this type of que.stion first. Furthermore, this question con­

stituted 25 percent of all questions asked regardless of their order. It

35

TABLE A-1

ORDERED FREQUENCIES OF QUESTIONS ASKED BY SUBJECTS (COLLAPSED OVER ALL INCIDENT TYPES)

Order of Question Question Topic 1 2 3 4 5 Total

Type of Incident 48 6 4 1 1 60*

Level of Congestion 13 19 5 2 2 41

Lane Blockage 2~ 18 5 0 0 48* Y'-(?.

Amount of Delay 9 18 5 4 2 38

Speed of Traffic 7 2 2 1 0 12

Location of Incident 2 3 1 1 0 7

Location of Nearest Exit 5 3 11 3 0 22

Other 3 6 3 3 2 17

112 75 36 15 7 ~·

n = 112

*asked significantly mare frequently than other classes (p < .05)

36

%

2~ /

V"

Z<Y

16

5

3

9

7

can therefore be concluded that incident type (cause of the traffic problem)

is of primary importance to the driver, and should be included when signing

for freeway incidents.

Level of congestion, lane blockage, and amount of delay were also of

considerable concern. Thirteen subjects first asked a question about level

of congestion; nineteen asked about level of congestion during their second

question. Forty-one (17 percent) of the subjects asked about the congestion

level prior to making a decision to either stay on or leave the freeway. Other

infonnation in Table A-1 may be interpreted in a similar manner.

Also of importance was the number of freeway questions (or information

bits) that must be resolved by the driver before some decision is made to con­

tinue on or leave the freeway. A breakdown of these responses is presented

in Table A-2. It may be noted that after three questions (regardless of type),

86.6 percent of the drivers studied had obtained enough information to make

some decision. In fact, a third (33 percent) of the drivers were able to make

a decision following only one question. Therefore, it would appear that the

majority of drivers' information needs concerning freeway conditions can be

satisfied with three units of infonnation, one of these obviously being the type

of incident.

To determine what the qther two units in this order were, an analysis of

the decision points was made. Presented in Table A-3 is a breakdown of the

percentage of subjects making a decision after asking a particular category

of question regardless of the order the question was asked. Several interesting

findings are evident from these results.

Probably the most significant finding is related to the frequency with

37

TABLE A-2

PERCENTAGE OF SUBJECTS MAKING DECISIONS AS A FUNCTION OF NUMBER OF QUESTIONS ASKEO

No. of ~uestions Fr~q. of s Percentage of Asked N) Asking Only Total

N Questions Subjects

1 37 33.0

2 39 34.8

3 21 18.8

4 8 7.1

5 7 6.3

38

Cumulative Percentage of Subjects

33.0

67.8

86.6

93.7

100.0

TABLE A-3

PERCENTAGE OF SUBJECTS MAKING DECISIONS FOLLOWING ASKING FOR TYPES OF INFORMATION

Question Topic f %

Incident 15 14

Congestion 32* 28

Lane Blockage 18 16

Delay 24* 21

Traffic Speed 4 4

Location of Incident 1 1

Exit Location 15 13

Other 3 3

112 100

*x2 = 13.5, p < .05

39

which decisions are made following certain types of questions. As was noted

earlier, significantly more (43 percent) requested type of incident information

o~ the first question than requested any other information. Altogether about

60 or over half asked this kind of question. The present results, however,

indicate that only 14 percent of the drivers studied were able to make some

decision following attainment of this type of information. Therefore, it would

appear that although incident type information is important to the driver with

respect to providing him with some overall picture of the traffic problem ahead,

it does not provide him with sufficient information to make a decision about

whether or not to divert. In fact, the critical information appears to be that

which describes the traffic conditions created as a function of the incident.

Inspection of Table A-3 reveals that the question categories after which most

decisions were reached are:

1. Level of congestion associated with the incident - 28 percent.

2. Amount of delay to be expected - 21 percent.

3. Extent of lane blockage - 16 percent.

As can be seen, these descriptors all describe a common factor related to

the incident, that factor being overall traffic conditions. In fact, 65 percent

of all subjects made a decision after asking one of these three categories of

information.

It may be wondered why more subjects did not ask for the location of the

nearest exit or for information regarding a possible bypass route around the

incident. Before a conclusion can be made that this type of information did

not come to mind, the nature of the experimental session should be reviewed.

40

(See instructions in Volume 12.) The subjects were asked to limit their

questions to the "freeway ahead", which implied that the question would

relate to traffic state variables. The location of the exits or alternate

routes was out of scope in this study. The subject, himself, was required to

formulate the question in such a manner as to obtain either an affirmative, or

a negative answer. Being unfamiliar with the city or freeway on which the

problem occurred, subjects would not be able to ask pertinent questions, such

as "Can I take State Highway 3 South?" or 11 Does the bypass rejoin the freeway

at F.M. 528?" Thus, specific route guidance information was not possible by

the method of questioning u~ed.

It may be recalled that subjects were divided into four approximately

equal groups and were given accordingly one of four types of incidents when

they asked any question relating to the nature. of the problem. These types of

incidents were accident, roadwork, congestion, and icy bridge.

An experimental question related to whether t.he type of incident given

affected in any way the final question which they asked before deciding to

divert. Table A-4 presents the frequencies of final question topics and cor­

responding percentage infonnation. The percentages shown are percentages of

the subjects assigned to that incident category. For example, 2 (6 percent) of

the 33 subjects who were told there was an accident immediately decided whether

to divert.

Some interesting findings were that congestion was more often the last

question for the "accident" group; incident and congestion the last question

for the 11 congestion 11 group; delay the last question for the "icy bridge" group,

and several questions for the "roadwork" group. Despite the sample of 112, the

41

TABLE A-4

PERCENTAGE OF SUBJECTS IN INCIDENT CATEGORIES MAKING DIVERSION DECISIONS AFTER SPECIFIC QUESTIONS

Incident Category

Question Topic Accident Roadwork Congestion f % f % f %

Incident 2 6 3 11 ·6 25

Congestion 13 39 7 26 7 29

Lane Blockage 5 15 7 26 3 12

Delay 7 21 5 18 3 12

Speed of Traffic 0 0 0 0 2 10

Location of Incident 1 3 0 0 0 0

Exit 4 13 4 15 3 12

Other 1 3 1 4 0 0

33 27 24

42

Icy Bridge f %

4 14

5 18

3 11

9 32

2 7

0 0

4 14

1 4

28

frequencies per cell are comparatively small for generalizing these findings

as to the effects of incident type upon a diversion decision. A larger scale

study is necessary before any conclusions can be reached. However, it may

be noted again that comparatively few subjects stopped asking questions given

any kind of incident information. Even though incident information was asked

initially by 43 percent, they typically continued to ask one or two additional

questions.

Summary

1. The nature of the incident was the first question asked by 43 per­

cent of the subjects.

2. Incident type, lanes blocked, level of congestion, and delay were

asked much more often than other types of information.

3. After three questions, 87 percent were ready to make a diversion

decision.

4. Only 14 percent could make a decision given only the type of inci­

dent.

5. The types of information which were requested most often immediately

before a decision was made, were amount of delay, lanes blocked, and

level of congestion.

6. The decision ultimately made by 74 percent of the subjects was to

divert.

43

Study 2 - Effect of Driver Familiarity

Objective

The objectives of the second study were as follows:

(a) To determine if the informational requirements of the driver differed

as a function on whether or not the driver was familiar with the

freeway segment being employed in the scenario.

(b) To determine if the familiar and unfamiliar drivers differ with

respect to the type of questions asked, the number of questions, and

the last question th~Y asked before making a diversion decision.

Method

The procedures employed in the second study were identical to the first

except that it was conducted at a shopping mall in Houston, Texas. Subjects

were randomly assigned to either the familiar or unfamiliar driver group prior

to administration of the questionnaire. The 51 subjects assigned to the fami­

liar driver group received a problem located on the Gulf Freeway, a major free­

way in Houston. The 43 subjects assigned to the unfamiliar driver group re­

ceived the same problem, but located on I-75 in Cincinnati, Ohio.

Results

As with the first study~ an analysis determined the frequency and percent­

age of questions which dealt with a particular topic and the frequencies for

each order they were asked. This data is presented for both the familiar and

unfamiliar drivers in Table A-5.

As was the case in St~dy 1, incident type was asked more frequently than

any other topic by both groups, particularly the unfamiliar drivers. The

44

Question ToDic

Type of Incident

Level of Congestion

Lane Blockage

Amount of Delay

Speed of Traffic

Location of Incident

Location of Nearest Exit

Other

TABLE A-5

FREQUENCY OF SUBJECT'S QUESTIONS BY TOPIC AREA AND ORDER FOR FAMILIAR AND UNFAMILIAR GROUPS

1 2 3 4 Total

Fam Unfam Fam Unfam Fam Unfam Fam Unf am Fam Unfam

.. i~) ----~

~~~ 7 5 0 1 0 0 26 30 /

10 5 3 1 5 2 1 0 (19-- I 8 ~ ( \ 6 5 6 \g) 1 1 0 0 c 18 _,J

5 1 3 2 2 2 0 0 5 0 .

2 1 0 0 1 1 0 2 3 -- 4

1 2 0 0 0 1 0 0 1 3

,I-\

3 3 4 7 3 0 1 1 ill/ 11 \-._J

5 2 6 4 1 5 1 0 13 11

51 43 29 31 13 13 13 3 96 90

Percent of Subjects

Fam Unfam

51 70

37 19

25 42

20 12

6 9

2 7

22 26

25 26

familiar drivers asked about congestion slightly more often, while the unfam­

iliar drivers asked about lane blockage more often. Next most often was the

location of the nearest exit (about 25 percent for each group).

Table A-5 also indicates that type of incident was more often the first

question asked by both the familiar and unfamiliar drivers. In fact, 77 per­

cent of those asking about the incident asked it as a first question. Congestion,

although asked less often, was also a first question by about 55 percent of

those asking. Lane blockage and exit information was more often the second

question, particularly by tne unfamililar group.

A comparison of the number of questions asked before a decision was made is

presented in Table A~6 for both groups. A significant difference was found be­

tween those familiar and unfamiliar drivers who were able to make a decision

after asking only one question. In this case, 43.1 percent of the familiar

drivers were able to make some decision vs. 27.9 percent for the unfamiliar.

This would tend to imply that drivers familiar with a given freeway or segment

of freeway require less information initially than unfamiliar drivers.

A comparison of the cumulative percentages with those in Study 1 indicates

that 93 percent made a decision after three questions in the Houston study,

whereas 87 percent made a decision after three questions in Study 1. In general,

it can be stated that drivers require approximately three bits of information

to make a diversion decision.

Table A-7 presents the percentage of subjects in each group who made a

diversion decision following various types of questions. The only significant

difference between familiar and unfamiliar drivers was for the congestion

category. Significantly more familiar drivers were able to make a decision

knowing the level of congestion than were unfamiliar drivers. With the noted

46

No. of Questions Asked (N)

1

2

3

4

5

TABLE A-6

PERCENTAGE OF SUBJECTS MAKING A DECISION AS A FUNCTION OF NUMBER OF QUESTIONS ASKED

Familiar

Freq of S Percentage Cumulative Freq of S Asking Only Percentage Asking Only N Questions N Questions

22 43.1 43.1 12*

16 31.4 74.9 18

10 19.6 94.1 10

3 5.9 100.0 3

0 0 - 0

51 100.0 43

Unfamiliar

Percentage

27.9

41.9

23.2

7.0

0

100.0

*X2 between familiar and unfamiliar expected frequencies = 2.94/p < .086

Cumulative Percentage

27.9

69.8

93.0

100.0

-

TABLE A-7

PERCENTAGES OF SUBJECTS MAKING A DECISION AFTER ASKING SPECIFIC TYPES OF QUESTIONS

Question Category familiar unfamiliar Study 1 unfamiliar

f % f % %

Incident 10 20 14 33 14

Congestion 14 27* 5 12* 28

Lane Blockage 7 14 3 7 16

Delay 6 11 3 7 21

Speed of Traffic 1 2 2 5 4

Location of Incident 0 0 3 7 1

Exit Location 8 16 4 10 13

Other 5 10 9 19 3

Total · 51 100 43 100 100

*x2 = p < .05

48

i

"

exception, it is apparent that the familiar and unfamiliar driver make

decisions based upon the same types of information.

Aside from the question of driver familiarity, Table A-7 also permits

a comparison of the percentage of unfamiliar subjects from this study making

a decision following a type of question with the same type of data from

Study 1, which also involved unfamiliar subjects from the Bryan-College Station

area.

The major differences noted between the two groups of subjects is that a

significantly larger percentage of Houston subjects (Study 2) made a decision

following the incident-type information, whereas smaller percentages made the

decision following lane blockage, congestion, and delay information. Exit

location information was comparable for the two studies.

There were also a greater variety of questions asked, which culminated in

a diversion decision than in the first study. Despite the difficulties in for­

mulating the question, a few subjects asked questions on the location of the

incident and a variety of miscellaneous questions.

It was determined that 73 percent of the familiar subjects and 72 percent

of the unfamiliar subjects made the decision to divert giventhe information

they requested. These values almost exactly coincide with the 74 percent who

chose to divert in the first study.

49

,,,,

Summary

1. The most frequently asked question by both familiar and unfamiliar

subjects dealt with the type of incident followed in frequency by

lane blockage, congestion, and exit information. Familiar drivers

more often asked for congestion and unfamiliar more often asked

about lane blockage.

2. 43 percent of subjects, who were familiar with the freeway and city,

made a diversion decision after only one question, whereas only 28

percent made a decision in the unfamiliar situation. The finding

of a significant difference suggests the familiar driver requires

less information initially.

3. As with Study 1, a decision to divert or not to divert was made fol­

lowing three questions. After 3 questions there was no difference

in information required by the familiar and unfamiliar driver to make

such a decision.

4. Familiar drivers more often than unfamiliar drivers made a diversion

decision following being given congestion information. Otherwise,

the two groups required essentially the same types of information

and thereafter made decisions in approximately the same manner.

5. A significantly larger percentage made a decision after incident

information only than did the subjects in Study 1. However, lane

blockage, congestion~ and delay information were less important to

a diversion decision than in Study 1.

6. The Houston subjects asked a greater variety of questions than did

the local subjects in Study 1.

50

7. Approximately three-fourths of the subjects decided to divert. Degree

of familiarity did not affect the percentage making this decision.

51

Study 3 - Effect of Traffic Problem Severity

Objective

The objective of the third study was to determine if the infonnational

requirements of the drivers were altered when the traffic problem posed was

mild.

Background

In Studies 1 and 2, the scenarios contained descriptions of severe traf­

fic problems. The subjects received an affirmative answer only if they antic­

ipated that the congestion was heavy; the traffic speed had been reduced to

10 mph or less; the delay time was 20 minutes; two lanes were blocked, etc.

(See Figure A-1.)

It was hypothesized that the severity of the problem might be a variable

which would affect the number and types of questions asked. For example,

Topic Area G results indicate that a delay of 20 minutes resulted in a report

of 60 percent diversion regardless of the traffic state information. Therefore,

it was necessary to test to ~ee to what degree a milder traffic problem might

result in either additional questioning or perhaps an early decision not to

divert.

Method

The third study was conqucted with 83 subjects in Houston employing the

unfamiliar mode of Study 2. Administration was at a licensing bureau.

Subjects were randomly assigned to either a mild problem or a severe problem

group. The procedures were identical to those used in Studies 1 and 2

with the exception of the changes in the scenario for the mild problem

group. The severe problem group used the same scenario as in Studies 1 and 2.

52

They were told congestion was heavy; traffic speed was 10 mph or less; delay

time was 20 minutes and 2 of 3 lanes were blocked.

The following information was given to the mild traffic group when a

subject asked a question regarding certain traffic descriptors:

Congestion - light

Traffic speed - 40 mph

Delay time - 2 minutes

l of 3 lanes blocked

The first two conditions effectively pose no problem at all. The delay

condition poses only a moderate annoyance to which very few would divert.

The one lane blocked would also not be too severe during the off-peak con­

dition posed.

If a subject anticipated a severe traffic problem, he would be told

11 No 11 and then be given the true state of affairs. (Since they were told

there was a problem ahead, the subjects might be more likely to anticipate

the more severe problem).

This study investigated a mild traffic problem only with respect to

the above descriptors. If a subject asked a question on type of incident

he was given this information as in the previous studies. In the event the

incident alone should be sufficient for a diversion decision, the subject

would not learn the actual mild state of traffic. However, the previous

research had indicated that few subjects decided after a single question

and, therefore, subjects would likely discover the mild traffic conditions

through further questioning.

53

Results

The initial analysis involved a comparison of the number of questions

reQuired to make a decision for the mild conditions group and the severe

conditions group. The results are presented in Table A-8 along with Study l

and 2 results for severe proplems, unfamiliar drivers. As can be seen, no

significant difference was fpund between these two groups 1n Study 3 when

a proportions test was applied ·to this data. This finding is interpreted

to mean that problem severity did not alter the number of questions asked

before deciding to divert. 93 percent of the subjects in the mild group

and 98 percent in the severe group were able to make a decision after only

three questions, a finding which confirms the results of Studies l and 2

that only three bits of information are required.

Table A-9 presents another comparison between the mild and severe prob.,.

lem groups in regard to the first question asked (column 1) and the frequen-

cies with which topics were asked as the second, third, or fourth question.

Again, type of incident was predominantly the first question for both' the

severe and mild problem groups.

The total frequencies of incident categories for the mild problem and

severe problem are also shown in Table A-9. A proportions test was applied

to the respective totals. The only significant differences were for type of

incident questions which were asked significantly more often by the severe

problem group than the mild problem group. This finding might be interpreted

that incident information only was more important when the motorist was trav­

eling in severe traffic than in mild traffic.

54

NUMBER OF QUESTIONS

1 2 3 4 5 6

TABLE A-8 PERCENTAGE OF UNFAMILIAR DRIVERS MAKING DECISIONS AS

A FUNCTION OF THE NUMBER OF QUESTIONS ASKED AND TRAFFIC PROBLEM SEVERITY

SEVERE PROBLEM LIGHT PROBLEM STUDY 1

f Percent Cumulative f Percent Cumulative Percent

17 40 40 12 1 29 29 33 14 33 73 162 39 68 35 11 25 98 10 25 93 19 0 0 0 2 5 98 7 0 0 0 1 2 100 6 1 2 100 0 0 -- 0

43 100 41 100 100

izP = 1.06/p < .29

2 zP = o.57/p < .57

STUDY 2

Percent

28 42 23 7 0 0

100

U'1 O"I

QUESTION TOPIC

Severe Problem

Type of inci.dent 31

Level of congestion 3

Lane blockage 4

Amount of delay 0

Traffic speed 0

Incident location 0

Exit location 2

Return point 0

Other 3

1z = 2.49/p < .016 2 z = o.88/p < .38

l Light

Problem

15

3

8

5

2

3

l

0

4

TABLE A-9 FREQUENCIES OF QUESTIONS ASKED BY

TOPIC, ORDER, AND PROBLEM SEVERITY

QUESTION ORDER

2 3

Severe Light Severe Light Severe Problem Problem Problem Problem Problem

3 4 2 2 0

3 5 2 3 0

6 6 3 2 0

4 4 1 1 O·

1 1 0 2 0

0 3 0 0 1

2 1 0 0 0

0 0 1 0 0

8 5 2 3 0

TOTAL 4

Light Severe Light Problem Problem Problem

1 36 22 1

l 8 122

0 13 16

0 5 10

0 l 5

0 1 6

1 4 3

0 1 0

0 13 12

82 86

As expected, the severity of the traffic information did affect the

percentage of subjects who elected to divert. 49 percent of the subjects

in the mild group elected to divert, while 84 percent of those in the

severe group decided the situation merited diversion.

Summary

1. Mild traffic problem descriptions did not result in significantly

more or fewer subjects asking a second question than did severe

traffic problem desGriptions.

2. A decision was made by over 90 percent after three questions, regard­

less of severity.

3. Type of incident was JOOst often the first question asked by both

groups. It was the only question asked more often by the severe

traffic group than the.mild traffic group.

4. As expected, level of severity did affect the percentage diverting.

Approximately half (49 percent) of those in the mild group elected

to divert, while 84 percent of those in the severe group stated they

would divert.

Conclusions

By reviewing the findings of the three studies in relation to the objec­

tives of the topic area, several conclusions emerge:

1. The critical classes of infonnation for a diversion decision frequently

include the nature of the incident, lane blockage, level of congestion,

and delay. Traffic speed and travel time were seldom asked. (See

Table A-10.)

57

TABLE A-10

FREQUENCY OF QUESTIONS ASKED (ALL STUDIES)

Question Study Study Study Totals Topic 1 2 3

Incident 60 56 58 174

Lane Blockage 48 31 29 105

Congestion 41 17 20 78

Delay 38 15 15 68

Exit Location 22 22 7 51

Incident Location 7 2 7 16

Speed 12 7 5 24

58

2. The type of incident was asked most often in all studies. Higher per­

centages of Houston subjects asked this question than did the local

subjects.

3. In all studies, incident information was more frequently the first

question. However, it was not sufficient infonnation. Less than a

third made a diversion decision following information on the nature

of the incident.

4. The studies are in agreement that th~ee units of information can

satisfy the infonnational needs of drivers, regardless of familiarity

with the freeway ano regardless of the severity of the traffic state.

One of these types of infonnation is the nature of the incident, but

the other two varied considerably.

5. A decision on whether or not to divert was made most often after con­

gestion and delay in Study 1 and after incident and congestion in

Study 2.

6. More familiar subjects than unfamiliar subjects made a decision fol­

lowing the asking of only one question suggesting the familiar driver

requires initially less information to decide.

7. Regardless of familiarity, type of incident was asked most often.

However, familiar drivers asked about congestion second most often.

Also, level of congestion was mentioned more often just prior to a

decision by the subjects given the familiar Gulf Freeway and Gulfgate

Shopping Center as the location of the problem, than by subjects

given a location of the problem in a distant city. Presumably, the

familiar group could react in terms of their own driving experiences

on this freeway, whereas when they were placed in an unfamiliar city,

59

they relied more on the incident descriptor.

8. Knowledge that the traffic state was mild did not alter the number of

questions asked. However, type of incident was asked more often by

those who were told the traffic state was severe than those told it

was mild. Apparently, given they asked other questions first, there

was less need for the mild traffic group to inquire further as to the

nature of the incident.

9. It should be recalled that in the instructions, subjects were told

that the sign dealt with a "problem ahead" and questions were to

address the freeway problem. (See instructions.) Therefore, this

study is not an investigation of the extent to which variables other

than traffic state - such as alternate route characteristics, bypass.

distance, and return point - are entertained in making a diversion

decision.

It should be noted that this study, although listed as Topic Area A, was

not the first study conducted. Had it been conducted initially, greater impe­

tus would have been placed on the area of incident-type descriptors than

reported in Topic Area G. However, the studies did confirm earlier research

which suggested that traffic speed and travel time were not major questions

which come to mind in a diversion decision and, therefore, did not merit the

research attention of the other variables.

10. In summary, the findings of the three studies are clear that three

pieces of information is adequate and the display of all types of

traffic state information is unnecessary. These studies and others

(Topic Area J) clearly support the finding that the first piece of

information should be a statement of the problem or incident. The

60

effects of the problem on traffic should also be described in some

manner with level of congestion and lane blockage being methods with

which the driving public is familiar in traffic advisories and ones

which can easily be believed are measurable, at least in categorical

terms.

The results of this study indicate that research should focus on the most

effective methods of communicating the following:

1. Nature of the incident

2. Extend of lane blockage

3. Level of congestion

4. Temporal information, especially delay.

Design Recommendations

This series of studies was conducted to assess priorities of different

categories of sign information, rather than to define detailed message design.

However, several general conclusions can be made relative to display of traffic

state information which would affect a diversion decision.

1. Display at most three units of traffic state information.

2. One unit of information will be insufficient (unless possibly ampli­

fied by an advisory to divert--a variable not investigated in this

topic area). If only traffic state information were to be displayed,

at least two descriptors are recommended.

3. Display first the nature of the incident.

4. Other traffic state information which may be displayed are the extent

of lane blockage, the level of congestion, and temporal information,

such as delay. Information, such as travel time and traffic speeds,

61

are redundant and should not be displayed for this purpose.

5. Exiting information may also be displayed.

6. With commuters (and especially when the traffic condition is severe),

it is important to display level of congestion. Either congestion,

lane blockage, or delay should be displayed immediately after the

type of incident.

62

V. TOPIC AREA B - TRAFFIC STATE DESCRIPTORS

Objectives

To determine the number of levels of traffic operation which can be

discriminated by drivers and establish a suitable vocabulary for each of

those levels. Specifically:

(a) To determine the number of traffic states which can be reliably

discriminated by drivers.

(b) To establish driver preferences for nomenclature describing extreme

traffic states.

(c) To determine the optimal verbal descriptors for the levels of

traffic states between the extremes.

Background

One function of changeable message signs is to provide an up-to-the minute

message about the state of traffic ahead of the driver but as yet undiscernable

to him. How much detail must the driver have to "get the message"? Detail

(i.e., number of different states the sign can display) costs money. Detail may

also lead to confusion if it is excessive and not explicit enough. The Highway

Capacity Manual (l) identifies six levels of service. A major question is,

"How many different states of traffic operations will most drivers recognize?"

In psychological terms, "How many levels of traffic density can drivers set up

on an absolute judgment basis?"

Various changeable message signing installations around the country have

adopted anywhere from two states (some variant of congested-uncongested, or,

in other words, "a problem for you - not a problem for you") up to 6 and more.

Before a vocabulary for expressing these states of traffic could be investigated

63

or even postulated, the number of states that had to be handled by this

vocabulary had to be established. What words, phrases, symbols do drivers

tend to associate with good and poor states of traffic operation?

Terms 1 i ke CONGESTION, FREEWAY BREAKDOWN, SLOW TRAFFIC are used or

proposed in several combinations at various installations (2). Which of

these terms reliably associated with either good or poor conditions of

operation, and how well does each term express that condition of operation

were questions that could be addressed in the laboratory.

Two words appear over and over again, not only in the literature but

in casual conversations with drivers: CONGESTION and TRAFFIC. The dictionary

defines CONGESTION as a state of blocking, obstructing, or otherwise affect­

ing a roadway by an overaccumulation or overcrowding of vehicles. TRAFFIC

means the flow of vehicles along a street or highway.* But these distinctly

different words with accompanying modifiers appeared to be used interchange­

ably by drivers. Examples are HEAVY TRAFFIC and HEAVY CONGESTION. Are they

regarded as synonymous, or does one phrase imply a higher level of 11 over­

crowdi ng 11 than the other?

*Webster's New Collegiate Dictionary. G. & C. Merrian, 1960.

64

Study 1 - Number of Discriminable Traffic States

Objective

The primary objective of Study 1 was to establish how many different

levels of traffic states a driver can discriminate or identify between a

nearly empty freeway and one jammed to immobility.

Method

Eighty-nine subjects were presented two slides: one depicted a nearly

empty freeway; the other one nearly full. Then 12 slides of the same freeway

with different levels of traffic states were presented. These levels were

intermediate between the two anchor slides. Subjects graded each slide on a

continuum anchored at either end of the first two slides. Anchoring was

accomplished by the following instructions to the subjects:

"Imagine yourself on a freeway such as you see here(moderate level of

traffic slide presented) ... as you travel near this city, you may encounter

a freeway like this (near empty freeway slide) or you may encounter a

freeway like this (jammed freeway slide). You have a sheet of paper in

front of you. On it are 14 lines. Note that the first line has a mark for

the slide on the left already on it. On line 2, place a similar mark at

the opposite end of the line for the slide on the right. These lines are

a kind of measuring stick of the situations you might find on this freeway.

Now you have two extremes of these freeways.

"We're going to show y_ou some more pictures of freeway situations. They

are all of the same freeway as you see now, but taken at different times

during the day. We 1 d like you to place a mark on each line where you think

it belongs, between the left-hand situation and the right-hand situation. 11

65

This study is thus a simple experiment in absolute scaling of traffic

state as perceived on a static depiction (slides). It was conducted in / . ~

College Station and then replicated in Houston to determine whether there

are any differences between drivers who do not drive urban freeways daily

and those who do.

Twelve different slides of a facility (1-10 in San Antonio) taken

at different times of day and levels of traffic states were used in the study.

Grading was by counting the number of vehicles in the 2 lanes visible in the

picture (driver viewpoint lanes orily, not opposing traffic). Two extra slides

were used for anchors, one depicting the freeway with only 3 cars visible, the

other a congested state, with brake lights showing (30 cars). Table B-1

shows the car count in each slide and consequent rank. Ranking was back­

stopped by paired-associate comparisons by staff members since some slides

had the same number of visible vehicles yet appeared to be at different

states of operation. The four orders of presentation of these 12 stimulus

slides were randomized.

Results

Responses (marks along the line associated with each slide) were

categorized into 12 equal intervals, under an assumption that if 12 levels

of operation could be discriminated on an absolute basis, then each of

the 12 intervals would be selected with an equal frequency .. · A frequency

count of marks appearing in each of the twelve intervals was then accumulated

and is depicted in Figure B-l.

The results reveal that there was essentially no difference in the

response by the Houston subjects and the subjects in College Station.

66

TABLE B-1

SLIDE SPECIFICATION OF FREEWAY TRAFFIC STATES

SLIDE NO. COUNT OF CARS ON FREEWAY RANK

Anchor Lo

1 3 1

2 4 2

3 5 3

4 6 4

5 <10* 5.5

6 >10 5.5

7 <11 7.5

8 > 11 7.5

9 17 9

10 <19 10.5

11 >19 10. 5

12 24 12 . Anchor 30 Hi

* Where car count same, lower ranked ·slide had cars more widely spaced - subjective evaluation.

67

:i

t-z w <....> 0:: w 0...

t­z w <....> 0:: w 0...

25

20

15

10

5

25

20

15

10

5

Houston (N=60)

Co 11 ege Sta ti on (N=89)

2 3 4 5 6 7 8 9 10 11 12

CONTiNUUM - EQUAL INTERVALS

, ___ Combined Data (N=149)

2 3 4 5 6 7 8 9 10 11 12

CONTINUUM - EQUAL INTERVALS

FIGURE B-l Scaling With Respect To Levels

of Traffic Operation

68

Subjects tended to cluster.their absolute judgments of level of traffic

operation within the confines of this study either to the low or to the high

end of the continuum along which they were asked to scale each slide. This

dichotomous trend appears to be buffered by the existence of a central or

intermediate classification. Thus drivers both commuters and noncorrmuters,

on the basis of this study, seem to visualize or perceive traffic in terms

of three states.

Discussion

The interpretation of this study is that when drivers find themselves

in the midd1e of traffic they do not make fine discriminations among different

levels of traffic operations, but tend to think in terms of three levels of

traffic states. A corrmuter during the peak period, for example, would discern

three levels of operation. A driver traveling during the off peak period

would also think in terms of three levels. However, these levels of operation

may be different from those of the commuter. Study 1 was not intended to

determine these differences.

Another question not addressed in this study was the role traffic move­

ment plays in judging level of traffic operation. The scenes displayed to the

subjects were static photographs and not motion picture clips. It is possible

that more states are evoked between congestion displayed by motion pict~re

and congestion illustrated on a slide.

69

Study .2 - Descriptors for Extreme Traffic States

Objective

The objective of this experiment, which was carried out in C'njunction

with Study 1, was to establish driver preferences for the words, phrases,

or symbols denoting extreme traffic states that various jurisdictions have

been using on a routine or experimental basis.

Method

Eighty-nine subjects were shown two extremes of traffic conditions (the

same 2 11 anchor 11 slides used in Study 1). They were instructed to judge each

of 28 different signs with respect to 1) whether the sign referred to a low

extreme traffic density state or to a high extreme state, and 2) how well

the sign expressed that state along a continuum from 11 bad 11 to 11 good. 11

Subjects viewed the two 11 extreme 11 slides all the way through the experi­

ment. The stimulus slide with a word, phrase, or symbol on it appeared just

below the 11 extremes 11 slides on the rear-projection screen in the laboratory.

Table B-2 lists the words, phrases or symbols that were presented to the

drivers. Each was presenteq as a white-lettered sign on a green background.

The order of presentation of these slides was in 4 different random orders. /

This study was run in College Station only. Eighty-nine subjects

participated.

Results

Each word or word equivalent was scored in two ways: 1) proportion of

correct response (i.e., associated with the extreme it is attempting to express)

70

TABLE B-2 NOMENCLATURE FOR EXTREME TRAFFIC STATES

Low Traffic Density State

FREE FLOWING TRAFFIC

FREE MOVING TRAFFIC

FREEWAY GRADE-A

FREEWAY OK

FREEWAY OPEN

LIGHT TRAFF! C

NO CONGEST! ON

NO DELAY

NORMAL TRAFF! C

UNCONGESTED

•••* (BLANK SIGN)

(GREEN BEACON)

* Three white dots shown on sign

71

High Traffic Density State

CONGESTED TRAFFIC

CONGESTION

DELAY

EXTRA DELAY

FREEWAY BREAKDOWN

FREEWAY GRADE-F

FREEWAY JAMMED

HEAVY CONGESTION

HEAVY TRAFFIC

JAMMED TRAFFIC

PREPARED TO STOP

SLOW TRAFFIC

STOP-AND-GO TRAFFIC

TRAFFIC JAM

(RED BEACON)

and 2) frequency count of subjects who scored that word above midpoint

of the 11 bad-good 11 continuum.

The results for the low traffic state messages and the high traffic

state messages are presented in Tables B-3 and B-4. The choice frequency

represents the number of subjects that rated a particular descriptor above

the midpoint of the "bad-good" continuum.

For the low traffic state messages, LIGHT TRAFFIC and UNCONGESTED was

rated on the "plus" side by 62 and 61 of the 89 subjects. In contrast, only

2 subjects rated the three dots on the plus side. Other descriptors rated

low were the "Green Light" and the "Blank Sign" which were rated above the

midpoint by only 6 and 9 subjects--not too unexpected. These three descriptors

also resulted in the most errors. Other descriptors receiving relatively

low scores were FREEWAY GRADE A (20)' NORMAL TRAFFIC (28)' and FREEWAY OK (29).

The results for the high traffic state messages shown in Table B-4 re­

veal that the choice frequency for the descriptors ranged between 72 and 11.

HEAVY TRAFFIC, CONGESTED TRAFFIC, and CONGESTION were the three top choices.

The "Red Beacon" sign and the FREEWAY GRADE F descriptor were the least pre­

ferred having been rated above average by only 12 and 11 of the 89 subjects.

The greatest number of errors, 17 and 15, were associated with FREEWAY GRADE

F and PREPARE TO STOP. As an afterthought, it is questionable whether PREPARE

TO STOP is consistent with the other descriptors used and probably should not

have been included in the study.

Table B-5 presents the results of this study in terms of the proportion

of correct interpretations and proportion of ratings above midpoint of the

"bad-good" scale. A composite score for each message was derived by combining

72

TABLE B-3 LOW TRAFFIC STATE MESSAGES (N = 89)

Choice Number Frequency* Message Errors

51 FREE FLOWING TRAFFIC 12

52 FREE MOVING TRAFFIC 10

20 FREEWAY GRADE-A 11

29 FREEWAY OK 6

40 FREEWAY OPEN 8

62 LIGHT TRAFFIC 3

55 NO CONGESTION 3

48 NO DELAY 9

28 NORMAL TRAFFIC . 11

61 UNCONGESTED 3

2 •• •*~ 44

9 (BLANK SIGN) 31

6 (GREEN BEACON) 22

* Frequency is the number of ratings above midpoint on an unstructured scale.

~)(- -rtt ~ 1.A-14_~ f-..c- cl:, ..J-~ S f...o .__.., t!>...., S C.1"..-cL ...

73

TABLE B-4 HIGH TRAFFIC STATE MESSAGES (N = 89)

Choice Number Freguency* Message Errors

71 CONGESTED TRAFFIC 4

68 CONGESTION 1

37 DELAY 1

31 EXTRA DELAY 2

33 FREEWAY BREAKDOWN 2

11 FREEWAY GRADE-F 17

53 FREEWAY JAMMED 3

63 HEAVY CONGESTION 4

72 HEAVY TRAFFIC 5

49 JAMMED TRAFFIC 1

42 PREPARE TO STOP 13

51 SLOW TRAFFIC 7

45 STOP-AND-GO TRAFFIC 5

60 TRAFFIC JAM 1

12 (RED BEACON) 8

* Frequency is the number of ratings above midpoint on an unstructured scale.

74

MESSAGE

Low State LIGHT TRAFFIC UNCONGESTED NO CONGESTION FREE MOVING TRAFFIC NO DELAY FREE FLOWING TRAFFIC FREEWAY OPEN FREEWAY OK NORMAL TRAFFIC FREEWAY GRADE-A (GREEN BEACON) (BLANK SIGN) •••

High State CONGESTION CONGESTED TRAFFIC HEAVY TRAFFIC TRAFFIC JAM HEAVY CONGESTION FREEWAY JAMMED JAMMED TRAFFIC SLOW TRAFFIC STOP-AND-GO TRAFFIC DELAY. FREEWAY BREAKDOWN EXTRA DELAY PREPARE TO STOP (RED BEACON) FREEWAY GRADE-F

TABLE B-5 RANKINGS OF DESCRIPTORS FOR LOW AND HIGH TRAFFIC STATES

A B % RATING % CORREC COMPOSITE SCORE

ABOVE MID PT.

70 97 A+ B = 167 . 69 97 166 62 97 159 58 89 147 54 90 144 57 86 143 45 91 136 3~ 93 126 31 88 119 22 88 110 07 75 82 10 65 75 02 51 53

76 99 A+ B = 175 80 95 175 81 94 175 67 99 166 71 95 166 60 97 157 55 99 154 57 92 149 51 94 145 42 99 141 37 98 135 35 98 133 47 85 166 13 91 104 12 81 93

75

COMPOSITE RANK

l 2 3 4 5 6 7 8 9

10 11 12 13

l 1 1 4 4 6 7 8 9

10 11 12 13 14 15

both scores additively. The composite score is merely a method by which

the messages for the low traffic state and for the high traffic state can

be ranked.

It is difficult to determine which of the messages are the best based

only on the composite rank shown in Table B-5. However, the data indi-

cate the types of descriptors that could have been eliminated from further con­

sideration because of their high frequency of errors and low ratings by the

subjects. For the low traffic state, the following descriptors appear to be

unacceptable:

••• (GREEN BEACON)

(BLANK SIGN)

FREEWAY GRADE A

The following descriptors appear to be unacceptable for the high traffic state:

FREEWAY GRADE F

(RED BEACON)

Although the above coded descriptors were found to be unacceptable at this

stage of the research program, they were included in other supportive studies

discussed in subsequent sections of this report. These additional studies

verified the ambiguity of the coded messages in the form presented above

and the high degree of confusion with respect to driver interpretation.

The reader is reminded that the subjects viewed each sign once. Thus

they would be judging the signs as an unfamiliar driver would as he sees the

message for the first time. The above descriptors considered to be unacceptable

are coded messages that are qpparently difficult for drivers to decipher without

some additional information.

76

Study 3 - Verbal Descriptors of Level Service

Objective

To determine verbal descriptors assigned to various levels of traffic

state.

Method

Another approach for associating messages with levels of traffic

operation is to match varying levels with the messages. This approach

permits developing some icteas as to how to gradate messages as traffic

changes occur during an operating period. Specifically, Study 3 attempted

to establish verbal traffic descriptors associated with six levels of

service shown pictorially.

Drivers were told they were viewing a prediction of traffic ahead while

they were on a rest stop in a fast-food--souvenier shop outside Houston,

Texas. An array of six slides were presented, each depicting a different

1 evel of traffic service. The array showed a freeway jammed full, and 5 other

pictures showing levels down to an almost empty freeway.

Subjects viewed each message in successive random order (4 different

orders were used in the study). The six pictures of freeway conditions were

displayed during the entire experiment. The pictures were 35 mm slide frames

randomly spliced together into a 3 1/4 x 4 lantern slide frame. The pictures

range from a low traffic density state, 11 111, to a high traffic density state,

11 611• Projection was with a theatre-type "magic 1antern. 11

77

Subjects checked off squares on the data sheet arranged spatially li1 ~

the six pictures on the screen before them. They checked off as many pictures

as they thought were represented by the message presented immediately below

the traffic state array. Then they designated by encircling the appropriate

square which picture was best expressed by the message. The preliminary

checkoff was primarily to ease the frustration around in forced-choice exreri-

ments where many matches might be made; the checkoff sets the stage for the

final selection of the actual match.

The candidate messages presented to subjects for matching are listed

in Table B-6. These messages were configured as in Study 2: white lettering

on a green background.

One hundred and six subjects participated in the laboratory study in ~ ~

College Station. The· study was then replicated in Houston to determine

differences between commuters in a large city and non-local drivers (College

Station). Forty-three subjects participated in the Houston study.

Results

The frequencies of driver association of the candidate descriptors to the

six traffic states for the College Station data are shown in Table B-7. As

can be observed from the data, there were major discrepancies in the results.

For example, 8 subjects associated the VERY CONGESTED descriptor with picture

l which illustrated a near empty freeway. Likewise, 8, 7, 6, and 5 subjects

associated the HEAVY TRAFFIC, DELAY, HEAVILY CONGESTED, and JAMMED TRAFFIC

descriptors with picture 1. Similar discrepancies are noted throughout the

other pictures. A closer ex&mination of the data revealed that several subjects

78

TABLE B-6 CANDIDATE TRAFFIC STATE DESCRIPTORS

MESSAGES

CONGESTED

DELAY

EXTRA DELAY

FREE FLOWING TRAFFIC

FREEWAY JAMMED

FREEWAY OK

HEAVILY CONGESTED

HEAVY TRAFFIC

JAMMED TRAFFIC

LIGHT TRAFFIC

MODERATELY CONGESTED

MOVING WELL

NO DELAY

NORMAL TRAFFIC

s~ow TRAFFIC

STOP-AND-GO TRAFFIC

UNCONGESTED

VERY CONGESTED

79

TABLE B-7 FREQUENCY OF DRIVER ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

COLLEGE STATION

Traffic Density States Descriptor (Low) 1 2 3 4 5 6 (High)

CONGESTED 3 8 3 7 15 65

DELAY 7 3 3 6 10 77

EXTRA DELAY 5 5 4 5 8 75

FREE FLOWING TRAFFIC 54 19 10 9 8 5

FREEWAY JAMMED 5 5 2 l 5 85

FREEWAY OK 54 32 8 1 3 4

HEAVILY CONGESTED 6 3 1 4 13 79

HEAVY TRAFFIC 8 2 2 1 17 72

JAMMED TRAFFIC 5 3 1 3 5 87

LIGHT TRAFFIC 56 30 7 4 3 4

MODERATELY CONGESTED 5 8 13 39 35 2

MOVING WELL 40 28 13 12 5 4

NO DELAY 57 28 3 3 4 6

NORMAL TRAFFIC 22 11 26 28 3 10

SLOW TRAFFIC 12 10 6 3 6 56

STOP-AND-GO TRAFFIC 12 5 5 5 14 64

UNCONGESTED 61 27 4 4 1 6

VERY CONGESTED 8 6 6 1 6 77

80

N

101

106

102

105

102

102

106

102

104

104

102

102

101

100

93

105

103

104

for one reason or another did not properly follow instructions in the labora­

tory. In an attempt to obtain a representative educational destribution in

the experiments, several subjects were solicited by the researchers from the

cleaning and repair groups at Texas A&M. This study was among the first

conducted in the laboratory, and it was not recognized until after this study

that the majority of this lower educated group were not able to properly

follow instructions. The schedule of the research did not allow for individ­

ual testing where the experi~ent could be administered to each individu~l

separately. Thus,the researchers had to be more selective in the subsequent

studies.

The data for Study 3 were screened to remove those answer sheets where

the subjects did not follow instructions. The revised data are shown in

Table B-8. The results of the Houston study are shown in Table B-9.

The data were analyzed to determine patterns of association. One approach

is to evaluate the position of the median frequency {50th percentile) in

relation to the six traffic state pictures. This association is presented in

Table B-10.

The analysis of the median values produced some interesting results.

For the words provided to the subjects, the College Station drivers tended

to associate the words with either the low traffic density state {picture l)

or the high state {picture 6), with two exceptions: NORMAL TRAFFIC was asso­

ciated with the third traffic state and MODERATELY CONGESTED with the fourth.

An examination of Table B-8 reveals that the College Station drivers tended

to associate NORMAL TRAFFIC throughout the six traffic state spectrum. This

indicates that the term is quite confusing to drivers from small cities.

81

TABLE B-8 FREQUENCY OF DRIVER ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

COLLEGE STATION (REVISED)

Traffic Density States

Descriptor (Low) 1 2 3 4 5 6 (High)

CONGESTED 1 1 1 2 8 49

DELAY 1 0 1 2 4 54

EXTRA DELAY 1 0 2 1 3 55

FREE FLOWING TRAFFIC 41 10 9 2 0 0

FREEWAY JAMMED 0 0 0 0 0 62

FREEWAY OK 43 17 2 0 0 0

HEAVILY CONGESTED 0 0 0 0 4 58

HEAVY TRAFFIC 1 1 1 0 7 51

JAMMED TRAFFIC 0 0 0 0 1 60

LIGHT TRAFFIC 43 15 2 2 0 0

MODERATELY CONGESTED 0 2 11 33 15 1

MOVING WELL 33 15 7 6 1 0

NO DELAY 46 14 1 1 0 0

NORMAL TRAFFIC 13 8 18 16 3 4

SLOW TRAFFIC 4 5 2 2 7 41

STOP-AND-GO TRAFFIC 0 0 3 2 7 50

UNCONGESTED 44 17 1 0 0 0

VERY CONGESTED 0 0 1 0 1 60

82

N

62

62

62

62

62

62

62

61

61

62

62

62

62

62

61

62

62

62

TABLE B-9 FREQUENCY OF DRIVER ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

HOUSTON

Traffic Densit~ States Descriptor (Low) 1 2 3 4 5 6 (High)

CONGESTED 0 0 0 0 22 21

DELAY 0 0 1 1 15 26

EXTRA DELAY 0 0 3 3 15 22

FREE FLOWING TRAFFIC 20 10 7 5 0 1

FREEWAY JAMMED 0 0 2 0 15 25

FREEWAY OK 18 17 3 0 5 0

HEAVILY CONGESTED l 0 5 0 9 25

HEAVY TRAFFIC 0 0 3 2 17 18

JAMMED TRAFFIC 0 0 1 0 10 28

LIGHT TRAFFIC 15 18 3 2 0 2

MODERATELY CONGESTED 0 0 8 19 10 0

MOVING WELL 17 10 8 6 1 1

NO DELAY 17 22 2 l 0 1

NORMAL TRAFFIC 3 l 9 20 6 2

SLOW TRAFF! C 0 1 5 5 16 13

STOP-AND-GO TRAFFIC 0 1 5 1 18 18

UNCONGESTED 20 18 1 2 0 2

VERY CONGESTED 0 0 0 0 14 29

83

N

43

43

43

43

42

43

40

40

39

40

37

43

43

41

40

43

43

43

TABLE B-10 SUMMARY OF DRIVER ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - MEDIAN VALUES

Traffic Density State

(Low) 1 2 3 4 5 6 Hiqh)

College

NORMAL TRAFF! c I MODERATEL y . Station

FREE FLOWJNG CONGESTED TRAFFIC CONGESTED DELAY

FREEWAY OK EXTRA DELAY LIGHT TRAFFIC FREEWAY JAMMED MOVING WELL HEAVILY CONGESTED NO DELAY HEAVY TRAFFIC UNCONGESTED JAMMED TRAFFIC

SLOW TRAFF! C STOP-AND-GO TRAFFIC VERY CONGESTED

Houston FREE FLOWING NORMAL TRAFFIC CONGESTED DELAY

TRAFFIC MODERATELY HEAVY TRAFFIC EXTRA DELAY FREEWAY OK CONGESTED SLOW TRAFFIC FREEWAY JA~~MED I LIGHT TRAFFIC STOP-AND-GO HEAVILY CONGESTED MOVING ,,WELL TRAFFIC JAMMED TRAFFIC NO DELAY VERY CONGESTED UNCONGESTED

For the Houston subjects the median value of the six low density traffic

states was associated with picture 2 rather than picture 1, in contrast to the

College Station sample. The Houston subjects• concepts of lighter traffic

states apparently encompasses a broader range of traffic flow than that of

the College Station subjects. This is probably due to their greater experience

with commuting on freeways in a large city. Of major interest was that the

Houston drivers tend to make finer associations at the higher traffic density

levels. The descriptors CONGESTED, HEAVY TRAFFIC, SLOW TRAFFIC, and STOP­

AND-GO TRAFFIC were viewed as not representing as severe a traffic state as

DELAY' EXTRA DELAY' FREEWAY JAMMED, HEAVILY CONGESTED, JAMMED TRAFFIC' and

VERY CONGESTED.

85

... .- .

Study 4 - Verbal Descriptors of Level of Service - Follow-up

Objective

This study was a further attempt to determine relative association of

descriptors to various degrees of traffic states, but using a sounder method­

ology than Study 3.

Method

The experiment was initially run in College Station involving 151 sub­

jects in a card-sort routine and was later replicated in Houston, St: Paul,

and Los Angeles with minor modifications. The number of subjects partici­

pating in the regional studies were 108 in Houston, 143 in St. Paul, and 142

in Los Angeles. Subjects were told that a traffic scene being projected on

the laboratory screen might represent a freeway situation they could encounter

on any Wednesday morning in their city. ( 11 Houston 11 was used for the College

Station subjects). They were then told that words on 3 x 5 index cards might

describe the conditions ... or they might not. The subjects were then asked to

sort the cards for those that described worse conditions than that depicted in

the slide. Then they were asked to sort the remaining cards for those that

were felt to describe conditions better than that shown in the slide.

With the cards that then remained subjects were instructed to rank order

the cards with respect to describing the slide of traffic state (ties were per­

mitted) .

Two independent variables were part of this study. Several messages, each

on a 3 x 5 index card, were given to the subjects in a packet arranged in random

order. The other between-groups variable was the level of traffic service

86

displayed by a slide on the screen. The following three levels, from a rela­

tively light freeway traffic state to a freeway heavily congested, were used:

Slide 1 Slide 2 Slide 3

Each group of subjects at a particular study site viewed only one of the above

traffic scenes.

The initial set of 12 traffic descriptors for the laboratory studies con­v

ducted in College Station are shown in Table B-11. As results became available

from related laboratory and other associated studies, additional potential

descriptors were identified and added to the studies conducted in Houston, ............ .........-St. Paul, and Los Angeles. Eighteen descriptors were studied in Houston, 38

in St. Paul, and 41 in Los Angeles. These descriptors are also presented in

Table B-11.

The following is a summary of the number of subjects viewing each of the

traffic states:

Slide 1 Slide 2 Slide 3

College Station 52 41 58 Houston 34 27 48 St. Paul 62 25 55 Los Angeles 44 37 55

192 130 216

Results

Table B-12 summarizes the combined responses from the College Station,

Houston, St. Paul, and Los Angeles studies.

87 I -- I

As such, the data presents response

TABLE B-11 CANDIDATE TRAFFIC STATE DESCRIPTOR MESSAGES

IDENTIFIED BY STUDY LOCATION*

College Descriptors Station Houston St. Paul

LIGHT CONGESTION x x x f.DDERATE CONGESTION x x x HEAVY CONGESTION x x x UNCONGESTED x x x CONGESTED x x x VERY CONGESTED x x x LIGHT TRAFFIC x x x f.DDERATE TRAFFIC x x x HEAVY TRAFFIC x x x FREE FLOHING TRAFFIC x x x STOP AND GO TRAFFIC x x x JAMMED TRAFFIC x x x FREEWAY OK x x NO DELAY x x DELAY x x EXTRA DELAY x x MOVING WELL x x tlOBMAL IB8EEIC x x FREE MOVING TRAFFIC x FREEWAY OPEN x FREEWAY CLEAR x MOVING AT SPEED LIMIT x NO CONGESTION x CONGESTION x MODERATELY CONGESTED x CONGESTED TRAFFIC x HEAVILY CONGESTED x SLOW TRAFFIC ·x SPEEDS REDUCED x MOVING BELOW SPEED LIMIT x TRAFFIC STOPPED x TRAFFIC JAM x

· FREEWAY JAMMED x FREEWAY BREAKDOWN x MINOR DELAY x MAJOR DELAY x FREEWAY GRADE A x FREEWAY GRADE F x TRAFFIC CONDITION A FREEWAY CONDITION C TRAFFIC CONDITION F

*Each descriptor placed on separate card

88

Los Angeles

x x x x x x x x x x x ~ x x x x x x x x x x x x x x x x x x x x x x x x x x x x x

TABLE B-12 PERCENTAGE ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - COMBINED DATA

Descriptor Sl i.de 1 Slide 2 Slide 3

BETTER ·sAME WORSE N BETTER SAME WORSE N BETTER SAME WORSE N

LIGHT CONGESTION 29 31 40 187 73 23 6 126 81 17 2 214 MODERATE CONGESTION 8 31 61 186 30 58 12 130 57 39 4 211 HEAVY CONGESTION 0 3 97 188 1 17 82 125 1 34 65 213 UNCONGESTED 56 40 4 188 82 12 6 125 86 12 2 213 CONGESTED 1 7 92 186 10 55 35 129 11 57 32 215 VERY CONGESTED 1 5 94 185 2 20 78 129 3 31 66 216 LIGHT TRAFFIC 70 26 4 190 B7 10 3 127 89 10 1 214 MODERATE TRAFFIC 16 59 25 190 53 42 5 125 79 21 0 211 HEAVY TRAFFIC 1 3 96 186 3 47 50 130 5 59 36 216 FREE FLOWING TRAFFIC 48 49 3 190 83 14 3 125 88 11 1 216 STOP-AND-GO TRAFFIC 3 6 91 186 3 36 61 127 12 43 45 216 JA""1ED TRAFF! C 0 2 98 186 1 9 90 130 1 11 88 216 FREEWAY OK 30 68 2 137 76 18 6 83 85 15 0 144 NO DELAY 43 55 2 136 83 11 6 83 92 8 0 143 DELAY 0 4 96 135 7 42 51 90 8 49 43 158 EXTRA DELAY 1 4 95 136 1 26 73 85 5 18 77 156 MOVING WELL 29 68 3 139 78 16 6 86 87 13 0 158 NORMAL TRAFFIC 20 71 9 138 72 21 7 85 77 22 1 153 FREE MOVING TRAFFIC 46 54 0 107 88 12 0 57 91 9 0 110 FREEWAY OPEN 63 36 1 101 84 16 0 58 85 15 0 103 FREEWAY CLEAR 80 19 1 104 90 8 2 60 90 10 0 105 MOVING AT SPEED LIMIT 28 72 0 106 74 22 4 58 90 9 1 108 NO CONGESTION 60 40 0 100 83 14 3 59 88 12 0 109 CONGESTION 0 3 97 99 7 52 41 61 8 69 23 110 MODERATELY CONGESTED 8 27 65 98 29 61 10 62 56 42 2 106 CONGESTED TRAFFIC 0 2 98 101 7 43 50 58 5 61 34 110 HEAVILY CONGESTED 0 0 100 103 0 18 82 62 1 26 73 110 SLOW TRAFFIC 1 11 88 98 13 61 26 61 24 67 9 110 SPEEDS REDUCED 5 18 77 102 11 65 24 62 24 .63 13 110 MOVING BELOW SPEED LIMIT 2 16 82 100 13 65 22 62 30 54 16 110 TRAFFIC STOPPED 0 1 99 103 0 5 95 59 l 10 89 110 TRAFFIC JAM 0 0 100 103 0 26 74 62 0 29 71 110 FREEWAY JAMMED 0 0 100 102 0 8 92 60 l 14 85 110 F~EEWAY BREAKDOWN 1 3 96 102 0 8 92 59 l 15 84 99 MINOR DELAY 1 9 90 98 27 36 37 59 42 49 9 106 MAJOR DELAY 1 D 99 103 3 11 86 63 2 11 57 110 FREEWAY GRADE A 57 34 9 86 50 47 3 34 46 53 1 68 FREEWAY GRADE F 3 25 72 87 9 55 36 33 6 65 29 66 TRAFFIC CONDITION A 48 30 21 33 58 31 11 26 36 56 8 45 TRAFFIC CONDITION F 0 17 83 35 13 35 52 23 9 61 30 46 FREEWAY CONDITION C 5 41 54 37 21 71 8 24 26 70 4 47

89

characteristics of subjects assumed to represent a national population. The

data are presented for each of the three slides (traffic states) used in the

study.

No statistical procedure is available to test significance between the

11 better than, same as, worse than 11 responses for each traffic state. The

researchers, therefore, elected to identify differences by inspection. The

cell with the highest response was deemed to be significantly greater if it

exceeded the lower cells by at least 30 percent.

Table B-13 depicts the results of the evaluation. The asterick (*)

entries are the cells found to be significantly higher than the others accord­

ing to the criterion selected by the researchers. By studying this table some

inferences can be drawn.

Certain patterns should emerge that would allow interpretation of the

results with respect to drivers' relative association of the descriptors to

increasing traffic states (density). In addition, it was expected that each

traffic state descriptor could be categorized as to whether it is highly speci­

fic, less specific, vague, or ambiguous and confusing.

Theoretically, the choice of three slides (traffic states) used by the

researchers could result in the following groupings by the subjects:

A descriptor could be viewed as describing=

1. better state than slide 1 2. same state as slide 1

3. worse state than slide 1, but better state than slide 2 4. same state as slide 2 5. worse state than slide 2, but better state than slide 3

6. same state as slide 3 7. worse state than slide 3

8. overlapping more than 1 state

90

TABLE B-13

SIGNlFICANT ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES AS DETERMINED BY INSPECTION - COMBINED DATA

Descriptor Slide l Slide 2

BETTER SAME WORSE BETTER SAME WORSE BETTER

FREEWAY CLEAR * * * LIGHT TRAFFIC * * * FREE FLOWING TRAFFIC * * * * FREE MOVING TRAFFIC * * * * FREEWAY OPEN * * * * NO CONGESTION * * * * NO DELAY * * * * UNCONGESTED * * * * LIGHT CONGESTION * * * * * FREEWAY OK * * 'Ii

MOVING AT SPEED LIMIT * * * MOVING ~JELL * * * Nf)RtAAI TRAFFIC * * * MODERATE TRAFFIC * * * * MODERATE CONGESTION * * * * CONGESTION * * * MINOR DELAY * * * * MODERATELY CONGESTED * * * MOVING BEi nw SPFEn LIMIT * * * SLOW TRAFFIC * * SPUDS REDUCED * * CONGESTED * * * CONGESTED TRAFFIC * * * DELAY * * * HEAVY TRAFFIC * * * STOP-AND-GO TRAFFIC * * * EXIRA DELAY * * FREEWAY BREAKDOWN * * FREEWAY JAMMED * * HEAVILY CONGESTED * * HEAVY CONGESTION * * JAMMED TRAFFIC * * MAJOR DELAY * * TRAFFIC JAM * * TRAFFIC STOPPED * * VERY CONGESTED * * r=r:u:r:w11.v r,i:rnnF A * * * * * EREFl>JAY GRADE F * * * FREl'.'t.IAY r.nNnnrnN f. * * * TRAFJ'.'Tr rnNnITTnN A * * * * * * TRAFFIC CONDITION F * * *

91

Slide 3

SAME WORSE

* * * * * * * * * * * * * * * *

* * * * * * * * * *

* * .* * *

However, a review of the data revealed that the subjects, as a rule, tended

to place the descriptors into the following groups:

1. better than slide 1 (Traffic State 1)

2. same as slide l (Traffic State 2)

3. same as slide 2 (Traffic State 3)

4. same as slide 3 (Traffic State 4)

5. worse than slide 3 (Traffic State 5)

6. overlapping more than l state

If the majority of the subjects associate a descriptor with one of the above

5 traffic states, the descriptor can be considered as having a highly speci­

fic association. A less specific descriptor is one that encompasses any two

successive traffic states. The descriptor would be considered as vague if it

encompasses more than two states. An ambiguous and confusing descriptor is

one that overlaps more than one state and a significant number of subjects

were not able to associate the descriptor to any of the states. The latter

would be noted by looking at the data from each group of subjects and comparing

the number of responses to each descriptor. Examples are discussed in the

following paragraphs.

The descriptor LIGHT TRAFFIC was found to depict a better traffic state

than that shown in slides 3, 2, and 1. Thus, the descriptor is highly specific

to an extremely low traffic density state. EXTRA DELAY was found to describe

a worse state than that shown in slides 1, 2, and 3. Therefore, the descriptor

is highly specific to a very high traffic density state. The above two descrip­

tors are illustrated in Figure ~-2 as encompassing only one state.

Other descriptors were interpreted by the subjects as describing more than

one traffic state. UNCONGESTED, for example, described better states than that

92

FIGURE B-2 ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - COMBINED DATA

Traffic States

Slide 1 Slide 2 Slide 3 Descriptor 1 2 3 4 5

FREEWAY CLEAR LIGHT TRAFFIC FREE FLOWING TRAFFIC FREE MOVING TRAFFIC FREEWAY OPEN NO CONG ES TI ON NO DELAY UNCONGESTED LIGHT CONGESTION FREEWAY OK MOVING AT SPEED LIMIT MOVING WELL NORMAL TRAFFIC MODERATE TRAFFIC MODERATE CONGESTION CONGESTION MINOR DELAY MODERATELY CONGESTED MOVING BELOW SPEED LIMIT SLOW TRAFFIC SPEEDS REDUCED CONGESTED CONGESTED TRAFFIC DELAY HEAVY TRAFFIC STOP-AND-GO TRAFFIC EXTRA DELAY FREEWAY BREAKDOWN FREEWAY JAMMED HEAVILY CONGESTED HEAVY CONGESTION JAMMED TRAFFIC MAJOR DELAY TRAFFIC JAM TRAFFIC STOPPED VERY CONGESTED

* FREEWAY GRADE A I+ FREEWAY GRADE F

FREEWAY CONDITION C * ... TRAFFIC CONDITION A I* TRAFFIC CONDITION F

* Ambiguous and Confusing

93

shown in slides 3 and 2, but was interpreted as describing both the same

state shown in slide 1 and better state than slide 1. This descriptor over­

laps two states, as shown in Figure B-2, and thus is considered as being less

specific for describing a lo~ traffic density state. CONGESTED was interpreted

as a better state than shown in slide 1, but the same as and worse state than

slide 2, and same as and worse state than slide 3. Figure B-2 illustrates

the descriptor overlapping traffic states 3, 4, and 5. Since the descriptor

encompasses more than 2 states, it is considered as being vague.

Table B-13 also reveals that FREEWAY GRADE A was significant in describing

the same as and better state than slide l, the same as and better state than

slide 2, and the same as and better state than slide 3. In addition, Table B-12

shows that there was a significant number of subjects that were not able to

associate the descriptor to any state as exemplified by the significant reduction

of responses in comparison to the other descriptors. Thus, this descriptor

is ambiguous and confusing. Likewise, FREEWAY GRADE F, FREEWAY CONDITION c,

TRAFFIC CONDITION A, and TRAFFIC CONDITION F are ambiguous and confusing.

Figure B-2 illustrates the association of the numerous descriptors to the

five traffic states. The relative association between descriptors and their

individual qualities in describing specific traffic states are apparent. The

descriptors are further summarized in Tables B-14 and B-15.

The results reveal that, on the average, highly specific descriptors are

available to describe the light end and the very heavy end of the traffic state

continuum. The following descriptors were found to describe extremely light

flow conditions (traffic state 1):

FREEWAY CLEAR

LIGHT TRAFFIC

94

l.O (J1

TABLE B-14 SUMMARY OF HIGHLY SPECIFIC AND LESS SPECIFIC TRAFFIC STATE DESCRIPTORS - COMBINED DATA

1

FREEWAY CLEAR LIGHT TRAFFIC

2

FREEWAY OK MOVING AT SPEED LIMIT MOVING WELL NORMAL TRAFFIC

FREE FLOWING TRAFFIC FREE MOVING TRAFFIC FREEWAY OPEN NO CONGESTION NO DELAY UNCONGESTED

TRAFFIC STATES

3 4

CONGESTION MINOR DELAY MODERATELY CONGESTED MOVING BELOW SPEED LIMIT SLOW TRAFFIC SPEEDS REDUCED

MODERATE TRAFFIC

5

EXTRA DELAY FREEWAY BREAKDOWN FREEWAY JAMMED HEAVILY CONGESTED HEAVY CONGESTION JAMMED TRAFFIC MAJOR DELAY TRAFFIC JAM TRAFF! C STOPPED VERY CONGESTED

TABLE B-15 SUMMARY OF VAGUE, AMBIGUOUS AND CONFUSING

TRAFFIC STATE DESCRIPTORS -COMBINED DATA

Vague

CONGESTED

CONGESTED TRAFFIC

DELAY

HEAVY TRAFFIC

LIGHT CONGESTION

MODERATE CONGESTION

STOP-AND-GO TRAFFIC

96

Ambiguous and Confusing

FREEWAY CONDITION C

FREEWAY GRADE A (F)

TRAFFIC CONDITION A (F)

The following highly specific descriptors were associated with light flow con­

ditions slightly heavier than the extreme light state (traffic state 2):

FREEWAY OK MOVING AT SPEED LIMIT MOVING WELL NORMAL TRAFFIC

On the extremely heavy traffic state end of the continuum, the following des­

criptors are highly specific (traffic state 5):

EXTRA DELAY FREEWAY BREAKDOWN FREEWAY JAMMED HEAVILY CONGESTED HEAVY CONGESTION JAMMED TRAFF! C MAJOR DELAY TRAFFIC JAM TRAFFIC STOPPED VERY CONGESTED

Severai ·descriptors were found to be less specific in that they were associated

with a broader range of either light traffic conditions or moderate-to-heavy

traffic conditions. The following descriptors were associated with the first

two traffic states:

FREE FLOWING TRAFFIC FREE MOVING TRAFFIC FREEWAY OPEN NO CONGESTION NO DELAY UNCONGESTED

Descriptors associated with the next two highest traffic states were:

CONGESTION MINOR DELAY

97

The descriptor:

MODERATELY CONGESTED MOVING BELOW SPEED LIMIT SLOW TRAFFIC SPEEDS REDUCED

MODERATE TRAFFIC

was found to describe a traffic state somewhere between the less specific des­

criptors discussed above since it overlaps traffic states 2 and 3.

Descriptors found to be vague are as follows:

CONGESTED CO~GESTED TRAFFIC DELAY HEAVY TRAFFIC LIGHT CONGESTION MODERATE CONGESTION STOP-AND-GO TRAFFIC

Ambiguous and confusing messages were basically the coded letter grade

messages:

FREEWAY CONDITION C FREEWAY GRADE A (F) TR~FFIC CONDITION A (F)

Attempts to rank order the descriptors that the subjects selected as

describing the same state as shown on each slide and arranged in order or pre­

ference were unsuccessful due to the wide variability of choices and ranking

by the subjects.

Regional Analysis

Results of studies from the four study locations are presented in Figures

B-3 through B-6 and in Tables D-1 through D-8, shown in Appendix D.

98

. FIGURE B-3 ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

COLLEGE STATION

Traffic States

Slide l Slide 2 Slide 3 Descriptor l 2 3 4

LIGHT TRAFFIC UNCONGESTED FREE FLOWING TRAFFIC LIGHT CONGESTION MODERATE TRAFFIC MODERATE CONGESTION CONGESTED HEAVY TRAFFIC HEAVY CONGESTION VERY CONGESTED JAMMED TRAFFIC STOP-AND-GO TRAFFIC

99

5

FIGURE 8-4 ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

HOUSTON

Traffic States

Slide l Slide 2 Slide 3 Descriptor l 2 3 4

FREE FLOWING TRAFFIC LIGHT TRAFFIC NO DELAY UNCONGESTED FREEWAY OK MOVING WELL NORMAL TRAFFIC LIGHT CONGESTION MODERATE TRAFFIC MODERATE CONGESTION CONGESTED DELAY HEAVY TRAFFIC STOP-AND-GO TRAFFIC EXTRA DELAY HEAVY CONGESTION JAMMED TRAFF! C VERY CONGESTED

100

5

FIGURE B-5 ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - ST. PAUL

Traffic States

Slide 1 Slide 2 Slide 3 Descriptor 1 2 3 4 5

FREEWAY CLEAR LIGHT TRAFFIC NO CONGESTION UNCONGESTED FREE FLOWING TRAFFIC FREE MOVING TRAFFIC FREEWAY OK FREEWAY OPEN LIGHT CONGESTION NO DELAY MODERATE TRAFFIC MOVING WELL NORMAL TRAFFIC MOVING AT SPEED LIMIT MODERATE CONGESTION MODERATELY CONGESTED MINOR DELAY CONGESTED CONGESTED TRAFFIC CONGESTION HEAVY TRAFFIC MOVING BELOW SPEED LIMIT SLOW TRAFFIC SPEEDS REDUCED STOP-AND-GO TRAFFIC DELAY EXTRA DELAY VERY CONGESTED HEAVILY CONGESTED HEAVY CONGESTION TRAFFIC JAM FREEWAY BREAKDOWN FREEWAY JAMMED JAMMED TRAFFIC MAJOR DELAY TRAFFIC STOPPED FREEWAY GRADE A ~

FREEWAY GRADE F I*

* Ambiguous and Confusing

101

FIGURE B-6 ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - LOS ANGELES

Traffic States

Slide l Slide 2 Slide 3 Descriptor l 2 3 4 5

FREEWAY CLEAR FREE FLOWING TRAFFIC FREE MOVING TRAFFIC FREEWAY OPEN LIGHT TRAFFIC NO CONGESTION NO DELAY UNCONGESTED FREEWAY OK MOVING AT SPEED LIMIT MOVING WELL NORMAL TRAFF! C MODERATE TRAFFIC LIGHT CONGESTION CONGESTION MINOR DELAY MODERATE CONGESTION I

MODERATELY CONGESTED MOVING BELOW SPEED LIMIT SLOW TRAFF! C SPEEDS REDUCED CONGESTED CONGESTED TRAFFIC DELAY HEAVY TRArFIC STOP-AND-GO TRAFFIC EXTRA DELAY FREEWAY BREAKDOWN FREEWAY JAMMED HEAVILY CONGESTED HEAVY CONGESTION JAMMED TRAFFIC MAJOR DELAY TRAFFIC JAM TRAFF! C STOPPED VERY CONGESTED FREEWAY CONDITION C * FREEWAY GRADE A ... FREEWAY GRADE F * TRAFFIC CONDITION A ... TRAFFIC CONDITION F *

* Ambiguous and Confusing

102

From these data, an attempt was made to determine word association con­

sistency between the four study locations. However, of the 12 descriptors

studied in all four cities, only JAMMED TRAFFIC and FREE FLOWING TRAFFIC were

consistently interpreted. The descriptor was associated with traffic state 5,

the most severe state. Differences existed between the cities for the remaining

11 descriptors.

It was speculated that perhaps differences may be attributed to the size

of the city and the degree of freeway congestion the subjects normally exper­

ience while driving. Although the St. Paul subjects commute regularly on urban

freeways, the degree of trqffic congestion they encounter is not as severe as

that experienced by Houston or Los Angeles drivers. The College Station sub­

jects reside in a city without freeways but generally have had freeway driving

experience in large metropolitan areas. It was reasoned that since the concept

of congestion is relative, there may be similarities of descriptor association

between the sma 11 er cities and between the 1 arger cities. Thus, the responses

from College Station were compared to those of St. Paul to evaluate any simi­

larities. ·Likewise, comparisons were made between the Houston and Los Angeles

data.

Table B-16 summarizes the descriptor associations found to be consistent

between the College Station and St. Paul data. Interestingly, 10 of the 12

descriptors studied in both cities were consistently associated to the traffic

states shown in the table. Four descriptors, LIGHT TRAFFIC, UNCONGESTED,

MODERATE TRAFFIC, and JAMMED TRAFFIC were highly specific, the first two to

traffic state l, the thi.rd to state 2, and the fourth to state 5. An addi­

tional five FREE FLOWING TRAFFIC, LIGHT CONGESTION, CONGESTED, HEAVY TRAFFIC,

103

TABLE B-16 SUMMARY OF DESCRIPTOR ASSOCIATION FOR SMALL CITIES -

COLLEGE STATION AND ST. PAUL

TRAFFIC STATES

l 2 3 4

UNCONGESTED MODERATE TRAFFIC

LIGHT TRAFFIC

FREE FLOWING TRAFFIC CONGESTED

LIGHT CONGESTION HEAVY TRAFFIC

MODERATE CONGESTION

5

JAMMED TRAFFIC

HEAVY CONGESTION

Descriptors Not Consistent:

1. STOP AND GO TRAFFIC

2. VERY CONGESTED

and HEAVY CONGESTION were found to be less specific. The first two descrip­

tors encompass states l and 2, the next two descriptors encompass states 3 and

4, while the last overlaps states 4 and 5. One descriptor, MODERATE CONGESTION

was considered as vague, although it was associated with the same traffic

states by both College Station and St. Paul subjects. Only the descriptors

STOP-AND-GO TRAFFIC and VERY CONGESTED were not associated the same by subjects

from both cities.

A summary of the Houston and Los Angeles data is presented in Table B-17.

Again, the association of most of the descriptors was found to be consistent

between these two cities. Of the 18 descriptors studied at both locations,

the associations of 15 descriptors were found to be consistent between the sub­

ject groups. Six descriptors were found to be highly specific, 6 less specific,

and 3 vague. FREEWAY OK and MOVING WELL were viewed as being highly specific

to traffic state 2, while EXTRA DELAY, HEAVY CONGESTION, JAMMED TRAFFIC, and

VERY ·CONGESTED were highly specific to state 5. Less specific descriptors in­

clude FREE FWWING TRAFFIC, LIGHT TRAFFIC, NO DELAY, and UNCONGESTED encompassing

traffic states 1 and 2,. MODERATE TRAFFIC overlapping states 2 and 3, and

MODERATE CONGESTION associated with states 3 and 4. CONGESTED, DELAY, and

HEAVY TRAFFIC were associated with three states (3, 4, and 5} and are thus

considered as vague. The three descriptors not associated consistently be-

tween the subject groups were LIGHT CONGESTION, STOP-AND-GO TRAFFIC, and

NORMAL TRAFFIC.

105

TABLE B-17 SUMMARY OF DESCRIPTOR ASSOCIATION FOR LARGE CITIES -

HOUSTON AND LOS ANGELES

TRAFFIC STATES

1 2 3 4

FREEWAY OK MOVING WELL

FREE FLOWING TRAFFIC MODERATE CONGESTION LIGHT TRAFFIC NO DELAY UNCONGESTED

MODERATE TRAFFIC

I

HEAVY TRAFFIC DELAY CONGESTED

Descriptors Not Consistent:

1. LIGHT CONGESTION 2. STOP AND GO TRAFFIC 3. NORMAL TRAFFIC

5

VERY CONGESTED JAMMED TRAFFIC EXTRA DELAY HEAVY CONGESTION

Comparison of Tables B-16 and B-17 reveals some interesting contrasts

and similarities:

1. The subjects from the smaller cities tended to be more apprehensive

about traffic conditions at the lower traffic states. For example,

they identified highly specific descriptors (UNCONGESTED and LIGHT

TRAFFIC) with the extreme light flow conditions represented by traf­

fic state 1. In contrast, subjects from the larger cities associated

these descriptors with a broader range of 1 i ght fl ow conditions en­

compassing states 1 and 2. Of particular interest is that the College

Station and St. Paul subjects interpreted LIGHT CONGESTION to mean

the same as FREE FLOWING TRAFFIC by associating both descriptors with

the two lowest traffic states (1 and 2). A review of other descrip­

tors also reveals the tendency of the subjects from the small cities

to identify with congestion at a lower traffic state ·than the large

city subjects. Thi.s finding is consistent with the results dis­

cussed in Study 3.

2. Of the 12 descriptors studied in all four cities, only FREE FLOWING

TRAFFIC and JAMMED TRAFFIC were associated consistently. JAMMED

TRAFFIC was found to be highly specific to the high traffic state,

whereas FREE FLOWING TRAFFIC was a less specific descriptor associated

with states 1 and 2.

107

Discussion

The results indicate that driver association of descriptors to traffic

states is dependent upon the size of the city in which they reside and do

most of their driving. With the exception of the most severe traffic state,

large city drivers associate descriptors somewhat differently than those

living in smaller cities.

Figure B-~ and Tables B-14 and B-15 represent relative driver association

of descriptors to various traffic states averaged across all four cities

studied. As such, they may not be a good guide to base decisions regarding

choice of terminology. Tables B-16 and B-17 are more representative of large

cities and small cities, respectively, and provide better guidelines for mes­

sage selection based on size of city. Unfortunately, only 12 common messages

were studied in the smaller cities {College Station and St. Paul) and 18 common

messages in the large cities (Houston and Los Angeles). Thus inferences can

be made regarding a limited number of messages. Ideally, all 41 messages

studied in Los Angeles should have been evaluated in the other three cities.

In spite of the fact that not all descriptors were evaluated in the four

cities, a comparison of the St. Paul and Los Angeles results revealed some simi­

larities that could be constrµed to imply some consistency between large and

small cities. Several descriptors, for example, were found in both cities to

be highly specific in describing the extreme high traffic state {state 5). These

include:

FREEWAY BREAKDOWN

FREEWAY JAMMED JAMMED TRAFFIC MAJOR DELAY TRAFFIC STOPPED

108

It is speculated that these descriptors would have been associated similarly

by the College Station and Houston subjects. Likewise, consistency between

the St. Paul and Los Angeles data suggest the following descriptors would

be appropriate in describing traffic states 3 and 4 in both small and large

cities:

CONGESTION

MOVING BELOW SPEED LIMIT

SLOW TRAFFIC

SPEEDS REDUCED

The descriptors containing letter grades such as:

FREEWAY GRADE A (F}

were found to be ambiguous and confusing in both the St. Paul and Los Angeles

studies. Without fail, each time this study was conducted one or more sub­

jects asked questions concerning the meaning of the descriptor. Likewise,

in Los Angeles questions were asked about the descriptors:

FREEWAY CONDITION C

TRAFFIC CONDITION A (F}

The above three letter grade descriptors were confusing and ambiguous in the

cities studied, and it is resasonable to assume that there would be interpre­

tation difficulties in the other cities as well.

109

Design Recommendations

1. Unanchored letter grade descriptors such as FREEWAY CONDITION A (F),

FREEWAY GRADE A (F), and TRAFFIC CONDITION A (F) are ambiguous and

confusing and should be avoided. Anchoring the letter grades, similar ·

to the designs discussed in the next chapter on "Traffic State Coding",

would probably increase driver understanding of the coded message.

2. Since the results of the study suggest that there is a slightly different

association of descriptors to various traffic states between large city and

small city drivers, different terminology should be used to describe the

states.

3. In small cities, the following compatible descriptors would be effective

in describing the continuum of traffic states assuming 4 levels of traffic

operations:

LIGHT TRAFFIC - MODERATE TRAFFIC - HEAVY TRAFFIC - JAMMED TRAFFIC

UNCONGESTED - LIGHT CONGESTION - CONGESTED - MAJOR DELAY

The followjng compatib1e descriptors would be effective in.describing the

continuum of traffic states assuming 3 levels of traffic operations:

FREE FLOWING TRAFFIC - HEAVY TRAFFIC - JAMMED TRAFFIC

LIGHT CONGESTION - CONGESTED - HEAVY CONGESTION

The following descriptors were either not associated consistently among the

small cities studied or were found to be vague and thus should be avoided:

MODERATE CONGESTION

STOP-AND-GO TRAFFIC

VERY CONGESTED

110

4. In large cities, the following compatible descriptors would be effective

in describing the continuum of traffic states assuming 3 levels of traffic

operations:

UNCONGESTED - MODERATE CONGESTION

FREE FLOWING TRAFFIC - SLOW TRAFFIC or

LIGHT TRAFFIC

NO DELAY - CONGESTION

HEAVY CONGESTION or

VERY CONGESTED

JAMMED TRAFFIC

MAJOR DELAY or

EXTRA DELAY

5. There is evidence that the following descriptors would work equally as

well in describing the extreme high traffic density state in both small

and large cities:

FREEWAY BREAKDOWN

FREEWAY JAMMED

JAMMED TRAFFIC

MAJOR DELAY

TRAFFIC STOPPED

6. Care must be exercised in selecting appropriate sets of messages. Both

long and short descriptors can be used in audio systems, whereas, only

the shorter descriptors would in most cases be appropriate for visual

displays.

111

REFERENCES

1. Highway Capacity Manual, Highway Research Board Special Report 87, 1965.

2. Dudek, C. L. Human Factors Requirements For Real-Time Motorist Informa­tion Displays, Vol. 2 - State-of-the-Art: Messages and Displays in Free­way Corridors. Texas Transportation Institute, Report Number FHWA-RD-78-6, February 1978.

112

VI. TOPIC AREA C - TRAFFIC STATE CODING

Objectives

(a) To determine optimal methods of coding three levels of traffic

state information

(b) To determine whether the root descriptors 11 traffic 11 and 11 congestion 11

are interpreted as synonymous or different terms

Background

Results of Study 1 in the previous chapter indicated that motorists

tend to conceptualize three levels of traffic states while driving on the

freeway. The chapter dealt mostly with verbal descriptors-•words.

But there are other perhaps equally meaningful methods of expressing these

states in terms of symbolic or coded displays. The studies in this chapter

of the report address the issue of coding traffic states. Also, alternative

ways of presenting verbal information were considered: direct forming of

words vs. merely indicating which words already on the sign applied to the

present state of affairs on the freeway.

A central concept in studying traffic state coding is that of anchoring.

ANCHORING implies showing all possible states on a sign such that when any

one state is illuminated or displayed its relative position to the 11best"

and 11worse" state is clearly identifiable. For example, a sign along the

freeway may display traffic condition information by means of an academic

grading system: A being excellent, B good, etc., and F would be used for

a condition of severe traffic congestion. An unanchored system would merely

employ a single message such as: .

113

FREEWAY GRADE A

or

FREEWAY GRADE F

An anchored display would be as follows:

FREEWAY GRADE A B C D F

.Y--<:~ 0- -/'!(

Of course the latter sign design exceeds the three levels of traffic states

that Study 1 of the previous chapter implies a driver visualizes and is

used only to illustrate the anchoring concept. In addition, the utility

of the design will be dependent upon whether drivers can interpret the

meaning of the title and which ends of the spectrum constitutes 11 good 11

and 11 bad 11 conditions.

Another issue addressed in the studies discussed in this chapter of

the report rel ate to the root descriptors 11 traffi c 11 and 11 congesti on!'. There

was a question whether or not drivers viewed verbal descriptors such as

LIGHT TRAFFIC' MODERATE TRAFFIC' and HEAVY TRAFFIC to be synonymous with

LIGHT CONGESTION' MODERATE CONGESTION' and HEAVY CONGESTION. This issue was

one that plagued the researchers for several months during the early stages

of the laboratory studies.

114

Study 1 - Preliminary Screening of Traffic State Coding Methods

Objectives

The specific objective of this Study was to screen preliminary sign

designs as a first step in determining optimal methods of coding levels of

traffic state information. Another goal was to determine whether or not the

root descriptors 11 traffic 11 and 11 congestion 11 are interpreted by drivers as

synonymous terms. The assumption in the Study was that the number of levels

necessary to code was three.

Method

There were two co-varying factors considered in developing the sign

designs: 1) the type of coding - lights, numeric, symbolic, and verbal,

and 2) anchoring. Table C-1 illustrates the preliminary considerations

for traffic state coding. Figure C-1 presents the candidate coded signs

developed for the preliminary screening studies based on the considerations

shown in Table C-1. The Figure illustrates the signs containing the root

descriptor 11 congestion. 11 Signs containing the root descriptor 11 traffic 11

were also developed using identical designs shown in Figure C-1. _.,.,

The study was conducted in College Station and then replicated in

"""' Houston. Forty-six subjects in College Station were presented the candidate

sign designs with the root word 11 traffic 11; 42 subjects viewed signs contain­

ing 11 congestion. 11 In Houston, 56 subjects responded to the 11 traffic 11 signs

and 60 to the 11 congestion 11 signs.

Slides of the signs were presented in random order to subjects in the

two groups. The subjects were given the same instructions except for

the alternate usage of 11 traffic 11 vs. 11 congestion. 11 The subject's job

115

TABLE C-1

CODING AND ANCHORING CONSIDERATIONS FOR CANDIDATE SIGN DESIGNS

Coding Sign Designs*

Verbal a. Unanchored b. Anchored

Symbolic a. Unanchored b. Anchored with Numbers c. Anchored with Words

Numeric a. Unachored b. Anchored

Light Coding a. Unanchored (White Lamps) b. Unanchored (Color Coded) c. Anchored (Color Coded)

*See Figure C-1

116

1- 2- 3 4- 5- 6

7- 8- 9 10-11-12 13-14-15

16-17-18 19-20-21

22-23-24 25-26-27 28-29-30

Figure C-1 - Candidate Traffic State Descriptor Sign Designs

-------,-., lllff

4 · CoNCESTIOlt'· -••n1 • llUll'

7 1111111 Red.Jlll:::;:ll

White

10

13

' · COHISTION ". t 2 ~ -· ~

-STION-l

- -1 -' ----

22--

25 ' . CONGESTION

I • f ___ _

28

Green

5 ,. ·-.. COHESTIOJt • -., l-

14

. CONCESTIOlf

17 ,;·

l~ 2

23-26

---' CONGESTION I . .

I

L

Yellow

29···' Green · Yellow

6

~

) •·- I ,.COlllESTIOI - i " lllft'

-----'. CONGESTION

9 -- - - --

12-11111

15 lilillJ

18

-~co1cm1oa

21 l

c 3

24 -30

COIHiESTION _. . . -------

Note: Colors= White on green except as noted. 11 Traffic" are Identical.

Red Signs containing

117

was to decide which of 3 states-- light, medium, or heavy--was being expressed

by each sign as it was presented. They then encircled an appropriate word for

each presentation - "Light" - "Medium" - 11 Heavy 11 - on their answer sheet.

In the second part of the experiment, subjects rank ordered black and

white prints of each type of sign. Where color coding or color were important,

the appropriate portions of the prints were hand colored.

The third portion of the study was conducted only in College Station and

was an attempt to ascertain whether "traffic" and "congestion" are considered -

synonymous. In this part of the experiment, a continuum from a very empty

freeway to one jammed with vehicles was anchored on both extremeso Then the

subjects were handed two sets of cards, one set at a time, with the following

messages on them:

LIGHT TRAFFIC

MEDIUM TRAFFIC

HEAVY TRAFFIC

and

LIGHT CONGESTION

MEDIUM CONGESTION

HEAVY CONGESTION

The cards ~ith 11 traffic 11 were given first to the subjects that viewed the sign

designs containing the traffic descriptor, while subjects viewing the conges­

tion descriptor signs were first given the set containing the root word

11 congestion.~1 The subjects then marked the answer sheet on the scale, based

on their interpretation of the relative positioning of the descriptor, to the

anchor provided.

The independent variable for the first and second parts of the study was

the sign design. The dependent variable for Part 1 was the frequency of

errors in describing the meaning of the signs, and for Part 2, the subject

preference exemplified in the ranking. In the third part of the study, the

independent variable was the alternative root descriptors; the dependent

variable was the scaling of the descriptors on a continuum.

Results

Probably the most significant question to be. answered by the study data

in Part 1 is: Which of the candidate signs yield the fewest number of errors

of interpretation? For this purpose, the errors made by subjects were com­

bined for all three traffic states (light, medium, heavy}. These data for

both the College Station and Houston subjects are shown in Table C-2. A

t-test for number of errors made on coding types titled "traffic" vs. coding

types titled "congestion" w~~ npn-significant (probability greater than 0.05),

indicating that the subjects presented one form of titling did not vary with

respect to errors of interpretation from those presented the other form.

The combined errors for both the "traffic" and "congestion" ·signs are

rather high, ranging from 5 to 92 percent. These rates are probably inflated

by the presentation of many different coding methods to the same subjects,

with possible confusion and proactive interference to responses caused by

those signs which were very ambiguous. Thus, there is support for combining

scores across titling conditions for further analysis of these data.

The candidate coded sign designs are shown in Table C-3 in the preference

order of the subjects (Part 2). The Table represents rank ·order using the

combined scores of both the "traffic" and "congestion" titling conditions.

The high percentage of errors. and the low rank suggest that the sign

coding types 22-23-24 and 25-26-27 could be eliminated from further consider­

ation. Examples of these designs for the light congestion condition are

illustrated below:

CONGESTION fJ e

G ee

119

TABLE C-2

PERCENT ERRORS ASSOCIATED WITH CANDIDATE CODED TRAFFIC STATE DESCRIPTOR SIGNS

Cambi ned Errors Combined Errors Coding Type ~Refer to Fig. C-1) 11Traffic 11 11Congesti on 11

College Station (N=3x46=138) (N=3x42=126)

1- 2- 3 9 17 4- 5- 6 23 17 7- 8- 9 25 10

10-11-12 25 19 13-14-15 26 21 16-17-18 19 14 19-20-21 17 15 22-23-24 41 40 25-26-27 50 43 28-29-30 28 18

Houston (N=3x52=156) . (N=3x60=180)

1- 2- 3 6 5 4- 5- 6 12 3 7- 8- 9 15 14

10-11-12 21 12 13-14-15 21 7 16-17-18 8 21 19-20-21 9 15 22-23-24 92 66 25-26-27 .ll. 11 28-29-30 12 16

120

Grouped Errors

(N=264)

13 21 18 22 24 17 16

.il R 23

(N=336)

5 7

15 16 13 15 12 ]_§_

1.l 14

TABLE C-3

DESIGN PREFERENCES FOR TRAFFIC STATE CODING SIGNS

Coding Type Sum of Average Revised (Refer to Figure C-1) Ranks* Rank Rank

4- 5- 6 227 2.73 1

1- 2- 3 278 3.27 2

13-14-15 314 3.78 3

10-11-12 403 4.85 4

28-29-30 500 6.02 5

7- 8- 9 515 6.20 6

19-20-21 521 6.28 7

16-17-18 637 7.24 8

25-26-27 652 7.95 9

22-23-24 713 8.69 10

*11 Traffic 11 and 11 Congestion 11 signs combined

121

The results als-o indicated a consistent pattern with respect to drivers'

preference for the word descriptors.

It was of interest to determine whether or not any real difference

exists between the College Station and Houston data with respect to

either errors or preferences. Using the Mann-Whitney U-Test With

the error percentage data, differences between College Station and

Houston were found to be not significant (critical value of U at Pr 0.10

for a two-tail test was 34 vs. observed U of 35).

It was also of interest to deternine whether a significant difference

exists between rank ordering of the coding types by preference in the two

locales. To evaluate this, the preference data were used to calculate a

Spearman rank correlation coefficient. The value of rs, the rank correlation

coefficient, was 0.9 between College Station and Houston. The significance of

this value of rs for an N of 10 is beyond the 0.01 level. Hence, a great deal

of conmonality exists between the College Station and the Houston subjects in

preference ranking of these signs.

The final part of this experiment (Part 3) focused on grading of level of

traffic service along a continuum from a very low state to a very high state.

Thecontinuumwas anchored by two slides depicting these states. The subjects

were presented six cards in two sets of 3: Light-medium-heavy traffic and

light-medium-heavy congestion. Unfortunately, when the data were reduced and

analyzed, it was discovered that there was an artifact in the experimental

design. Subjects viewing the 11 congestion 11 descriptor signs graded the three

congestion state cards first. The tendency was to use the entire continuum

in the grading of the 11 congestion 11 cards. Thus, when they were presented the

122

11 traffic 11 state cards, they had no choice but to overlap the same segments of

the continuum as they used for the 11 traffic 11 states. The same problem arose

with the group of subjects viewing the 11 traffic 11 descriptor signs. Thus, once

again it was not possible to evaluate whether differences existed between the

root descriptors' 11 traffic 11 and 11 congestion. 11 The only supporting evidence

of differences resulted form Study 4 in the previous chapter.

123

Study 2 - Traffic State Coding Methods

Objective

This experiment was a follow-up to Parts 1 and 2 of Study 1. Seven of

the 8 candidates remaining from Study 1 were subjected to further study.

Method

Groups of subjects were shown only one of the candidate signs, shown in

Table C-4, and were asked to write the meaning of the sign in an 11 open-ended 11

response. All signs displayed a light traffic condition, with the exception

of the first sign design that had a moderate condition. This change was made

because of the belief that it would be the most difficult to interpret from

among the three possibilities. ../

Although the experiment was conducted in St. Paul and Los Angeles, it was

considered to be an extension of the Mediamaster studies conducted in College

Station. It was not the intent to determine regional differences.

A total of 360 subjects participated in the experiment. The number of

subjects responding to each of the 7 candidate designs ranged between 39 and 85.

Results

The results of the study are shown in Table C-4. As can be seen, the

designs containing word descriptors, both anchored and unanchored, resulted in

the highest percentages of correct responses. "Correct" is defined as a

response in relation to the intended meaning of the sign. Sign Candidate 2

containing anchored word descriptors resulted in 98 percent correct responses,

followed by a 90 percent for Candidate 5 containing a 11 thermometer 11 code with

anchored word descriptors, and a 72 percent for Candidate 1 which had an

124

TABLE C-4

RESPONSE TO CANDIDATE TRAFFIC STATE DESCRIPTOR SIGNS

Sign Design Response e~l'.:!;~D:t N Correct Incorrect

• Not light, not heavy traffic ahead 27 59

• Medium to heavy traffic ahead 5 11 TRAFFIC No problems ahead 1 2 MODERATE I

...... I Heavy and slowing down ahead 7 15 N

U1

1 • Light traffic ahead 5 11

I No response 1 2

Total 46 72 28

• Light traffic ahead, no delays, HEAVY no congestion ahead 43 96

TRAFFIC MODERATE • No significant congestion ahead 1 2

• LIGHT • Moderate to heavy traffic ahead 1 2 -2 Total 45 98 2

TABLE C-4 (CONTINUED)

Sign Design Response ~et:~eat N Correct Incorrect

• Light traffic ahead 11 25

• Light congestion ahead 8 18

• Heavy traffic ahead 1 2

• Stopped traffic ahead 4 9

TRAFFIC • Danger ahead for short distance 1 2

t::@ • Left lane blocked (closed) 6 13

• Lane blocked ahead 2 4 3 I Left side of road blocked 2 4

~ I Don't know 10 22 N

°' Total 45 25 74

I Light traffic ahead 15 33 I Heavy traffic ahead 4 9

TRAFFIC I Heavy traffic next 1-1~ miles 5 11 1 2 3 I Congestion/Danger 1 mile ahead 2 4 W:f I I Obstruction/Congestion in left

lane 12 27 4 Keep left 1 2 I

I Don't know 6 13 Total 45 33 67

TABLE C-4 (CONTINUED)

Sign Design Response Percent N Correct Incorrect

• Light traffic ahead 46 90

• Dangerously heavy traffic ahead 1 2 TRAFFIC • Obstruction/Congestion in left

LIGHT MODERATE HEAVY lane 2 4

~ I • Others 2 4

Total 51 90 10 5

....... N ....... • Light traffic ahead 16 19

• Heavy traffic 1 mile ahead 3 3

• One lane open ahead 11 13 TRAFFIC • Traffic moving in lane 1 6 7

[!] • Left lane/lane 1 congested/ blocked 9 11

6 • Right lane congested 4 5

• Others 5 6

• Don't know 31 36 Total 85 19 81

TABLE C-4 (CONTINUED)

Sign Design Response Eercgnt N Correct Incorrect

• Light traffic ahead 5 13 ...... • Congestion ahead 2 5 N 00 • Traffic heavy 1 mile 1 3

TRAFFIC • One lane open/two lanes closed 7 18

• Congestion in left lane 8 20

ITJ II II • Left lane/lane 1 open , others · blocked 15 38

7 • Others 1 3 Total 39 13 87

unanchored verbal descriptor. The lower percentage for Candidate 1 may have

been attributed to the possible ambiguity of the term MODERATE. Fifteen per­

cent of the 46 subjects responding interpreted the sign to mean "heavy traffic 11

or "light traffic" ahead. A better choice of word may have increased driver

understanding of the message. However, the anchored word signs were proven

to be the design types that are most easily interpreted.

Coded signs were not understood by the subjects. Sign Candidates

3, 4, 6, and 7 were correctly interpreted by only 25, 33, 19, and 13 per­

cent of the subjects. Many of the subjects associated the horizontal

thermometer scale and codeq numbers with specific lanes rather than traf­

fic states. Others associated the red portion of the thermometer as

implying "danger" or "congestion". For Sign Candidate 3, for example,

21 percent of the 45 subjects interpreted the sign to mean "left lane

blocked", "lane blocked ahead", or "left side of road blocked". Thirty­

one percent believed one of the following messages applied: "light con­

gestion ahead", "heavy traffic ahead", "stopped traffic ahead", or "danger

ahead for short distance". Twenty-two percent of the subjects simply

could not ascribe any meaning to the sign.

The use of the number codes in Sign Candidates 6 and 7 resulted in some

interesting interpretations as shown in Table C-4. Most subjects associated

the number with a lane and not with a specific level of traffic state.

Discussion

The results strongly suggest that drivers do not understand coded traf­

fic state descriptor messages. Number codes, thermometer codes, and as was

the case in Study 4 of the previous chapter of this report, letter codes are

129

not understood in first trial situations. The results also suggest that when

codes are used, they must be anchored by appropriate verbal descriptors (see

Sign Candidate 5 as an example).

Word descriptors appear to work well and probably would be effective

(based on Study 4 of the previous chapter) whether anchored or not. The

results of this sectiion, however, inidicate that anchored verbal descriptors

would be more effective than if not anchored.

Another factor that may have influenced subject interpretation of the

signs was the sign title. The term TRAFFIC was used on all the signs in Study

2. It is not known whether another title such as TRAFFIC CONDITION would have

increased driver understanding of the intended message.

Design Recommendations

1. Avoid the use of unanchored numbers, letter. or other codes to

describe traffic states on the freeway.

2. Number, letter, or other coded signs must be anchored with appropriate

word descriptors similar to the following assuming presentation of

five possible traffic states.

TRAFFIC

LIGHT JAMMED -w [I] 0 0 ~ ~= 1 :;'--~-; ( '-

3. If it is decided that only three traffic states will be displayed,

then the coded sign must be as follows:

. 130

TRAFFIC JAMMED

ill

4. There is no data to support the need for coded numbers or letters

in the designs shown in item 2 and 3 above. The codes could

probably be removed without any loss of understanding.

5. A simple and more appropriate design would be as follows:

TRAFFIC LIGHT HEAVY JAMMED

·~~~ 6. Unanchored single message verbal descriptors such as LIGHT TRAFFIC

can also be used. The library of possible word descriptors

were presented in the previous section of this report.

131

VII. TOPIC AREA D - LOCATION AND LENGTH OF CONGESTION

Objectives

To detennine the types of information which familiar and unfamiliar

motorists would prefer on a changeable message sign regarding the location

and length of congestion:

(a) To determine preferences for designation of the location in terms

of distances, cross-street name designations, or exit numbers.

(b) to determine nouns, adjectives, verbs, and modifiers preferred to

indicate this infonnation.

(c) to establish the format of the information.

(d) to establish the message load or minimum amount of information

deemed adequate to convey the information.

(e) to determine differences in the above for designation of the

beginning and end of congested areas.

(f) to determine the capabilities of actual urban freeway commuters

to provide names of cross-streets and relatively accurate distance

information regarding their freeway routes.

(g) to establish preferred modes of designating the location of congestion

for commuters and small city drivers.

132

Background:

Numerous studies have suggested that actual freeway commuters rank the

location of congestion among the most important information they require.

Huchingson and Dudek (]._) found it to be the most frequently requested

information for telephone traffic information services. Dudek and Jones ( 2)

also found it ranked first in importance. Case, Hulbert, and Beers ( 3)

reported it ranked second to lane blockage information.

Bogda no ff and Thompson ( i) reported two public opinion surveys of

message priorities for non-recurrent incidents, which gave contrasting data

on the question of specifically how the location information should be given.

The first survey reported distance information ranked second to lane blockage

while the location by interchange name or ramp was ranked fifth. The second

survey asked directly the motorists preference between distance in miles and

nearest cross-street. Two separate surveys, before and after the energy crisis,

reported 53 percent preferring cross-street designations and 47 percent the

mileage distance.

A study by Heathington, Worrall, and Hoff (~) studied traffic descriptors,

but presumed knowledge of how location information should be presented. They

presented each descriptor followed by the message "NEXT 3 MILES. 11

Since this topic is of considerable importance, an in-depth study of

signing parameters--content, format, load, etc.--was designed which addressed

the questions of both message preferences and the abilities of actual freeway

drivers to provide the location information. The latter was based on the

assumption that the information must be meaningful to the motorists before

they could correctly interpret it and act upon it.

133

Two studies were conducted by TTI relative to modes of presenting loca­

tion and length of congestion information. The first was conducted locally

(College Station) and employed the 11 build-a-sign 11 experimental technique.

The second study was conducted in Los Angeles and involved requesting

specific location information regarding a familiar freeway and, also, prefer­

ences for signs giving the locations in two ways.

134

Study 1 - Descriptors for Congestion Location - Noncommuters

Objectives

To determine the types of information which unfamiliar drivers would pre­

fer regarding the location and length of congestion.

Method

The local study involved the 11 build-a-sign 11 technique (See Chapter III) . .....,,..

The experiment was conducted in the TTI Mediamaster laboratory. Subjects

were handed a packet of 5 x 8 cards each with a sign component message. They

were also provided cartoon drawings depicting traffic situations. Their task

was essentially to select from the sign component messages, a set of messages

which described the situation depicted in the drawing. They were to arrange

the components in a meaningful order and then copy the message onto an answer

sheet, which simulated a blank sign.

Eighty subjects were selected from the subject pool according to a

stratified sampling plan. Forty subjects were assigned to

Condition A-1, B-1 and the other forty were assigned to Condition A-2, B-2.

These conditions differed in their instructional set and task assignment

as follows:

A-1 - Local resident and familiar cross-street, Beginning of congestion picture.

B-1 - Local resident and familiar cross-street, End of congestion picture.

A-2 - Visitor to large city, unfamiliar cross-street, Beginning of congestion picture.

B-2 - Visitor to large city, unfamiliar cross-street, End of congestion picture.

135

The two treatment groups differed in terms of their instructional set as to

their familiarity with the city and, particularly, with the cross-street name.

Each schematic (see Volume 12) depicted either the beginning or end of

a traffic queue at a bridge crossing a four-lane divided highway. In addition,

it gave the street name, the exit number, the distance in miles, and the

designation "You are here" at the beginning of the distance arrow designator.

The independent variables were as follows:

Content

• Choice of subject: CONGESTION, TRAFFIC

• Choice of verb: BEGINS, STARTS, BACKED UP TO, ENDS, CLEARS

• Choice of modifiers: SLOW, FREEMOVING, STOP-AND-GO

• Choice of locational reference: AHEAD, (exit number), (distance:

1 or 2 miles), (street name)

• Choice of write-in filler words: AT, AND, THE, etc.

Format

• Choice of the order in which components were placed in the message.

Load

• Choice of the number of components used.

Familiarity (as established by instructional set)

Beginning or end of the problem (as depicted in the cartoon pictures)

The dependent variable was preference for particular words, formats.

and loadings which would "give you the information you would like to have about

the situation you have encountered. 11

136

Results

Descriptive summaries of the frequency count data for the four

conditions are presented in Tables D-1, D-2, D-3, and D-4. The findings

for Condition A-1 (Familiar, Beginning) were surrrnarized as follows:

1. CONGESTION was preferred to TRAFFIC.

2. BEGINS was strongly preferred to STARTS.

3. AHEAD was preferred to "distance in miles". The "street name"

and "exit number" followed closely in that order.

4. SLOW was the preferred modifier for TRAFFIC, but only 15 of 87

total choices included it.

5. Based upon modal data count, CONGESTION is the preferred first

component and AHEAD, the preferred second component.

6. A message load of three or four components was typical.

The findings for Condition B-1 (Familiar, End) were as follows:

1. TRAFFIC was slightly preferred to CONGESTION;

2. CLEARS was strongly preferred to ENDS.

3. "Distance in miles 11 was very slightly preferred to the other

three designators.

4. Modifiers to the subject were seldom used.

5. No clear-cut format is evident~

6. A message load of three of four components was typical.

137

TABLE D-1 - FREQUENCY COUNT SUMMARIES FOR CONDITION A-1 (FAMILIAR DRIVER, BEGINNING OF CONGESTION)

ORDER OF COMPONENT SELECTION

DESCRIPTION l 2 3 4 5 6 7 8 9

Congestion 19 6 4 l 2

Traffic 6 6 2 l 5 l

Slow 10 l 4

Stop & Go 2 l 2 4 l

Free Moving 2 l l 2 l

Begins l 3 5 l l l

Ends l

Starts l l l

Backed Up To

Clears

Ahead 10 8 4 5 4 l

l Mile 3 7 2 6 3 l l l

At Exit 3 l 2 2 6 l l l

At Hwy 30 l 5 3 3 5 l

TOTAL 44 39 35 27 19 14 6 4 l

138

TOTAL

32

21

15

10

7

12

l

3

0

0

32

24

14

18

189

TABLE D-2 - FREQUENCY COUNT SUMMARIES FOR CONDITION B-1 (FAMILIAR DRIVER, END OF CONGESTION)

ORDER OF COMPONENT SELECTION

DESCRIPTOR 1 2 3 4 5 6 7 8

Congestion 10 4 2 1

Traffic 8 8 1 1 1 1 '

Slow 5 1

Stop & Go 1

Free Moving 2 1 2 1

Begins 1 1 1 1 1

Ends 6 2

Starts 1

Backed up From 1 2 1 1

Clears 1 6 2 2 1 1

Ahead 1 3 4 6 4 1 1

2 Mil es l 3 11 7 3 1 2

At Exit 3 1 1 2 3 2 4

At Hwy 30 2 5 3 6 2 1

TOTAL 33 33 32 27 20 11 4 2

139

9 TOTAL

17

20

6

l

6

5

8

l

5

1 14

20

28

13

19

1 163

The findings for Conditions A-2 (Unfamiliar, Beginning) were as follows:

1. CONGESTION was strongly preferred to TRAFFIC.

2. A verb was seldom used.

3. "Distance in miles" was slightly preferred over AHEAD.

4. Subject modifiers were seldom used.

5. CONGESTION should be the first component of the message.

"Distance" was the third component, but no choice for second

component appeared.

6. A message load of three or four components was typical.

The findings for Condition B-2 (Unfamiliar, End) were as follows:

1. TRAFFIC was preferred to CONGESTION.

2. CLEARS was strongly preferred to ENDS.

3. "Distance in miles" was preferred to AHEAD.

4. Subject modifiers were seldom used.

5. TRAFFIC was the preferred first component and CLEARS the

preferred second component.

6. A message load of three or four components was typical.

140

TABLE D-3 - FREQUENCY COUNT SUMMARIES FOR CONDITION A-2 (UNFAMILIAR DRIVER, BEGINNING OF CONGESTION)

ORDER OF COMPONENT SELECTION

DESCRIPTOR 1 2 3 4 5 6 7 8

Congestion 17 7 1 1 1

Traffic 6 5 2 1

Slow 3 2 1 1

Stop & Go 2 3 1

Free Moving 1 1 2 1

Begins 1 1 1 l

Ends 1

Starts 3

Backed Up To 1

Clears

Ahead 7 7 9 3 1 1

1 Mile 4 4 15 6 2

At Exit 5 2 5 3 6 3 1

At Tree Lane 4 1 3 1 3 1

TOTAL 40 39 35 23 12 5 4 2

141

TOTAL

27

14

7

6

5

4

1

3

1

0

28

31

20

13

i60

'

I

TABLE D-4 - FREQUENCY COUNT SUMMARIES FOR CONDITION B-2 (UNFAMILIAR DRIVER, END OF CONGESTION)

ORDER OF COMPONENT SELECTION

DESCRIPTOR 1 2 3 4 5 6 7 8

Congestion 7 4 2

Traffic 12 5 1 1 1

Slow 2 1 1 1

Stop & Go 3 1

Free Moving 3 1 1 1 2 1

Begins 3 2 1 1

Ends 2 2 3

Starts 1 1

Backed Up From 1 2 1

Clears 10 2

Ahead 1 7 8 3 3

2 Miles 1 7 11 7 2 1

At Exit 5 3 2 2 2 3 2

At Tree Lane 2 3 1 2 1 2

TOTAL 37 36 33 24 15 8 3 3

142

9 TOTAL

13

20

5

4

9

7

7

2

4

12

22

29

1 15

11

1 160

Table D-5 presents frequency count summaries of location descriptors

used with the familiar or unfamiliar driver instructions (collapsed across

beginning and end situations). Note the major changes were increased use

of miles and exit numbers with the unfamiliar driver set and decreased use

of unfamiliar cross-street names. The total usage strongly favors use of

distance infonnation in miles or in the shorter, less explicit notation

of "ahead".

Table D-6 summarizes the frequency data for the subject and the verb for

situations depicting the beginning and end of a traffic queue. CONGESTION

BEGINS is the subject/verb combination most frequently used to depict the

beginning of a queue some distance ahead. TRAFFIC CLEARS is the subject/verb

combination for depicting the end of a queue some distance ahead. When TRAFFIC

was used at the beginning of a queue, the adjective SLOW occasionally was

used. However, its use in the message is not recommended because the percen­

tage using SLOW was small in proportion to those using TRAFFIC without a modi­

fier. The word SLOW may be implied in this context.

Only limited support exists for the use of a verb at all for the begin­

ning of a queue. Only 22 of the subjects used a verb in conjunction with a

beginning state, while 51 subjects used a verb to depict the end state.

Table D-7 summarizes the number of message elements used in construction

of a message. The instructions placed no restrictions on the number of cards

the subject could select. The number of elements used dropped off after 3 com­

ponents and dropped abruptly after 4 components, suggesting drivers recognize

the need for brevity.

143

TABLE D-5 - Effect of Familiarity Instructions on Location Descriptor Choices

Drivers Instructional Set

Familiar Unfamiliar Difference Total

Ahead 52 50 -2 102

Miles 51 60 +9 111

Exit 27 35 +8 62

Name 37 24 -13 61

167 169

TABLE D-6 - Traffic Descriptors for Beginning and End of Queue

BEGINNING END Congestion 59 30

Traffic 35 40

Begins 16 11

Starts 6 3

Ends l 15

Clears 0 26

Backed up From l 10

Slow 22 11

144

TABLE D-7 ~ Numbers of Descriptors Used to Convey Message

1 2 3 4 5 6 7 8 9 Condition A-1 44 39 35 27 19 14 6 4 l

Condition B-1 33 33 32 27 20 11 4 2 l

Condition A-2 40 39 35 23 12 5 4 2 0

Condition B-2 37 36 43 24 15 8 3 3 l

TOTALS 154 147 145 101 66 38 17 11 3

145

Discussion

The findings of the local experiment must be interpreted in the per­

spective of the experimental methods employed to investigate the messages.

All subjects lived in a community of 80,000 and were not regular freeway

commuters. The familiarity set was established by the instructions they were

on the East Bypass (Highway 6) in Bryan while the unfamiliar set was esta­

blished by stating they were in Columbus, Ohio. The stimulus pictures were

identical except for the names given to the cross-street (the familiar dri­

ver, Highway 30, and the unfamiliar driver, Tree Lane). While different sub­

jects were used in the familiar and unfamiliar conditions, one may question

whether or not the subjects were behaving in the same manner as actual day­

to-day commuters who may be intimately familiar with cross-streets, but only

vaguely familiar with distance information.

The results do suggest the use of CONGESTION when the situation involves

the beginning of a queue and TRAFFIC CLEARS when it involves the end of a

queue. The use of distance in miles and/or AHEAD are indicated, but this

generalization is subject to the conditions of the experimental design. (See

Study 2 for further investigation of this variable for day-to-day commuters).

Finally, the results suggest a brief message of three or at most four

message components.

146

Study 2 - Descriptors for Congestion Location - Commuters

Objectives

The regional study was designed to provide an answer to objectives (f)

and (g) and to establish the preferred way of locating congestion when the

drivers were commuters with a backlog of information regarding a local free-

way system.

Method

The method involved the administration of a two-s~ction questionnaire /,,/"

to a stratified sample of eighty-three freeway drivers in the Los Angeles

area (See Volume 12 for the questionnaire).

The first three questions of Section One were asked principally to

get the driver thinking about a particular freeway with which he was familiar.

Question #1 asked the subject to select from a checklist the freeways with

which he was most familiar and included an 11 other 11 category for minor freeways

not in Los Angeles proper.

The second question asked for the freeway on which he traveled the

longest distance to work.

The third question was in relation to this freeway only or any other

freeway with which he was highly familiar. The addition of the second option

allowed for freeway users who perhaps worked locally, yet had driven extensively

to downtown Los Angeles or to other regions of greater Southern California.

The third question asked the driver to indicate the name of the avenue

at which he entered the freeway and the direction he traveled. This informa-

tion was necessary for scoring Question No. 4.

147

Question No. 4 requested that the subjects list in sequence the names of

the cross-streets along the freeway between their points of entry and exit.

The answers given would be individualized, so that scoring involved consulting

a large map of Southern California and checking off the cross-streets

listed against those indicated on the map. Hence, errors of omission could

be readily determined and calculated as percentages of the total cross­

streets along the route.

Question No. 5 requested an estimate of the distance in miles in regard

to the person's freeway trip, again from the point of entry to exit. Question

No. 6 asked for an estimate of the freeway distance between major freeway

interchanges in the Los Angeles area.

The second section of the questionnaire dealt with commuters preference

for two simple signs. One displayed CONGESTION - 3 MILES AHEAD; the other

displayed CONGES1'ION AT LONG BE~CH FREEWAY. The situation posed was that

the driver was in downtown Los Angeles and he had just entered the Santa Ana

Freeway headed for Long Beach, where he planned to exit.

Since the order in which the message appeared in the instructions and

on the answer sheet might bias the choice, two of the four sessions received

one message first and the other two sessions received the other message first.

In this manner, any possible order effects could be determined and the effect

would be counterbalanced so as not to influence the total preference scores.

148

Results

The results of the Los An~eles survey are presented in Tables D-8

through D-11. Responses to the first three questions are not reported

since the questions were included primarily to get the respondents think­

ing about a particular freeway or freeways they traveled to work. All

respondents answered the first question by checking two or more freeways

in the Los Angeles region. All respondents also indicated a particular

freeway they traveled a long distance to work and indicated, for question

3, the name of an avenue at which they entered the freeway.

Table D-8 indicates the percentage of cross-streets which were correctly

identified based upon a recent map of the Southern California area. Those

participating in session A were especially gifted at listing cross-streets

with a median value of 92% correctly given. The session B participants were

significantly poorer in giving cross-streets with a median value of 73%.

Collectively, the 39 respondents listed 85% correctly.

This value is probably conservative for two reasons: 1) Some respondents

traveled several freeways and attempted to list all cross-streets even in

areas remote from their homes; 2) the poorest performance was for those who

indicated a short route with seven or fewer cross-streets. Thus, if there

were 4 cross-streets and 3 were given their score was 75% and if 2 were given,

50%. Had the total percentage cross-streets named been calculated independent

of subjects the percentage score would have been about 90%. However, this

technique would lend too heavy a weight to the exceptional respondent.

149

TABLE D-8 PERCENTAGE OF CROSS-STREET EXITS IDENTIFIED ALONG WORK TRIP ROUTES

( N = 39)

Combined Session A Session B A & B Totals

Ranks Percent Identified Ranks Percent Identified Ranks N %

1-8 100 1-2 100 1-10 10 - 100 9 96 11 1 - 96

10 92...,Mdn 3 92 12-14 3 - 92 11 92

12 90 4 90 15-16 2 - 90

13 86 5 86 17-19 3 - 86 14 86 -..Mdn

15 82 6 84 20 1 - 84 21 l - 82

7-8 80 22-23 2 - 80

16 75 9 75 ~Mdn 24-25 2 - 75 10 71 26 l - 71

17 67 11 67 27-29 3 - 67 18 67

12 63 30 l - 63 13 60 31 l - 60

19 57 14 57 32-39 2 - 57 15 56 34 l - 56

20 50 35 l - 57

16 45 36 l - 45 17 40 37-38 2 - 40 18 40 19 33 39 l - 33

Mdn (10) 92/; Mdn (9.5) 7J.:: Mdn (19.5) 85% --------- --------· . - -··---

150

TABLE D-9

PERCENTAGE ERROR IN ESTIMATING WORK TRIP DISTANCES (N=38)

Tri~s of Less than 5 miles (N=6)

Under = -Subject Est.Distance Actual Distance Error (miles) Percent Over = +

4-B l. 5 3.5 2.0 63 6-B 5.0 4.0 1.0 25 +

15-B 3.0 3.0 0 00 N/A 10-A 3.0 2.0 1.0 50 +

14-A 1.0 1.0 0 00 N/A 16-A 4.0 4.5 0.5 12

Mdn = 1. 0 19 (3.5) 2/4 +

TriES of 5 to 10 miles (N=l2)

a~~~2 Under = -Subject Est.Distance Actua 1 Distance Error (miles} Percent Over = +

5-B 5.0 7.0 2.0 29 7-B 7.5 7.5 0 00 N/A

10-B 10.0 7.0 3.0 43 +

11-B 20.0 9.0 11.0 122 +

12-B 6.5 5.0 1.5 30 +

16-B 11.0 7.5 3.5 47 +

17-B 6.5 7.0 0.5 07 1-A 10.0 7.5 2.5 33 +

7-A 5.0 5.5 0.5 09 11-A 8.0 7.5 0.5 06 + 12-A 9.0 7.5 1.5 20 +

17-A 6.0 7.0 1.0 14

Mdn = 1. 5 25 (6.5) 7/11 +

151

Subject

1-B 2-B 8-B

14-B 2-A 4-A 5-A 8-A 9-A

13-A 18-A 20-A

Subject

3-B 9-B

13-B 3-A 6-A

15-A 19-A 21-A

TABLE D-9 (Cont.)

PERCENTAGE ERROR Ii.'J ESTIMATING WORK TRIP DISTANCES (N=38)

Tri~s of 10 to 20 miles (N,.12)

~~~~~ Under = -Est.Distance Actual Distance Error (miles} Percent Over = +

11. 5 12.25 .75 06 20.0 11.0 9.0 82 + 22.0 18.0 4.0 22 + 6.0 11.0 5.0 45

25.0 17 .o 8.0 47 + 30.0 10.0 20.0 200 + 10.0 13.0 3.0 31 18.0 18.0 0.0 00 N/A 19.0 18.0 1.0 06 + 10.0 11.0 1.0 09 16.0 16.0 0.0 00 N/A 15.0 13.0 2.0 15 +

Mein ,. 2.5 18.5 (6.5) 6/10 +

TriQS of over 20 miles (N=8)

(~;o~~ Under = -Est.Distance Actual Distance Error ~miles} Percent Over = +

13.0 21.0 8.0 38 29.0 27.0 2.0 08 + 22.5 22.0 0.5 02 + 25.0 27.0 3.0 11 25.0 25.5 0.5 02 31.0 23.0 8.0 29 + 40.0 34.0 6.0 18 + 23.0 25.0 2.0 08

Mdn = 2.5 8.0 (4.5) 4/8 +

Total Sampl~ Mdn = 1.75 mi. 18% error + = 19 - = 14

N/A = 5

152

...... 1.n w

Ou.

1

2

3

4

TABLE D-10

FREEWAY DISTANCE ESTIMATION BETWEEN MAJOR INTERCHANGES IN MILES (N=38)

Actual Mean Median Mdn % FWY FROM TO N Distance Estimate Estimate Error

SANTA SAN HARBOR MONICA DIEGO 29 9 10.2 10.0 1/9 11

LONG SANTA SAN BEACH ANA DIEGO 22 10 15.0 14.0 4/lC 40

SAN SANTA SUNSET DIEGO MONICA BLVD 30 4 8.9 6.0 2/4 50

HARBOR COLISEUM SANTA (SANTA MONICA BARBARA) FWY 23 3 5.6 3.0 3/0 0

No Est F %

9 23

16 43

8 21

15 39

TABLE D-11 RANK ORDER OF ESTIMATES TO QUESTIONS l THROUGH 4

RANK QUESTION #1 RANK QUESTION #2 RANK QUESTION #3 RANK QUESTION #4

l 21 l 30 l 40 l 30 2 20 2 25 2 25 2 20

3-4 15 (2) 3 23 3-4 20 (2) 3 18 5-10 12 (6) 4-5 20 (2) 5 18 4 10

11 11 6-7 18 ( 2) 6 12 5-6 6 (2) 12-17 10 (6)+• 8 16 7 11 7 5.

18 9 * 9-10 15 (2) • 8 10. 8 4 19-20 8 (2) 11-12 14 (2)+ 9-12 8 (4) 9-12 3 (4)+ *

21-25 7 (5) 13-14 12 (2) 13 7 13 2.5 26-27 6 (2) 15 11 14-16 6 (3)+ 14-18 2 ( 5) 28-29 5 ( 2) 16-19 10 (4)* 17-21 5 (5) 19 1.5

CODE 20 7 22 4.5 20-23 1.0 (4) 21 6 23-24 . 4 (2 )* .. = Median 22 2 25 3.5

• = Mean 26-28 3 ( 3) 29 2

* = Actual 30 1

Table D-9 presents the distance estimates in miles of the route given

in the previous answer. Also shown is the actual measured distance, the

error in miles, the percentage error expressed in relation to the actual

distance, and the direction of error (overestimation or underestimation).

These data were further analyzed in terms of the length of the route

taken to work. As indicated at the bottom of the second page of Table D-9,

the average error was 1.75 miles or 18%.

As expected the absolute error in miles increased somewhat with the

length of the trip, but the percentage error decreased for trips longer

than ten miles. There was a slight, but insignificant tendency to over­

estimate the distance traveled.

These data were for a highly familiar route which the respondent had

traveled daily or many times. Table D-10 summarizes the distance estimation

for major freeways in the Los Angeles region. Two routes were comparatively

long (9 and 10 miles) and two routes were relatively short (3 and 4 miles).

Although the routes were all major ones, the respondents performance was

highly variable and much poorer.

As indicated in the last column of Table D-10, 21 to 43% of the subjects

left this question blank suggesting they had no conception of the distance.

Some subjects gave estimates for some freeways and not others.

The results indicate a tendency to overestimate all distances. The mean

error was somewhat larger than the median error with mean error reflecting

some extremely large deviations.

Table D-11 gives the mileage estimates in rank order beginning with the

largest estimates. An arrow and circle indicate respectively the median and

mean estimates and an asterisk gives the actual distance.

155

Table D-12 presents the results of the preference study which simply

called for a choice between distance in miles and in distance by intersecting

freeway or cross-street. This test was given to four sessions designated A,

B, C, and D. In session A and B, the cross-street was given on the left and

in sessions C and D the distance was given on the left. Unfortunately, the

sessions did not have exactly the same numbers of subjects. Sessions A and

B had 22 subjects each. Session C had 16 and Session D had 23. Hence, there

were 44 subjects with the cross-streets first and 39 with distances first.

Table D-12 indicates that there were no order effects. 41 subjects

selected the first or left-hand message and 42 subjects preferred the second

or right-hand message. In all sessions except Session A the cross-street

designation was preferred to the distance designation. Overall, 48 of the

83 subjects (58%) preferred the cross-street name. These differences cannot

be attributed to order effects since there was no tendency to select the

first message.

Discussion:

The findings of the second study do not support the results of the first

study relative to designation of the location of a problem. The first study

employed a local Bryan-College Station sample and reported distance in miles

was preferred to the cross-street name. Seventy-one percent of those giving

either a name or miles selected miles when they were told to behave as unfam­

iliar drivers and 58% selected miles when told to behave as familiar drivers.

However, when actual co!Tllluters were employed as subjects in Study 2, 58%

preferred the cross-street designation. These findings support those of Bog­

danoff and Thompson ( 4) who conducted two separate surveys.

156

TABLE D-12 PREFERENCES FOR LOCATION OF CONGESTION (N=83)

CONGESTION Message Message Pref. GIVEN BY Given First Given Last Freq.

w w w w CROSS-STREET 9 16 9 14 48

w w ~ w DISTANCE 7 9 13 6 35

Frequency of Selection of First or Second Message 41 42 83

Data presented for Sessions A, B, C, and D with order of signs on Answer Sheet counterbalanced. N=44 with Cross-street first. N=39 with Distance first. Order effects were found N.S.

157

The findings of the second study also indicated that commuters are

highly familiar with the names of cross-streets along a route they travel

frequently and that indicating an accident or congestion by cross-street

designation would not present a communications problem. By contrast, giving

the distance in miles could present a communications problem for some drivers.

The second study did not ask for distances to specific interchanges along the

commuters own route since this would be highly individualized. However, the

implication was if they could not estimate the distance of their work trip

accurately they would have a similar difficulty in estimating the distance

to any particular en route interchange. Study 2 also demonstrated great

variability and a tendency to overestimate distances to the most common free­

way interchanges in the Los Angeles area.

158

Design Implications

1. When displaying on a changeable message sign the location of congestion

or a traffic problem, the message used will vary somewhat with the

location of the sign and with the traffic engineers knowledge of whether

the drivers will be primarily familiar or unfamiliar with the area.

2. If the drivers are unfamiliar as, for example, a sign location outside the

urban area or along a bypass, loop, or beltway, the messages recommended

are as follows:

(a) Unfamiliar drivers

(1) Back of a queue:

Congestion

Miles

(2) Front of a queue:

Traffic Clears

Miles

159

Congestion Begins

Miles

3. If the drivers are primarily commuters as, for example, a sign located

within the city on major freeways, the messages recommended are as follows:

(b) Familiar drivers (commuters)

(1) Back of a queue:

Congesti an

at

(Cross-Street)

(2) Front of a queue:

Traffic Clears

at

(Cross-Street)

160

REFERENCES

1. Huchingson, R. D. and Dudek, C. L. Development of a Dial-in Telephone System Based on Opinions of Urban Freeway Motorists. Transportation Research Record 536, 1975.

2. Dudek, C. L. and Jones, H. B. Real-Time Information Needs for Urban Freeway Drivers. Texas Transportation Institute Research Report 139-3, August 1970.

3. Case, H. W., Hulbert, S. F. and Beers, J. Research Development of Changeable Messages for Freeway Traffic Control. University of California, Los Angeles, UCLA-ENG-7155, August 1971.

4. Bogdanoff, M. A. and Thompson, R. P. Evaluation of Warning and Information Systems - Part 1, Changeable Message Signs. Report No. CA-DOT-07-3130-1-75-5, California Department of Transportation, July 1976.

5. Heathington, K. W., Worrall, R. D. and Hoff, G. C. An Analysis of Driver Preferences for Alternative Visual Information Displays. Highway Research Record 303, 1970.

161

VIII. TOPIC AREA E - LANE BLOCKAGE (CLOSURE) AND AVAILABILITY DESCRIPTORS

Objectives

To establish effective wording and/or symbolic coding to depict lane

blockage on freeways having four or more lanes in one direction. Specifically,

(a) to determine whether side mounted signs can be used to describe lane

blockage and avail&bility information.

(b) to determine effective words and/or symbology to describe lane

blockage and lane availability information.

(c) to determine the importance of color.

( d) to determine the rel~tionship between color and symbolic codes.

(e) to determine driver interpretation of 11 blocked 11 versus "closed" mes-

sages.

Background

Overhead red 11 X11 and green arrow lane use control signals have been used

effectively to indicate lane blockage and lane availability (]J. It is anti­

cipated, however, that many changeable message signs used for informing dri­

vers of freeway conditions that include lane blockages and availability will

be side mounted. In addition to a possible disassociation with specific lanes

using side mounted signs, the use of matrix signs precludes color coded red

11 X11 and green arrow designators.

On a three-lane freeway section word descriptors such as LEFT LANE BLOCKED,

MIDDLE LANE BLOCKED, and RIGHT LANE BLOCKED are probably effective descriptors.

When there are more than three lanes, word descriptors may become confusing to

drivers, particularly when describing conditions on one of the two inner lanes.

162

Lane-use control signals have been adopted by the Federal Highway Admin­

istration as a national standard to permit or prohibit the use of specific lanes

of a street or highway or to indicate the impending prohibitions of use (_g_).

According to the MUTCD, lane-use control signals are now most corrononly used for

reversible-lane control. (They may) also be used u.'here there is no intent

or need to reverse lanes. Some applications of this type are:

1. On a freeway, where it is desired to keep traffic out of certain

lanes at certain hours to facilitate the merging of traffic from

a ramp or other freeway.

2. On a freeway, near its terminus, to indicate a lane that ends.

3. On a freeway or long bridge, to indicate a lane which may be

temporarily blocked by an accident, breakdown, etc.

The meanings of the current standards are listed below(.£).

1. A steady DOWNWARD GREEN ARROW means that a driver is permitted to

drive in the lane over which the arrow signal is located.

2. A steady YELLOW X means that a driver should prepare to vacate,

in a safe manner, the lane over which the signal is located because

a lane control change is being made, and to avoid occupying that

lane when a steady RED X is displayed.

3. A flashing YELLOW X means that a driver is permitted to use a lane

over which the signal is located for a left turn, using proper caution.

4. A steady RED X means that a driver shall not drive in the lane over

which the signal is located, and that this indication shall modify

accordingly the meaning of all other traffic controls present. The

driver shaU obey aU other traffic controls and foUow normal safe

driving practices.

The laboratory studies concerned with lane blockage (closure) signs

were conducted through a series of four studies.

163

Study 1 - Words and Coding Methods - Understanding of and Preferences for Messages (Part 1)

Objectives

The primary objective of Study 1 was to determine whether drivers under­

stood side mounted signs depicting lane blockage (closure) and lane availability

information when the signs contained no titles. Secondary objectives were to

determine drivers' preferences for lane blockage (closed) and lane availability

information signs, and to determine their preferences. for the sign title.

Method

The candidate sign designs are shown in Figure E-1. Ten basic sign designs

were developed and used in the experiments. Each sign was designed to display

a two-lane blockage (closure). Also, each sign presented messages that were

11 anchored 11 without lane number designators and with lane number designators,

yielding a total of 20 basic signs. Anchoring implies presenting the extreme

values of the message and the relative positioning of the value that currently

applies. For example, for l~ne blockage information, anchoring is accomplished

by displaying the lanes blocked (closed) by their relative position on the

sign (left-to-right). Adding lane numbers to the sign reinforces anchoring of

lane blockage information.

In addition to the above signs, 13 signs, coinciding with the signs dis­

playing lane blockage (closure) information, were used to display conditions

when all lanes were clear of obstructions. This resulted in a total of 33 signs. i/

The study was conducted in the Mediamaster laboratory. Groups of approxi-

mately five subjects were shown a sign projected on the screen and asked to

press a button when they thoµght they understood the meaning of the sign.

164

FIGURE E-1 CANDIDATE LANE BLOCKAGE (CLOSURE) SIGN DESIGNS

Two Lines Blocked Sutu1 All LIMI Open Stltus

[]] f1'I lr{,J 0 2 J

~ 0 ~ 0 SiMllt H Stqn 35

~ ~ ~ ~ Stgn 1

Rad x Stgn 11 Stgn 41

Red x

j [t] [!] 0 ltJ 1 z 3 4 ltJ [t] [t] [t] 1 2 3 4

[!] [!] [!] [!] [!] [I] [I] [I] S1gn Z Sign 32

Rid X, Green ArrcM Sign \Z GrMn Ar-rows Stgn 42

Red X, Green Arl"O'l:d Gret:n Arrows

I® ® © © 1 2 3 4 @ @ @) @) I 1

Sign 3 © © ® @ @) @ ® @ Stgn 33

Red Beacon 51gn 13 S1gn 43

Red Beacon

~~ @ @ \ z 3 4 @ @ ® © 1 z 3 o @ © f3I ® ~ ® ® ® ® © @ @ @

® 0 ® <rib © ® © © S1gn 4 51gn 34

Red and Green Brt1cons Sign 14 Green Bucons Sign 44 Red and Green Beacons Green Beacons

181.0CKED BLOCKED I BLOCKED BLOCKED

Sign S Sign JS Stgn 45 Stgn 15

I CLOSED CLOSED I Sue H Stgn 35 s- 11 Sign 45

CLDSED CLOSED Sign 6

Sign 16

BLOCKED BLOCKED

OPEN OPEii BLOCKED BLOCKED OPEN OPEN OPEN OPEN

St90 7 OPEN OPEN Stgn 37 OPEN OPEN OPEN OP£11

S1gn 17 Si90 47

CLOSED CLDSED Sant H Stgn 37 S- H Sign 47

OPEN OPEN CLOSED CLDSED

OPEN DPEN Sign 8

Sign 18

x x Sdll IS Stgn 35 Sim IS Sign 45

x x Sign 9

S1gn 19

+ + 2

+ x x • + + + + + + + + x x 519'1 40 Si9R 10

S1gn 20 Stgn SO

LEFT LANE BLOCXED RlljltT LANES BLOCKED Lffi LANES BLOCKED

LEFT CElllER LANE BLOCKED

Sign 21 Sign ZZ Sign 23

Note: A11 1tign1 arw Wlitt an grnn wt~ the except1on of 11911 porttons H not.cl.

165

This provided the measurement of reaction time. They were then instructed

to write the meaning in an "open-ended" response. The process was repeated

for each sign. Reaction time of each subject was recorded by an obs~rver

monitoring the electronic reaction time recorder. Since the subjects were

viewing the sign designs for the first time, the measured response can be

interpreted as those of unfamiliar drivers.

The subjects were instr~cted that the sign was at the side of the road

so there was no clue in the instructions that the messages dealt with lane

status. These were inferences the subject had to make.

Four randomized orders of presentation were used. Each group was shown

one of the four orders. Seventy subjects participated in the experiment.

The following is the breakdown by presentation order:

Order Number of Subjects

Order A 19

Order B 12

Order C 19

Order D 20

70

The independent variable was the sign design. The dependent variables

were the frequency of errors in describing the meaning of the signs, and the

reaction time (interpretation time) to the signs.

Results

A summary of subject (unfamiliar driver) sign interpretation errors and

reaction times for the candidate signs displaying lane blockage (closure)

166

information (Signs 1 through 20) ~s given in Figure E-2. The data reveal

that, as a rule, the signs containing verbal descriptors (BLOCKED/CLOSED/OPEN)

displayed relative to each lane, anchored by lane, or both resulted in the

least number of errors and the lowest reaction times. Signs 8, 15, 17, 18,

7, and 16 resulted in l, l, L l, 3, and 6 errors (1, l, l, l, 4, and 8 per­

cent). Associated average reaction times of 5.3, 5.2, 5.5, 4.7, 6.0, and

5. 1 seconds were among the lowest of the group. In contrast signs 1 and 9

containing X's resulted in the greatest number of errors: 25 (36 percent).

The X's displayed on the sign were assumed to be anchored with each lane by

their relative positioning on the sign. The average reaction times for these

signs were among the highest.

A Multinomial Test indicated significant differences in errors between

the signs was highly significant (x2 = 61.8).

An Analyses of Variance of reaction times to the candidate sign designs

(Table E-1) revealed significant differences between the signs at the .05

level. A Tukey Test was then applied to the data to determine the nature of

the sign differences. The Tukey Test was selected because it is a more con­

servative test than the Newman-Kuels or Duncan and it minimizes the Type I

error. The results of the Tukey Test shown in Table E-2, are interpreted

as follows: Signs underlined by a common line do not differ from each other;

signs not underlined by a common line differ. Thus the following differences

in reaction times were noted at the .05 level:

Signs

18

6, 15, 16

5, 7, 8, 13, 17, 20

No other di ffcrcnces Here found.

<

<

<

167

Signs

9, 10, 14

9' 10 9

FIGURE E-2 -----

ERRORS AND REACTION TIMES ASSOCIATED WITH CANDIDATE LANE BLOCKAGE (CLOSURE) SIGN DESIGNS - UfffAi~ILIAR DRIVERS

25 (36)

!]~~01 Sign 1

Red X

16 (23)

I ltl [!] [!] oo I Sign 2

Rtd X, Green Arl"C*

19 (27)

I®© 0 0 I Sign 3

Red Blacon

19 • ® ® © @ @

Sign 4

(27)

:1 Rad and Green Beacons

15 (21)

I BLOCKED BLOCKED I Sign 5

11 (16)

I CLOSED CLOSED I Sign 6

3 (4)

BLOCKED BLOCKED

OPEN OPEN

Sign 7

___ 1 __ ~1) CLOSED

x

•

CLOSED

OPEN OPEN

Sign 8

25 (36)

22 x

Sign 10

x I

(31)

• I

Sign 11

Red x

21 (30)

~ooctJdJI Sign 12

Red X , Green Arrow

21 (30

Sign 13

Rici Beacon

24 l z 3 4

~ ® 6 ® © @ © e

Stgn 14

Rid and Green B11con1

1 (1)

BLOCKED llOCKED

Sign 15

6.7

[m ~ ~ 0 Stgn I Red X

7.6

Red X. Green AITOW

6.8

[@ © ® ® Sign 3

Red a.icon

7.0 ®®@I @ ® ~J

Red and Green Beacons

5.5

[BLOCKED BLOCKED I Sign 5

6 (8) 4. 9 ~--------. I CLOSED CLOSED I

CLOSED CLOSED Sign 6

(1) 6.0

BLOCKED BLOCKED

BLOCKED BLOCKED OPEN OPEN

OPEN OPEN Sign 7

1 5.3 CLOSED CLOSED

CLOSED CLOSED OPEN OPEN OPEN OPEN

Sign 18 Sign B

12 (17) 9.3

x x 51911 19

Stgn 9

15 8.2

+ + • x ~ Stgn 20 1191' 10

7.1

Sign 11

Red X

6.7 l z J 4

II] II] [!] 0 Sign 12

Red X, Green Arrow

5.7 l 2 4

®®~@ Stgn 13

Red Beacon

7.7 l z J

® ® ~ © @ ©

Sign 14

4

® @

Rad and Gl'ffn Beacons

5.2

BLOCKED BLOCKED

Sign 15

5.1

CLOSED CLOSED

Sign 16

5.5

BLOCKED BLOCKED OPEN OPEN

Sign 17

4.7

CLOSED CLOSED

OPEN OPEN

Sign 18

6.9

x Sign 1g

6.2

[~ + x x Stqn 20

g/ Humber of errors followed by perccntace of errors. Number of subjects• 70

'£/Number of subjects ranged between 65 and 70. Average number of subjects• 68

168

Source

Signs

Subjects Error

TABLE E-1 ANALYSIS OF VARIANCE FOR REACTION TIMES ASSOCIATED

WITH CANDIDATE LANE BLOCKAGE (CLOSURE) SIGNS -UNFAMILIAR DRIVERS

d. f.

19 69

1275

SS

1865.6 42000.2 30181.2

MS

98. 19 608.69

23.67

** Significant at .01 level

169

F

4.15**

...... -...J 0

Sign Number 18 6 16

Average Reaction 4.7 4.9 5. l Time

TABLE E-2 TUKEY ANALYSIS OF REACTION TIMES ASSOCIATED

WITH CANDIDATE LANE BLOCKAGE (CLOSURE} SIGNS -UNFAMILIAR DRIVERS

15 8 17 5 13 7 20 l 12 3 19 4

5.2 5.3 5.5 5.5 5.7 6.0 6.2 6.7 6.7 6.8 6.9 7.0

11 2

7 .1 7.6

Note: Signs underlined by a common line do not differ from each other; signs not underlined by a common line do differ at .05 level.

14 10 9

7.7 8.2 9.3

Another review of Figure E-2 reveals that signs 18, 6, 16, and 15 were

signs containing anchored verbal descriptors (BLOCKED/CLOSED/OPEN). Sign 9

contained arrows displayed to indicate the lanes blocked but were not anchored

by lane numbers. Sign 10 displayed both X's and arrows that were anchored

by their relative positioning on the sign.

The analysis of the individual signs indicated certain patterns: Signs

with verbal descriptors tended to result in better performance than the other

designs containing X's and arrows or beacons. Additional analyses were thus

conducted to determine whether differences existed between signs grouped according

to design similarities. The grouped signs are shown in Figure E-3 along with

the group average errors and reaction times.

An analysis of variance presented in Table E-3 revealed significant

differences in the number of errors. Tukey's Test shown in Table E-4 re­

sulted in the following significant differences in errors at the .05 level:

Groups Groups

C, D < E, A, B

No other differences were noted.

Analysis of reaction times for the grouped sign designs (Table E-5)

revealed significant differences at the .05 level. Tukey's Test (Table E-6)

resulted in the following differences in reaction times at the .05 level:

Groups

C, D

No other differences were noted.

<

Groups

E

In summary, sign designs containing verbal descriptors anchored by lane,

resulted in significantly fewer errors than the other sign designs. Verbal

descriptor signs also resulted in significantly lower reaction times than

171

FIGURE E-3 ERRORS AND REACTION TIMES OF GROUPED SIGN DESIGNS -

UNFAMILIAR DRIVERS

Average £rror,; A~r191 Amactton Tl• (Sec.)

I []] ~ ~ m I l 1 2 l 4

I I []] ~ ~ m I l 1 2 j 4

~ ill ~ ill ~ ill ~ ill Stvn 1 Sivn 1 Red X S1gn 11 Red x Stgn 11

20.0 Red x 7.02 Red x

I [t] [!) m [t] I I 1 z ] 4

I I [t] [!) [!) [t] I I 1 2 l 4

[t] !I] [!) [!) [t] [i] 0 0 Stgn 2 Sign 2

Red X. Green ArroM Sign 12 Red X. G.-een Arrow Stgn 12

Rtd 1. Green Arl"Ollf Red x. Green Arrow

I@ @ © © I I 1 2 l 4

I I@ @ © © I I 1 2 3 4

© © @ @ © © @ @ Stgn 3 Sign l

Red Beacon Stvn 13 Red a..con Sign 13

20.8 Red Beacon 6.80 Red Beacon

I G ® ® @

I I 1 2 ] 4

I I e ® ® fl!)

I I 1 2 ] '

© e @ © G ® e ® © 0 @ © ~ ® • ® ® 0 ® 0 ® fJ ® • Stgn 4 Stvn 4

Red and Green Beacons Stgn 14 Red and Green Beacons Sip 14 Red and Green Beacons Red and Green Beacons

I

I

I

I

I BLOCKED 3 I BLO:KEO

2 ]

IL~UD I I BLOCKED BLOCKED I l BL~KED 2 3 Bl~KED I Sign 5 Sign 5

Stgn 15 Si90 15

8.3 5.18

I CLOSED CLOSED I I

1 2 l ' I

I CLOSED CLOSED I I 1 2 l ' I CLOSED CLOSED CLOSED CLOSED

Sign 6 Sign 16

Stgn 6 Stgn 16

l BLOCKED BLOCKED I I 1 2 3 , I I ILOCKEO BLOCKED I I 1 2 3 ' l OPEN OPEN BLOCKEQ BLOCKED OPEN OPEN BLOCKED BLOCKED

Sign 1 OPEN OPEN Sign 7 OPEN OPEN

Stgn 17 Stvn 17

1.5 5.38

I CLOSED CLOSED I I OP:N

2 ] 4

I I a.osEo CLOSED I I 1 2 ] 4

I OPEN OPEN CLOSED CLOSED

OPEN OPEN CLOSED CLOSED OPEN OPEN OPEN

Stvn B Stvn 8 St90 18 st90 18

I x I I 1 2 3 ' I I x x I I

1 2 ] ' I x x x x x

Stgn 9 Sign 9 Stgn 19 Si90 19

18.5 7.65

I t I I 1 2 J 4 I I t I I 1 2 ] 4 I t x x + + t x x + + x x x x

St90 10 st90 IO

Stp 10 st,. 20

172

TABLE E-3 ANALYSIS OF VARIANCE OF ERRORS FOR GROUPED SIGN DESIGNS -

UNFAMILIAR DRIVERS

Source

Groups Error

d. f.

4

15

SS

1163. 7

285.5

MS

290.9 19.0

** Signific9nt at .01 level

Sign Group

Average Errors

D

1.5

TABLE E-4 TUKEY ANALYSIS OF ERRORS FOR GROUPED

SIGN DESIGNS -UNFAMILIAR DRIVERS

c E A

8.3 18. 5 20

173

F

15.3**

B

20.8

Source

Groups Error

TABLE E-5 ANALYSIS OF VARIANCE OF REACTION TIMES FOR

GROUPED SIGN DESIGNS -UNFAMILIAR DRIVERS

d. f.

4 11

SS

18. 6

9.4

MS

4.65 .8545

* Significant at .05 level

Sign Group

Average Reaction Time

TABLE E-6 TUKEY ANALYSIS OF REACTION TIMES FOR

GROUPED SIGN DESIGNS -UNFAMILIAR DRIVERS

c D B

5. 18 5.38 6.80

174

A

7.02

F

5.44*

E

7.65

the white on green X and arrow designs (Groups E). The high reaction times for

Sign 9 and Sign 10 were major contributors to this difference.

It was of interest to determine whether average reaction times were dif­

ferent to the signs with lane numbers (6.08 seconds) and those without (6.73

seconds). A paired data analysis revealed that there was no significant

difference.

The final analysis cond~cted in Study 1 was concerned with the errors

associated with the "all lanes open" status signs shown in Figure E-4.

Although the results may be of some interest they may be somewhat question­

able. Drivers were asked ta indicate the meaning of signs that correlated

with lane blockage signs. Sign 35, for example, was a blank sign, and ob­

viously one would not expect drivers to interpret the meaning of a blank

sign without knowing what the sign was used for. Also, many of the other

signs illustrated beacons or other inserts that were not illuminated and

thus appeared as a blank sign.

Discussion

The results suggest that side mounted lane blockage (closure) signs

with verbal lane status descriptors anchored by lane can be interpreted by

unfamiliar drivers even when the sign does not contain a title. All the

other candidate signs tested resulted in high percentages of errors and

suggest that the designs are not adequate to communicate the intended message.

This would suggest that these candidate displays should contain a title.

It was not unexpected that verbal signs would result in fewer errors

in meaning than coded signs, because the latter are dependent upon at least

one-trial learning. This does not, however, mean that "X's and arrows" would

175

FIGURE E-4 ERRORS ASSOCIATED WITH ALL LANES OPEN STATUS SIGNS -

UNFAMILIAR DRIVERS

26 (37) Sll!lt II Sl;n 35

1 z ] 4

I ~ ~ ~ ~ Stgn 41

9 (13) 9 (13) Ii] !ii ltJ [i) I 1 2 ] 4

I [t] ltJ [i] [i] . S1gn 32

Green Arro.tS St9n 42 Grettn ArrOllls

35 ~50) 27 (39)

1~ ~ @ ~1 I@ 2 J 4

I ~ ® ~ sign ]]

St90 4l

13 19) 13 (19) @ • 0 @ I 2 J •

I © © © © Et G @ G © © © ® I Stgn l4

Gl"ffn h1con1 Stgn 44 Green Bea.cons

32 {46) 19 (.27] I r-2 Sign 35

Stgn 45

SUit IS Sign 35 Slet H Sign 45

1 1) 0 ·o OPEN OPEN OPEN OPEN

$t9n JI OPEN OPEN OPEN OPEN

St90 47

s .... 519" ]7 s .. II Sttn 47

S- 11 Stgn !5 S.. 11 Stgn 45

14 (20) 17 24

+ + + + I J

+ + + + 519" 40

St90 !IO

176

··;_:,_

not be effective once the code is known. In fact, the required physical

dimensions of the verbal signs would necessarily be much larger than the

coded signs because of the letter size requirements for the display.

177

Study 1 - Words and Coding Methods - Understanding of and Preferences for Messages (Part 2)

Objective

To determine driver preferences for sign designs.

Method

The second part of the experiment was a card sort study. Photographs

of the ten basic signs plus one additional sign design containing a word

message were presented to the subjects that participated in Part 1. In

contrast to Part l, the photographs used in Part 2 depicted one-lane block­

ages. The subjects were told the meaning of the signs and were asked to

arrange the signs in the order in which they felt did the best job in getting

the message across to the drivers. Random card orders were presented to each

of the 83 participants.

The independent variable was the sign design. The dependent variable

is the sum of all the sign rankings across subjects.

Results

The sign designs used in the card sort study are shown in Table E-7

in the preference order of the subjects. Ranking data are shown in Table E-8.

A Chi Square analysis revealed that the rankings are not evenly distri­

buted (x2 = 162.4). An inspection of Table E-8 suggests that Signs 8, 7, 2,

and 10 consisting of either word descriptors or X and arrow indications

anchored by lane were ranked significantly higher than the other sign designs.

178

TABLE E-7 DESIGN PREFERENCES FOR LANE BLOCKAGE (CLOSURE) SIGNS

Rank

Sign 8 I CLOSED OPEN OPEN OPEN I

Sign 7 BLOCKED 2 OPEN OPEN OPEN

Sign 2 I [JJ [i] []] [!] I 3 Red X, Green Arrow

Sign 10 I + + x + I 4

_J Sign 4 @ @ © @ 5 Red and Green @ © @ ® Beacons

Sign 1 I ~ ~ ~ llf] 6 Red X

Sign 21 LEFT CENTER LANE BLOCKED 7

Sign 5 BLOCKED 8

Sign 9 x 9

Sign 6 CLOSED I 10

Sign 3 © @ ® w I 11 Red Beacon

Note: Signs are·white on green with the exceptions noted.

179

Sign Number

8

7

2

10

4

1

21

5

9

6

3

TABL£ E-8

PREFERENCES FOR VERBAL AND CODING LANE BLOCKAGE (CLOSURE) SIGNS

Sum of Average Ranks Rank

281 3.38

282 3.39

301 3.62

314 3.78

457 5.51

470 5.66

474 5. 71

477 5.75

527 6.35

528 6.36

540 6.51

X2 RANKS = 162.4**

180

Revised Rank

1

2

3

4

5

6

7

8

9

10

11

Discussion

The results suggest that drivers prefer to have anchored information on

a sign for each lane. It appears desirable that an OPEN or BLOCKED indication

be given for each lane using either word or coded descriptors. Verbal descrip­

tors and X's and arrows were preferred over the use of beacons to signify lane

conditions.

181

Study 1 - Words and Coding Methods - Understanding of and Preferences for Messages (Part 3)

Objective

To detennine driver preferences for sign titles.

Method

In the third part of the study, the same subjects were asked to select

one of three alternative titles for the sign. If they believed that no title

was necessary or if the subjects had another title alternative, they were to

so indicate.

The independent variable was the sign design. The dependent variable

was the frequency of choice.

Results

The frequency of sign title choices is shown in Table E-9. The results

show that:

l. The choice No Title Needed was selected significantly more

frequently (40 percent of subjects) than the other alternatives.

2. LANE CONDITION AHEAD was the second choice, having been selected

by 31 percent of the subjects.

Discussion

The results indicate that once drivers become familiar by learning the

meaning of the lane blockage (closure) signs, they prefer not to have the

sign titled. However, results of part 1 of the study indicated that

untitled signs, other than the BLOCKED BLOCKED OPEN OPEN type signs,

would not be understood by unfamiliar drivers.

182

TABLE E-9

DRIVER PREFERENCE OF SIGN TITLES FOR LANE BLOCKAGE (CLOSURE) SIGNS

Title

LANE BLOCKED AHEAD

LANE CONDITION AHEAD

LANE CLOSED AHEAD

No Title Needed

Other Titles

* Significant at .05 level

Total

Number of Subjects

11

26

12

34*

2

85

TABLE E-10

DRIVER PREFERENCE OF LANE NUMBERS ON LANE BLOCKAGE (CLOSURE) SIGNS

Lane Numbers Preferred

Lane Numbers Not Pref erred

Total

183

Number of Subjects

42

43

85

Percent

13

31

14

40

2

100

Percent

49

51

100

Study 1 - Words and Coding Methods - Understanding of and Preferences for Messages (Part 4)

Objective

This part of the study was concerned with determining driver preference

for having lane numbers on roadside signs (where there was no obvious associa­

tion as with overhead signs).

Method

A slide illustrating a lane blockage sign with lane numbers was presented

to the subjects who were asked to indicate their preference. Subjects were

told that the numbers stood for the respective lanes. Eighty-five subjects

responded.

The independent variable is the sign design. The dependent variable is

the frequency of sign selection.

Results

Driver preferences for lane numbers are shown in Table E-10. An analysis

indicated that there was no significant difference between the number of drivers

preferring lane numbers versus those that did not.

The results were inconclusive as to whether or not subjects preferred the

addition of numbers as a cue to particular lane status. If the status of all

lanes is given, then the number is essentially a redundant cue. However, if

only the blocked lanes status was given (e.g., signs 5, 6, and 9), the numbers

are not redundant at a distance. The numbers give the viewer his bearing or

orientation. In this study, the subjects• preferences were made after seeing

all the various combinations in previous studies, so the evaluation was overall

preference - not tailored to the particular sign.

184

Study 2 - Words and Coding Methods - Understanding of Signs

Objective

The objective of this study was to determine the effectiveness of each

candidate lane blockage {closure) sign when drivers are knowledgeab1e of the I

meaning of the signs. These drivers may be assumed to be freeway commuters.

Method

The experiment was conducted similarly to Study 1. ·In this case, however,

the participants were told that the signs projected on the screen represent

signs designed to tell the driver that the particular lane~ are either unob­

structed, or are blocked due to an incident. They were instructed to press

the proper combination of buttons on their tables as quickly as possible,

which coincided with the lanes depicted by the message on the sign as being

blocked. If the sign indicated that all lanes were unobstructed, the partici­

pants were instructed to press all four buttons. Subject response and reaction (,...-'

time were automatically determined via the Mediamaster equipment.

Three randomized orders of presentation were used. Each subject group

was shown one of the orders. Eighty-six subjects participated in the experiment.

The following is the breakdown by presentation order:

Orqer

A

~

c

185

Number of Subjects

29

28

29

86

The same sign designs used in Study 1 (Part 1) were also used in

this experiment. However, three new sign designs, Signs 21, 22, and 23,

with verbal lane blockage descriptors were added. The candidate sig~ de­

signs are shown in Figure E-5.

The independent variable was the sign design. The dependent variables

were the frequency of errors and the reaction time.

Results

A summary of subject errors in sign interpretation and average reaction

times after being told the ~eaning of the signs (familiar driver) is given

in Figure E-6. A review of the results reveals, as expected, a significant

reduction in errors and reaction times in comparison to those for the un­

familiar driver (Figure E-2).

Among the 23 sign designs studied, Signs 16, 22, 21, and 23 had the

!largest number of errors (8, 8, 7, and 5). Signs 21, 22, and 23 were the I

new signs containing verbal messages describing which lanes were blocked.

Signs 21, 22, 14, and 16 had the longest average reaction times.

A Multinomial Tes.t reveqled that significant differences existed be­

tween the number of errors associated with the sign designs (x2 = 61.8).

An Analysis of Variance (Table E-11) also indicated significant differences I

between the average reaction times. A Tukey Test (Table E-12) resulted in

the following reaction time qifferences at the .05 level:

Signs Signs

1, 2, 6, 7, 8, 9, 15 < 14' 16' 21 ' 22

3' 4' 5' 10' 11 ' 13' 18' 23 < 14, 21, 22

186

FIGURE E-5 CANDIDATE LANE BLOCKAGE (CLOSURE) SIGN DESIGNS -

FAMILIAR DRIVERS

EM'Ort A.Vllr•91 .. acttOfl Tt• (Sec.)

ill ~ ~ III fJ m ~ III ill ~ ~ III fJ m ~ IXl Stgn 1 Stgn 1

Red I St9n 11 Rad I Sign 11

Red I Rod I

I [t] IIl m [t] 1 2 l 4 I [t] [i] m [t] 1 2 l 4

Stgn 2 [i] [II [i] w

Sign 2 [II [II Ii] w

Red Jt. Green A.-raw Sign 12 Red Jt • GrHn A,...,,.. Sign 12

Red x. Green Arrow Red ·x, .._.. Arrw

I® © © © 1 z 4 '® © © © I 2 3 4

Sign 3 © © ® @ Stgn J

© © ® @ Red Beuon . Sl911 13 Red Be1con· Sign 13

RICI Beacon Rlld S.acan

@ @ @ @ 1 2 l 4 f) @ @ @ 1 2 3 4

® 0 e © e © e ® ® c e © f2I ® e ® Sign 4 ® e © e Stgn 4 ® 0 © e

Rad Md Green Be~cons Sign 14 Red Ind Green Beacons Sign 14

Red and Green 8e1con1 Aid ind Gl"ftn Beacons

I ILOCKEO BLOCKED I BLOCKED BLOCKED

I ILOCKED BLOCKED I BLOCKED BLOCKED

s19n 5 Stgn 5 Sign 15 Sign 15

I CLOSED CLOSED I CLOSED CLOSED

I CLOSED CLOSED.I

CLOSED CLOSED St911 6 Sign 6

Sign 16 Sign 16

BLOCKED BLOCKED BLOCKED BLOCKED OPEN OPEN BLOCKEO BLOCKED OPEN OPEN BLOCKED BLOCKED

Stgn 7 OPEN OPEN Stgn 7 OPEN OPEN

Sign 17 Sign 17

CLOSED CLOSED 2 l CLOSED CLOSED

OPEN OPEN CLOSED CLOSED OPEN OPEN CLOSED CLOSED OPEN OPEN OPEN OPEN

Stgn 8 Stgn 8 Stgn 18 Stgn 18

x x x x x x x

St9n 9 Sign 9 Stgn 19 Sign 19

• x x • • • .. + + x + x x 51'1'1 10

Stqn 20 St9" 10

Stan 20

LE" LANE BLOCKED RIGHT LANES BLOCKED LEFT LANES BLOCKED Em"

LE" CENTER LAME BLOCKED

Slqn 21 Sign 22 Slqn 23

LE" LAM ILOCXlD Rllllfl LAIUS llOCdD LEFT UllES IUltl£D A .. ro91 -tlOll Tl• (SK.) LE" CPTER LANE IL0Cl£0

Sign 21 Stt11 22 St90 23

187

FIGURE E-6 ERRORS AND REACTION TIMES ASSOCIATED WITH CANDIDATE LANE

BLOCKAGE (CLOSURE) SIGN DESIGNS - FAMILIAR DRIVERS

['"'" A•Nfl -ti• Tl• (Sec.)·

0 0 2.8 3.2 [!] ~ ~ III [!] ~ Fa III z 3

Sign I f}J III ~ III Sign I

f}J II] ~ II] Aid l Sign II Aid l Sign II

led l .... l

1 2 2.8 3.z I [t] [1J [1J [t] 1 z 3 • I lil [!] [1J liJ I I 2 J • Slllfl 2

III III [ii [ii Sign l

III III [ii [!] Red I, 61"ftft Arrow Sign lZ led x. "-A.-- Sign 12

Red I, &~ Arrow Red 11 Green Arrow

2 0 3. 1 3.2

1~ ® © © 2 3 • I@ @ © © I I 2 3 • Sip 3 © © ® ~ Sign 3 © © ® @

Red h1con Sip 13 .., ... _ Sign 13

Rid Beacon led ... , ..

1 3 3.4 4.4 e ® ® • 1 2 3 • l1 ®

® • I 2 3 • ® e • © e © fl ® • © • ® fl ®

© • © • ® e © • _@. ____ ~

Sign t Sign t Aid Ind G,..tn lt1con1 Sign It .... 1114 , .... h1C•• Sign It

llodlfld 8Nlft IHCOOI llodlftd G<Hnlucoo1

3 3. 1 2.8 I ILOCKEO llLOCl!D I I llL~KED 2 J

IL;UDI 111.0CKED kOClED I lllL~D 2 3

IL;lED I Sign 5 St'" 5

Sign 15 Sign 15

2 8 2.9 4.3 I Cl.OSID CLOSED I •

I

I Cl.OSED CLOSED I • I Cl.OSED CLOSED CLOSED CLOSED ,

Sign 6 Sign I Sign II Sip II

3 2.8

: OPEN OPEN I kOCl!D ILOCUD I

11.0Cl[D ILOCKID OPEii OPEii ILOCUD I

ILOCIED ILDClED Sign 7 °'"' OPEii Sign 7 OPEii OPEN

Sign 17 Sign 17

2 2.9 3.5 I Cl.DSED CLOSED 2 l a.mEo CLOSED J

OPEN OPEN q.osED Cl.OSID OPEi OPEN CLOSED Cl.OSED

OPEN OPEii OPEii OPEN Sign I

Sign 18 Sip I

Sign 18

0 0 2.8 3,9 x x x x • I x x x x

Sign I St'" I Sign II Sign 19

3.6 3.8

• x • • x x • I I

• + x x + + x Sign ID

Sign 20 Sign 10

Sl911 20

LI" LAii! BLOCKED RIGHT LAlllS aocuo LITT LANES ILOCUD !l'T'll"

LE" CEITEI I.Ml 11.0CUD

Sip ZI . Sign ZZ Sign U

LI" LAlll 11.DCUD 11811J~k- LIPT LAllEI 11.DCU:D ....... -tloo Tl• (SK.) LE" CEITEA I.All[ 11.0CUD

Sign ZI 11gn n Sign IJ

188

..... co l.O

Source

Signs Subjects Error

TABLE E-11 ANALYSIS OF VARIANCE FOR REACTION TIMES ASSOCIATED

WITH CANDIDATE LANE BLOCKAGE (CLOSURE) SIGNS -FAMILIAR DRIVERS

d. f. SS MS

22 876.7 39.85 85 4130.2 48.59

1866 13263.3 7.11

** Significant at .01 level

F

5.61**

...... c..o 0

Sign Number

Average Reaction Time

l 9 2 15 7

2.8

TABLE E-12 TUKEY ANALYSIS OF REACTION TIMES ASSOCIATED

WITH CANDIDATE LANE BLOCKAGE (CLOSURE) SIGNS -FAMILIAR DRIVERS

6 3 11 4 18 10 12 20 19 16 8 5 13 23 17

2.9 3. l 3.2 3.4 3.5 3.6 3.7 3.8 3.9 4.3

14 22 21

4.4 4.9 5.0

Sign 14 containing illuminated beacons with lane numbers, and Signs

21 and 22 containing verbal descriptions of the lane blockage had signifi­

cantly higher reaction times than 15 of the other sign designs.

The sign designs were again placed into 6 groups of similar design

features shown in Figure E-7. The average number of errors ranged between

0.5 for Group E signs containing the X and arrow displays, to 6.7 for Group

F signs containing verbal descriptions for the lane blockages. An Analysis

of Variance (Table E-13) revealed that there were significant errors between

sign design groups. A Tukey Test (Table E-14) resulted in the following

differences at the .05 level:

Sign Groups

A, B, D, E <

Sign Groups

F

Although the Tukey Test showed differences in errors between the above Sign

Groups, an Analysis of Variance indicated that no differences in average

reaction time existed between the Groups (Table E-15).

Discussion

This study actually dealt with reading speed and effectiveness in lane

association given that the subject already understood the meaning and given

the messages were clearly visible and discernible. The long verbal messages

apparently contributed to some confusion. The anchored, coded symbols resulted

in few if any errors given the code in advance.

191

FIGURE E-7 ERRORS AND REACTION TIMES OF GROUPED SIGN DESIGNS -

FAMILIAR DRIVERS [,.,..n Awen91 l11ctt0fl T1• (Sec.) ·

Al (!] IAI rn ~ ~ ill I I 1 z j • I m m m I I 1 l l ' I Frid m ~ m Frid m ~ m St9111 St911 l Red l st .. 11 ..... Stgo 11

0.8 .... l 3.13 llod I

I lil [!] [!] lil I I 1 2 , • I I lil m [!] Ii] I I 1 2 l • I lil Ii] [!] [!] lil lil [!] [!]

St911 2 Stt111 Z Red I, &,....., Arrow st.., 12 llld I, CNen Ar'l'Olll st.., 12

lledl,GrwnArrw Red I, Green Arrow

B

i~ [~ © © © I I 1 I J • I © © 0 I I·©

2 l • I © © ® @ © ® e Stgo l stvn l lledlHcan st.., u •Id IHcon St911 13

1.5 .......... 3.53 .... ......

l • @ @ e I l

1 2 l • l l1 @ @ • I l 1 z

l • J ® • e ® • ® • ® • • © • ®

~---~--St911 C © fl> © • st..,• © 0 RH and Gr'ffft laacont st .. ,. llH IOd G ..... ltlCOlll St91114

.. d lftd GNH IHCOM ltd and G,..n lllCOftl

c 111.0CllD 111.~l[D a;ual

c 11.0CUD I

IL;l[D I ILOClED I z l 111.llCllD IBL~ z 3

St911 I Stvn S Stt111 11 st .. 15

3.5 3.28

I CLOSED CLDSID I I 1 2 J • I I Cl.DUD CLOSED I

I

1 z J ,. I CLOSED CLDSID CLOSED CLD5ED

Stt111 6 Stvn 6 St'll' 16 St'll' 16

D D 111.0CKID BLOCKED I I I z J • I I llOCUD BLOCKED I I 1 2

3 • I DPIN Of'IM I LOCKED ILDCKED DPU DnM ILDCllD BLDCUD

Stvn 7 a.u DPP st.., 1 0.11 DP£ll

1.8 Stvn 17 3.23 ""' 17

I Cl.DSID CLmED I I~ z J • I I a.mu CLDSG I I 1 2 , • I Oflltl DPIN CLOHD Cl.DUD DPIN °'"

Cl.DSID CLOSED OPlll DPEll DPD

St"' B St911 I Stl'I 11 Stvn 18

E

I El I I x jJ I 1 2 J • x x I

I

1 2 l • x x x x

Stvn 9 st'" t Stt11119 st., 11

0.5 3.53

I • x • I I 1 I J • I I • x x • I I 1 2 l • I x + + + x x + x x st 111 10

stvn za ""' 10 St911 ZD

f

16.7 -·-·· -·-· I LIFT L.1111 ILotllD I I lltlltT LMIS aocllll I I UFT LAlllS kDCUD E .......

LIFT CUTER I.All£ ILOClliD

St90 21 . st,. n st"' u

F 14. 43 •-• -tt• Tl• (Soc.I I LIFT LMI 11.0CUO I I llfll!: !oM1S kOCIU l I LIFT LAlllS kDCUO

LIFT CINTll LAlll ILOCUD

lt11111 11111 n ""'a

192

TABLE E-13 ANALYSIS OF VARIANCE OF ERRORS FOR GROUPED SIGN DESIGNS -

FAMILIAR DRIVERS

Source d.f. SS MS

Groups 5 89.3 17.85 Error 17 45.2 2.66

** Significant at . 01 level

TABLE E-14 TUKEY ANALYSIS OF ERRORS FOR GROUPED SIGN DESIGNS -

FAMILIAR DRIVERS

Sign Group E A B D c Average Errors

Source

Groups Error

0.5 0.8 l. 5 1.8 3.5

TABLE E-15 ANALYSIS OF VARIANCE OF REACTION TIMES FOR

GROUPED SIGN DESIGNS -FAMILIAR DRIVERS

d.f. SS MS

5 3.7 0.73 17 6.0 0.35

193

F

6. 72**

F

6.7

F

2.07

Study 3 - Verbal and Coding Methods - Follow-up Study

Objective

This study was a follow-up to the preceding two studies. The best sign

design features based on driver reaction times, correct response, and prefer-

ences from Studies 1 and 2 were incorporated into 11 candidate sign designs

shown in Figure E-8 for further study.

Method

Groups of subjects were shown only one candidate sign and were asked to

write the meaning of the sign in an "open-ended" response. All signs were

white on green with the exceptions noted. v

Although the experiment was conducted in St. Paul and Los Angeles, it was

considered to be an extension of the Mediamaster laboratory experiments. It

was not the intent to determine regional differences.

A total of 538 subjects participated in the experiment. The number of

subjects responding to each of the 11 candidate sign designs ranged between

37 and 55.

The independent variable was the sign design. The dependent variable was

the frequency of correct and incorrect responses.

· Results

The results of the experiment are shown in Table E-16. Since the intent

was to determine driver interpretation of the signs, responses identifying the

correct lanes and a choice of Zanes blocked, Zanes closed or Zanes congested

were considered as possible correct answers, although it could be argued

whether Zanes congested can be considered a correct response.

194

FIGURE E-8

CANDIDATE LANE BLOCKAGE (CLOSURE) SIGNS USED IN FOLLOW-UP STUDY - UNFAMILIAR DRIVER

BLOCKED BLOCKED OPEN OPEN BLOCKED OPEN OPEN· BLOCKED

Sign l Sign 2

~ x x ~ LANE CONDITION

Sign 3 Sign 4 Sign 5 Red X's, Green Arrows Red X's, Green Arrows

LANE CONDITION LANES BLOCKED LANE CONDITION 1 2 3 4

x x ~ + x x ~ ~ x x ~ ~ Sign 6 Sign 7 Sign 8

LANES BLOCKED LANES BLOCKED LANES BLOCKED 1 2 3 4 1 2 3 4 1 2 3 4

x x x x e e Sign 9 Sign l 0 Sign 11

Red X's Red Beacons

Note: All signs are white on green with the exceptions a·s noted.

195

TABLE E-16 SUMMARY OF RESPONSES TO PRIMARY LANE BLOCKAGE (CLOSURE) SIGNS

Number of Correct Resgonses (1) (2) (3) Total

Lanes Lanes Lanes Correct Total Percent Percent Sign Blocked Closed Congested Responses Incorrect Correct Incorrect

Number {l }+{2}+(3} Reseonses Reseonses Reseonses

31 5 1 37 3 93 7

2 29 3 1 33 13 72 28

3 12 9 5 26 20 57 43

4 12 10 4 26 20 57 43

5 9 22 4 35 2 95 5

6 12 23 36 9 80 20

7 31 5 2 38 1 97 3

8 11 20 7 38 l 97 ·3

9 30 7 0 37 1 97 3

10 39 9 2 50 2 96 4

11 31 15 2 48 3 94 6

196

i, I

Signs without titles, using the word descriptors ,:;1,, 11 ·1\F/ 1 and , •1·1,:fi"

displayed on two lines but relative to the specific lanes affected (Sign

1) were understood by a large majority of the drivers (93 percent). When

the same messages were placed on one line (Sign 2), there was a significant

reduction in driver understanding. Sign 2 was interpreted correctly by only

72 percent of the subjects in comparison to 93 percent for Sign 1.

BLOCKED BLOCKED BLOCKED OPEN OPEN BLOCKED

OPEN OPEN

Sign l (93%) Sign 2 (72%)

The side mounted signs containing X's and arrows without titles were

understood by only 57 percent of the subjects regardiess of whether red X's

and green arrows (Sign 3) or white on green X's and arrows (Sign 4) were used.

[I] W W [I] I .._I _+ _x _x _+ ___ Sign 3 (57%) Sign 4 (57%)

Red X's, Green Arrows

Adding an appropriate title of LANE CONDITION or LANES BLOCKED to the

X and arrow signs significantly increased the number of correct responses.

Sign 5 displaying the title LANE CONDITION with red X's and green arrows was

understood by 95 percent of the subjects. The same title used in conjunction

with white on green X's and arrows (Sign 6) was interpreted correctly by only

80 percent of the respondents. The use of the title LANES BLOCKED with white

on green X's and arrows (Sign 7) resulted in a 97 percent correct response.

197

LANE CONDITION LANE CONDITION LANES BLOCKED

x x t t x x +· + Sign 5 (95%) Sign 6 (80%) Sign 7 (97%)

Red X's, Green Arrows

There was a slight increase in correct response for the LANE CONDITION

signs using white on green arrows when lane numbers were added. Sign 8 re­

sulted in 97 percent correct response in comparison to 80 percent for Sign 6.

The addition of the lane numbers did not significantly increase the correct

responses in comparison to the red X and green arrow design (Sign 5).

LANE CONDITION

l 2 3 4

x x + + Sign 8 (97%)

There was no difference in response between the sign using X's and

arrows with lane numbers (Sign 8) and the signs without arrows (Signs 9

and 10).

1

x

LANES BLOCKED

2 3

x Sign 9 (97%)

Red X 1 s

4

198

LANES BLOCKED

1 2 3 4

x x Sign 10 (96%)

There was only a slight reduction in correct response when the X's

shown in Sign 10 were replaced with red beacons to indicate which lanes

are blocked (Sign 11). Ninety-four subjects correctly interpreted Sign 11.

LANES BLOCKED

l 2 3 4

•• Sign 11 (94%)

Red Beacons

Signs with the title LANES BLOCKED (Signs 7, 9, 10, and 11) were described

as having lanes blocked by a higher percentage of the respondents than lanes

closed or congested. However, there was a tendency by the respondents to

describe the lane status as lanes closed rather than lanes blocked or congested

for Signs 5, 6, and 8.

Discussion

Eleven candidate designs for side mounted lane blockage (closure) and

lane availability signs were studied in the last of the preceding three

experiments. These designs emanated from the results of the first two

experiments.

A sign design using anchored word descriptors for each lane such as

BLOCKED and OPEN was shown to be understood by a very high percentage of

the subjects providing that the BLOCKED and OPEN messages are placed on

199

separate lines as shown below.

BLOCKED BLOCKED OPEN OPEN

There is a rapid deterioration in driver understanding of the message when

the words are placed on the same line. The latter design, therefore, is not

recommended. Based upon results of the first two experiments, it is also im­

portant that a word descriptor be assigned to each lane. Another advantage

is that if one knows the blocked lanes are always on the top line, the driver

need not have to read the word before reacting. Hence, offsetting enhances

the legibility distance and effective lane changing time.

The anchored word descriptor sign shown above can easily be implemented

using common type changeable message signs such as matrix or rotating drums.

The major disadvantage is the length requirement for this type of sign. For

example, using a 15 inch Series D letter would require the rotating drum to

be approximately 30 feet in length.

Lane blockage (closure) signs using X's and arrows were also shown

to be effective provided that they contained an appropriate title and

color combination. The use of the title LANES BLOCKED tended to result

in correct interpretations of lane blocked rather than lane closed or

lane congested. Whereas, the title LANE CONDITION with X's and arrows

tended to be interpreted as lane closures. X and arrow signs with a

LANES BLOCKED title were shown to be effective from the standpoint of

correct interpretation regardless of whether white on green X's and

arrows or red X's and green arrows were used. The use of red X's and

200

green arrows with the LANE CONDITION title was shown to be very effective.

However, for some unexplainable reason, white on green X's and arrows,

(resembling a static sign) with the LANF t(JNOTTTON title resulted in un­

expectably high incorrect responses. Adding lane numbers to the white

on green X and arrow signs resulted. in a very high percentage of correct

responses.

Adding lane numbers to the X and arrow signs with the LANES BLOCKED

title did not sigriificantly improve the percentage of correct interpretations.

Unknown at this point was whether drivers ascribe different meanings

to blocked versus closed messages.

201

Study 4 - Driver Interpretation of 11 Blocked" versus "Closed" Messages

Objective

The open-ended responses to Study 3 in which drivers interpreted the lane

control signs as indicating either blocked lanes or closed lanes, prompted

this new experiment to determine the meanings .drivers ascribe to these two

words.

Method

There were two phases to this study. Phase 1 was concerned with lane

blockage (closure) and Phase 2 addressed freeway blockage (closure). Each

group of subjects responded to only one of the two phases. Two signs were

presented on the answer sheet. In Phase 1, one sign read LEFT LANE BLOCKED,

the second LEFT LANE CLOSED. For Phase 2, the signs were FREEilAY BLOC..l(ED

AHEAD and FREEWAY CLOSED AHEAD. In each Phase, the subjects were asked

whether the signs meant the same thing. If not, they were requested to write

the reason why they differ. They were also asked whether their response

would be the same or different if they saw the signs. v

This study was conducted in Los Angeles and was considered to be an

extension of the Me~iamaster laboratory studies, and was not regarded as a

regional study per se. A total of 43 drivers responsed to Phase 1 and 76

drivers to Phase 2.

The independent variable was the sign messages. The dependent variable ...

was the frequency of response type.

202

Resu1ts

The resu1ts of the study are presented in Tables E-17 and E-18.

Specific results are as follows:

1. Twenty-six (60 percent) of the 43 respondents to Phase 1 believed

that LANE BLOCKED meant the same as LANE CLOSED. Seventeen (40

percent) ascribed different meanings to the messages.

2. Of the 17 subjects that believed the messages were different, 100

percent stated that LANE BLOCKED indicated a temporary blockage

due to an accident, stall, etc., and LANE CLOSED indicated a physi­

cal closure of prolonged duration.

3. Thirty-two (74 percent) of the 43 subjects indicated that their

response upon seeing the lane blocked and closed signs would be

the same, 5 (12 percent) stated their response would be different,

and 6 (14 percent) did not respond.

4. Sixty (79 percent) of the 76 subjects responding to Phase 2 stated

that the meaning of FREEWAY BLOCKED AHEAD was different than

FREEWAY CLOSED AHEAD. Sixteen (21 percent) believed the messages

to be the same.

5. Of the 60 subjects that believed the messages were different, 58

(97 percent) stated that FREEWAY BLOCKED indicated a temporary

obstruction of the freeway, whereas FREEWAY CLOSED was a prolonged

closure of the freeway.

6. Fifty-four percent of all the subjects indicated that their res­

ponse upon seeing the freeway blocked and closed signs would be

the same, 43 percent stated their response would be different,

and 3 percent did not respond.

203

N 0 ..p.

TABLE E-17 DRIVER RESPONSE TO LANE BLOCKED AND LANE CLOSED MESSAGES (Phase 1)

LEFT LANE BLOCKED LEFT LANE CLOSED l Number Percentage

• Do the signs mean the same thing?

• Would your response be the same or different?

Number of Percent of Subjects Subjects

Same 32 74 Different 5 12 No Response _6 14

Total 43 100

1 Of the 17 subjects stating the messages had different meanings, 17 (100 percent) stated that LANE BLOCKED indicated a temporary blockage due to an accident, stall, etc., and LANE CLOSED indicated a physical closure of prolonged duration.

N a <.n

TABLE E-18 DRIVER RESPONSE TO FREEWAY BLOCKED AND FREEWAY CLOSED MESSAGES (Phase 2)

FREEWAY BLOCKED AHEAD FREEWAY CLOSED AHEAD

Number ·Percentage

• Do the signs mean the same thing?

• Would your response be the same or different?

Number of Percent of Subjects Subjects

Same 41 54

Different 33 43 No Response 2 3

Total 76 100

• Of the 60 subjects that stated the messages had different meanings, 58 (97 percent) indicated that FREEWAY BLOCKED was a temporary obstruction, whereas FRF:EWAY CLOSED was a prolonged closure of the freeway.

Discussion

Somewhat suprisingly, 60 percent of the drivers polled believed that

LANE BLOCKED meant the same as LANE CLOSED. The remaining 40 percent

stated that LANE BLOCKED meant a temporary obstruction due to an accident,

stall, etc., and LANE CLOSED indicated a physical closure of prolonged

duration. -The results indicate, however, that LANE BLOCKED should be

used for temporary obstructions, and LANE CLOSED for physical closures.

Although 79 percent of the drivers polled ascribed different meanings

to the FREEWAY BWCKED AHEAD and FREEWAY CLOSED AHEAD messages' 54 percent

indicated that their response to the messages would be the same. Since the

FREEWAY CLOSED AHEAD message implies total closure, the expected response of

the driver would be to leave the freewa·y. Since the FREEWAY BLOCKED AHEAD

would tend to result in similar driver actions and possibly erratic maneuvers, '

this message should not be used when one or more lanes are open to traffic.

Instead, the LANE BLOCKED message is recommended.

206

Design Recommendations

l. The displays on side mounted lane blockage (closure) signs should

be completely anchored with respect to the lanes.

2. Untitled word message displays containing the messages OPEN BLOCKED

(CLOSED) appropriately anchored with respect to each lane can be used

for side mounted signs. The OPEN and BLOCKED legends should be dis­

played on separate lines. Examples of the designs are illustrated

below for a four-lane section of freeway:

BLOCKED BLOCKED OPEN OPEN

'

l 2 3 4

BLOCKED BLOCKED OPEN OPEN

3. Untitled X and arrow coded displays appropriately anchored with

respect to each lane should not be used for side mounted signs.

These sign designs must be titled. The preferred title is LANES

BLOCKED (or closed if appropriate). An example of a good display

is shown below:

LANES BLOCKED

x x t + This type of design is shorter in length than the word signs in

(2) above. 207

4. The X and arrow coded sign can either be white on green or color

coded red X's and green arrows for rotating drum, blankout, or

similar displays, or can be white on black in the case of matrix

signs. The choice would be dictated by whichever results in

the greatest target value, or by the available hardware.

5. The use of lane numbers on the recommended word or coded signs

are not necessary, but can be used if desired.

6. Titled coded signs without arrows containing X's to indicate lane

blockages can be used provided the lanes are anchored by numbers.

An example is illustrated below.

LANES BLOCKED 1 2 3 4

x x

7. Titled coded signs using illuminated beacons to indicate lane

blockage can be used provided the lanes are anchored by numbers.

An example is as follows:

LANES BLOCKED 1 2 3 4

•• 8. The message FREEWAY BLOCKED AHEAD should not be used to indicate

individual lane blockages. It should only be used when the free­

way is completely blocked.

9. The message RIGHT (LEFT) LANE BLOCKED can be used when there is

a temporary obstruction on the right or left lane. This message

208

may be used only when the freeway section is two or three lanes

in one direction. If the freeway section is 4 or more lanes,

use one of the above coding techniques.

10. The message RIGHT (LEFT) LANE CLOSED can be used when the

right or left lane will be obstructed for a prolonged period

such as for maintenance or construction.

11. When only one choic~ of message is available due to limitations

of the sign design' that is RIGHT (LEFT) LANE BLOCKED or RIGHT .

(LEFT) LANE CLOSED, either message may be displayed to indicate

a temporary or prolonged lane obstruction.

209

REFERENCES

1. Dudek, C. L. Human Factors Requirements For Real-Time Motorist Informa­tion Displays, Vol. 2 - State-of-the-Art: Messages and Displays in Freeway Corridors. Texas Transportation Institute, Report Number FHWA-RD-78-6, February 1978.

2. Manual On Uniform Traffic Control Devices For Streets And Highways. U. S. Department of Transportation, Federal Highway Administration, 1971.

3. Forbes, T. W., Gervais, E. R., and Allen, T. Effectiveness of Symbols for Lane Control Signals. Highway Research Board Bulletin 244, 1963.

210

IX. TOPIC AREA F - INCIDENT TYPES

Objectives

To deitermine the best tenninology for classes of problems that may affect

the driver's negotiation of the road ahead. The classes of incidents, how

they should be expressed, and whether they need be expressed at all are sub­

jects of study in Topic.Area F.

Background

There are a multitude of off-nominal or unexpected events that can ad­

versely affect operation of a freeway. From the driver's point of view, the

flow of traffic is not what it ought to be. The speed slows, cars begin to

weave erratically into lanes that momentarily seem to be moving better, brake

lights start coming on, and the phenomenon ca 11 ed "conges tion11 onsets. Some­

thing is "wrong" ahead. The system has had a breakdown or (at least) is not

working at a nominal (designed for) level of operation.

Early in this research program a catalogue of incidents which could affect

operation on a freeway was developed. This catalog is given in Table F~l. Again,

the issue was, how many of these incidents, and to what extent does the traffic

engineer need to sign for these events or conditions if he has.· some sort of

changeable message sign facility at his disposal. If he is planning a CMS in­

stallation, the more incidents that he must handle; the more flexible and hence

costly his facility must be. The real question becomes, "what is the minimum

number of classes of incidents that need to be displayed, and what shall we dis­

play for each of these incidents?" If all incidents could be conveyed by a sign

with a beacon that says ''trouble ahead" so much the better. It is also possible

that the incident can be implied by the consequences which are then displayed

211

TABLE F-1 CATALOGUE OF INCIDENTS

(FINAL SELECTION UNDERLINED)

Physically Blocks l or More Lanes

STALLED VEHICLE BREAKDOWN FLAT TIRE VEHICLE STOPPED MECHANICAL BREAKDOWN ACCIDENT TRUCK WRECKED TRUCK OVERTURNED TRUCK JACK-KNIFED CONSTRUCTION MAINTENANCE ROADWORK AMBULANCE EMtRGENCY VEHICLES LOAD SPILLED BUMP IN PAVEMENT PAVEMENT BROKEN WATER ON PAVEMENT FLOODED LANE SNOW COVERED ANIMALS ON PAVEMENT DEAD ANIMAL TRAFFIC ~ACKED UP EXIT JAMMED BRIDGE OUT LANE CLOSEQ. TWO LANES CLOSED FREEWAY CLOSED TRASH TUNNEL JAMMED TUNNEL OUT

Does Not Block Lane but Creates Slowdowns & Stoppages

ACCIDENT J EMERGENCY VEHICLES ON SHOULDER OTHER VEHICLES AT SIDE OF ROAD ACCIDENT IN OPPOSING DIRECTION ACCIDENT ON OPPOSITE SIDE OF ROADS CONGESTION CROWDED FREEWAY HEAVY TRAFF! C ANIMALS ON PAVEMENT SLOW MOVING VEHICLE PARADl_ FUNERAL CONVOY_ SMOKE ICE SNOW WATER FOG TRUCKS WITH HEAVY LOADS TRUCKS WITH WIDE LOADS PEDESTRIANS BICYCLES

212

to the motorist in terms of congestion level plus re-routing or other opera­

tional col11llands:

CONGESTION AHEAD

SLOW TO 25 MPH

and perhaps location/duration information.

Of the many incidents that could conceivably be displayed on a freeway

to prepare motorists for conditions ahead, the ones underlined in Table F-1

were selected by staff members as being inclusive without undue redundancy.

Basically they fall into 19 distinct classes as we see them. These classes,

and the words for each, are ~iven in Table F-2.

There is considerable evidence from Topic Area A and the audio studies that

drivers are not satisfied simply to know that there is congestion or delay

ahead. These are effects, but what he wants to know is the incident or problem

which brought about the effects. This information may then be used as a basis

for deciding whether or not to divert, slow down, or other contingency actions.

Obviously, every possible incident--even if known--could not be dis­

played on the CMS. Therefore, it would be necessary to reduce the total

vocabulary of incident messages.

Two criteria for inclusion of an incident were advanced:

1. The incident should be important enough to affect his driving

behavior and should be information which he felt he really wanted

to know.

2. The incident should describe unique situations not already expressed

in other incident messages. For example, a general classification

of 11 slow moving vehicles" could encompass a variety of specific

instances such as parades, funerals, convoys, etc. Should the gen-

213

TABLE F-2 CATEGORIES AND FINAL INCIDENT VOCABULARY

Category Title

1. Undamaged Vehicle Impeding Traffic

2. Damaged Vehicle Impeding Traffic

3. Lane or Road Closed

4. Objects on Road Impeding Traffic

5. Maintenance and Construction 6. Pavement Discontinuity

7. Friction Less Than Expected 8. Big Splash Ahead

9. Snow on Road

10. Reduced Visibility

11. Slow/Unpredictable Moving Obstacles on Road

12. Crowded Roadway

13. · Tunnel/Bridge Unusable

14. Exit Temporarily Unusable 15. Unusual Looking Vehicles at

Side of Road or Across Roadway 16. Line of Vehicles Traveling

Together

214

Words

VEHICLE STOPPED BREAKDOWN ACCIDENT TRUCK OVERTURNED TRUCK WRECKED LANE CLOSED TWO LANES CLOSED FREEWAY CLOSED LOAD SPILLED TRASH DEAD ANIMAL ROADWORK PAVEMENT BROKEN BUMP IN PAVEMENT ICE WATER ON PAVEMENT FLOODED SNOW LANE SNOW COVERED REDUCED VISIBILITY FOG SLOW MOVING VEHICLE ANIMALS ON PAVEMENT BICYCLES PEDESTRIANS HEAVY TRAFFIC CROWDED FREEWAY CONGESTION TRAFFIC BACKED UP BRIDGE OUT TUNNEL OUT TUNNEL JAMMED EXIT JAMMED VEHICLES AT SIDE OF ROAD ACCIDENT ON OPPOSITE SIDE PARADE FUNERAL CONVOY

OF ROAD

eral category not be presented rather than the specific instances?

Doing so would reduce the total vocabulary of incident messages

considerably.

The second study, reported in this Topic Area, investigated the question

of whether or not the incident was important enough to merit display. Other

studies have also provided evidence on the importance of certain incidents

such as the "accident".

The first study was directed more at reducing the number of incidents

displayed by looking for sets of incident words which could be adequately

described by a conman expression.

215

Study l - Categorization of Verbal Messages

Objectives

This study's objectives were to establish (a) the manner in which drivers

group together conceptually different kinds of incidents that could be dis­

played on a CMS, (b) the minimum number of categories of inc1dents they grouped

them into, (c) the names they chose for the categories of incidents. This in­

formation would provide a basis for CMS flexibility (how many different states

the CMS might have to present) and the better vocabulary of incident titles.

Method

The approach was an adaptation of the basic 11 Q Sort" technique first deve­

loped in 1953 by Stephenson.* In this experiment subjects were instructed to

imagine themselves on a six-lane freeway and approaching a CMS. They were

further told that each of the 39 messages could appear on the CMS. The subjects

were to imagine how the condition on each card might affect their trip. Then

they were instructed to sort the 39 cards into as many card piles as they felt

were needed, but no more than were needed. The instructions were purposely

kept as open-ended as possible. Finally, subjects were requested to "Name each

of these piles of signs. How would you express what is common about each pile?"

Thus subjects were encouraged to set up ad hoc categories - however named

or even non-verbalized - and then find a title for each category. The hope was

that using these category names would be a more efficient and succinct method of

expressing incidents than storing and displaying every conceivable incident which

could occur.

*Stephenson, W. The Study of Behavior, Chicago: University of Chicago Press, 1953.

216

.._.../

Sixty-one subjects were used in this College Station Laboratory study.

An additional thirty-six subjects were also run in Houston area studies, for

a total of 97 subjects. In the results to be reported below, the College

Station and Houston results will be segregated to establish if there were dif­

ferences in the numbers and types of categories used by small city dwellers

and large city dwellers.

Results

The mean number of categories used by subjects in College Station was 6.5.

Subjects in Houston used slightly fewer categories, 6.0. The results break

down as follows:

N College Station 61

Houston 36

Mean 6.5

6.0

Mdn 6

6

S.D. Mode 2.91 4 2.27 6

These findings are remarkably consistent. Now the experimental question was

what categories do the subjects, and by inference the population, sort these

incidents int6?

The instructions gave little guidance as to how to categorize these events

other than to ''imagine how these conditions might affect your trip''. The re­

sponses were highly variable (See Supplement). The investigators decided that the

best titles for the categories selected by the subjects were as follows:

1. Traffic Conditions

2. Warnings or Advisories

3. Detour

4. Slow (because of possible hazard)

5. Weather Conditions

6. Miscellaneous

217

These can be reduced to four without much trouble:

1, Conditions - all types J 11 Information 11

2. Warnings

J 3. Detour - change route

4. Slow

11 Advisories 11 or 11 Commands 11

The incidents seem to either tell about conditions or to trigger a self­

command, a note as it were, for the subjects to take some action. They use

more than 4 categories, but they are somewhat redundant semantically.

The frequencies and percentages of association of incidents with cate-

gories named with some variant of 11 Conditions 11,

11Warnings 11,

11 Detour 11, or

11 Sl ow 11 are tabul ari zed as in Table F-3. The reader can see that College

Station and Houston data are not far apart, and that the majority of subjects

in both locales cluster around 11 Conditions 11 and 11 Warnings 11• Table F-4 illus­

trates this point. The data in Table F-3 were converted to ranks across

categories, but within cities. Thus, the first message, BREAKDOWN, had the

highest association with 11 Warni ng 11 in both cities, while 11 Detour 11 had the

lowest association, as shown by the rank of 4 for both cities. Table F-5

reveals that only 11 Conditions 11 and 11 Warnings 11 are categories of practical

significance. Those incidents not on this list:

VEHICLE STOPPED ICE FLOODED WATER ON PAVEMENT SNOW LANE SNOW COVERED FREEWAY SNOW COVERED FOG

REDUCED VISIBILITY

218

TABLE F-3 FREQUENCIES OF ASSOCIATION OF INCIDENTS WITH CATEGORIES

(PERCENT)

Messages Conditions Warnings Detour Slow

College College College College Station Houston Station Houston Station Houston Station Houston

1. BREAKDOWN 15 (25) 16 (44) 28 (46) 18 ( 50) 2 (3) 2 (6) 10 (16) l ( 3)

2. VEHICLE STOPPED 12 (20) 17 (47) 30 (49) 15 ( 42) l (2) 2 (6) 12 (20) 2 (6)

3. ACCIDENT 15 ( 25) 6 (17) 33 ( 54) 25 (69) 2 (3) 3 (8) 9 (15) l (3)

4. TRUCK OVERTURNED 14 (23) 8 (22) 32 ( 52) 22 (61) 4 ( 7) 2 (6) 9 (15) l (3)

5. LOAD SPILLED 14 ( 23) 11 ( 31) 32 ( 52) 20 (56) 2 (3) 2 (6) 7 (11) 3 (6)

6. TRUCK WRECKED 14 (23) 6 ( 17) 32 ( 52) 25 (li9) 3 (5) 3 (8) 9 ( 15) l ( 3)

7. LANE CLOSED 19 ( 31 ) 21 ( 58) 20 (33) 7 (19) 8 ( 13) 4 (11) 10 (16) 3 (8)

8. TWO LANES CLOSED 18 (30) 22 (61) 18 ( 30) 8 (22) 11 (18) 4 (11) 10 (16) 2 (6)

9. FREEWAY CLOSED 12 (20) 22 ( 61) 12 (20) 8 (22) 29 (48) 5 ( 14) 1 (2) l ( 3)

10. TRASH 11 (18) 14 ( 38) 31 (51) 18 ( 50) 0 (0) 1 (3) 10 (16) 3 (8)

11. DEAD ANIMAL 12 (20) 15 (42) 33 (54) 15 (42) 0 (0) l (3) 10 (16) 4 { 11)

12. ROADWORK 16 (26) 21 (58) 26 (43) 11 ( 31) 2 (3) l { 3) 12 (20) 3 (8)

13. PAVEMENT BROKEN 14 (23) 19 { 53) 29 (48) 12 { 33) 0 (0) l ( 3) 12 (20) 3 (8)

14. BUMP IN PAVEMENT 13 { 21 ) 19 (53) 31 (51) 15 ( 42) 0 (0) 0 (0) 12 (20) 2 (6)

15. ICE 10 (16) 7 ( 19) 17 { 28) 13 ( 36) 0 (0) 1 ( 3) 5 (8) 1 (3)

16. FLOODED 10 (16) 5 ( 14) 14 (23) 13 (36) 10 (16) 2 (6) 1 (2) 1 (3)

17. WATER ON PAVEMENT 10 (16) 5 ( 14) 17 ( 28) 14 (39) 0 (0) 0 (0) 5 (8) 2 (6)

18. SNOW 10 (16) 6 { 17) 17 ( 28) 13 { 36) 0 (0) 0 (0) 4 (9) 1 (3)

19. LANE SNOW COVERED 11 (18) 10 (28) 17 ( 28) 10 (28) l (2) l (3) 5 (8) 1 ( 3)

20. FREEWAY SNOW COVERED 10 (16) 7 (19) 19 (31) 11 ( 31) 3 (5) 1 ( 3) 3. (5) 1 (3)

219

TABLE F-3 (Continued)

·--· Messages Conditions \~arnings Detour Slow

----College College College College Stilt ion Houston Station Houston Station Houston Station Houston

-

21. FOG 10 (16) 6 ( 17) 16 ( 26) 10 (27) 0 (0) 0 (0) 7 ( 11) 2 (6)

22. REDUCED VISIBILITY 10 (16) 6 ( 17) 16 (26) 9 (25) 0 (0) 0 (0) 8 (13) 2 (6)

23. SLOW MOVING VEHICLE 18 ( 30) 18 (50) 11 (18) 11 (31) l (2) l (0) 26 (43) 5 (8)

24. ANIMALS ON PAVEMENT 13 (21) 11 ( 31 ) 33 (54) 15 (42) 0 (0) . l (0) 9 ( 15) 6 (17)

25. HEAVY TRAFFIC 30 (49) 23 ( 64) 11 ( 18) 5 (14) 3 (5) 5 ( 14) 15 (25) 3 (8)

26. CROWDED FREEWAY 29 (48) 25 ( 69) 11 (18) 5 (14) 3 (5) 3 (8) 16 (26) 3 (8)

27. CONGESTION 29 (48) 23 ( 64) 8 ( 13) 6 ( 17) 3 (5) 3 (8) 18 (30) 3 (8)

28. TRAFFIC BACKED UP 31 ( 51 ) 24 (67) 11 (18) 4 (11) 3 (5) 3 (8) 14 (23) 4 ( 11)

29. BRIDGE OUT 11 (18) 21 (58) 18 ( 30) 7 ( 19) 30 (49) 5 ( 14) l (2) l (2)

30. TUNNEL OUT 11 (18) 15 (42) 13 (21) 6 (17) 25 (41) 5 (14) l (2) l (2)

31. TUNNEL JAMMED 24 (39) 18 ( 50) 14 (23) 3 (8) 10 (16) 4 (11) 10 (16) l (2)

32. EXIT JAMMED 30 (49) 23 (64) 11 (18) 4 ( 11) 11 (18) 3 (8) 7 (11) 3 (8)

33. VEHICLES AT SIDE OF ROAD 13 (21) 9 (25) 31 ( 51) 16 (44) 0 (0) 2 (6) 12 (20) 5 (14)

34. ACCIDENT ON OPPOSITE 27 (44) SIDE OF ROAD 16 (26) 9 (25) 18 ( 50) 0 (0) 2 (6) 9 (15) 4 (11)

35. PARADE 11 (18) 8 (22) 19 ( 31 ) 14 ( 39) 3 (5) 3 (8) 20 (33) 7 (19)

36. FUNERAL 12 (20) 8 (22) 18 ( 30) 16 (44) 3 (5) 2 (6) 24 (39) 7 ( 19)

37. CONVOY 14 (23) 9 (25) 16 (26) 13 ( 36) 2 (3) 2 (6) 24 (39) 8 (22)

38. PEDESTRIANS 9 (15) 8 (22) 32 (52) 18 (50) 0 (0) 1 ( 3) 13 (21) 5 (14)

39. BICYCLES 9 (15) 8 (22) 31 ( 51 ) 19 (53) 0 (0) 1 (3) 13 (21) 4 (11)

220

TABLE F-4 RANK ORDERS OF ASSOCIATION OF INCIDENTS WITH CATEGORIES

CATEGORIES

Messages Conditions Warnings Detour Slow

College College College College Station Houston Station Houston Station Houston Station Houston

1. BREAKDOWN 2 2 l 1 4 4 3 3

2. VEHICLE STOPPED 2 1 1 2 4 3.5 3 3.5

3. ACCIDENT 2 2 1 1 4 4 3 3

4. TRUCK OVERTURNED 2 2 1 1 4 4 3 3

5. LOAD SPILLED 2 2 1 1 4 3.5 3 3.5

6. TRUCK WRECKED 2 2 1 1 4 3 3 4

7. LANE CLOSED 2 1 1 2 4 3 3 4

8. TWO LANES CLOSED 1. 5 l 1.5 2 3 3 4 4

9. FREEWAY CLOSED 2.5 l 2.5 2 l 3 4 4

10. TRASH 2 2 1 1 4 4 3 3

ll. DEAD ANIMAL 2 1. 5 1 1.5 4 4 3 3

12. ROADWORK 2 1 1 2 4 4 3 3

13. PAVEMENT BROKEN 2 1 1 2 4 4 3 3

14. BUMP IN PAVEMENT 2 1 1 2 4 4 3 3

15. ICE 2 2 1 1 4 3.5 3 3.5

16. FLOODED 2.5 2 1 1 2.5 3 4 4

17. WATER ON PAVEMENT 2 2 1 1 4 4 3 3

18. SNOW 2 2 1 1 4 4 3 3

19. LANE SNOW COVERED 2 1.5 1 1.5 4 3.5 3 3.5

20. FREEWAY SNOW COVERED 2 2 1 1 3.5 3.5 3.5 3.5

221

TABLE F-4 (Continued)

--·

CATEGORIES ------Messages Conditions Warnings Detour Slow

College College College College Station Houston Station Houston Station Houston Station Houston

L

21. FOG 2 2 1 1 4 4 3 3

22. REDUCED VISIBILITY 2 2 l 1 4 4 3 3

23. SLOW MOVING VEHICLE 2 1 3 2 4 4 1 3 -24. ANIMALS ON PAVEMErn 2 2 l 1 4 4 3 3

25. HEAVY TRAFFIC 1 l 3 2.5 4 2.5 2 4

26. CROWDED FREEWAY 1 1 3 2 4 3.5 2 3.5

27. CONGESTION 1 1 3 2 4 3.5 2 3.5

28. TRAFFIC BACKED UP 1 1 3 2.5 4 4 2 2.5

29. BRIDGE OUT 3 1 2 2 1 3 4 4

30. TUNNEL OUT 3 1 2 2 l 3 4 4

31. TUNNEL JAMMED 1 1 2 3 3.5 2 3.5 4

32. EXIT JAMMED 1 1 2.5 2 2.5 3.5 ·4 3.5

33. VEHICLES AT SIDE OF ROAD 2 2 1 1 4 4 3 3

34. ACCIDENT ON OPPOSITE SIDE OF ROAD 2 2 1 1 4 4 3 3

35. PARADE 3 2 2 1 4 4 1 3 . 36. FUNERAL 3 2 2 1 4 4 1 3

37. CONVOY 3 2 2 1 4 4 1 3

38. PEDESTRIANS 3 2 l 1 4 4 2 3 . 39. BICYCLES 3 2 1 1 .4 4 2 3

222

TABLE F-5 HIGHEST ASSOCIATIONS OF INCIDENTS

WITH CATEGORIES (~ 50 PERCENT OF SUBJECTS IN COLLEGE STATION OR IN HOUSTON)

Conditions Warnings

LANE CLOSED BREAKDOWN

FREEWAY CLOSED ACCIDENT

ROADWORK TRUCK OVERTURNED

PAVEMENT BROKEN LOAD SPILLED

BUMP IN PAVEMENT TRUCK WRECKED

SLOW MOVING VEHICLE DEAD ANIMAL

HEAVY TRAFFIC BUMP IN PAVEMENT

CROWDED FREEWAY ANIMALS ON PAVEMENT

CONGESTION VEHICLES AT SIDE OF ROAD

TRAFFIC BACKED UP ACCIDENT ON OPPOSITE SIDE OF ROAD

BRIDGE OUT PEDESTRIANS

TUNNEL JAMMED BICYCLES

EXIT JAMMED

223

TUNNEL OUT PARADE FUNERAL CONVOY

elicit a wide variety of categorizations best characterized as 11 Miscellaneous 11•

ICE should have obtained a high association with "Warning", but it should be

remembered that Southeast Texans have little experience with ice except in cold

drinks!

Discussion

This study was one which called for an entirely open-ended response

in assigning titles to groups of words. Although the subjects typically

used six title categories, the titles given to the categories were almost

idiosyncratic (as many as the subjects themselves). (See Appendix E). There­

fore, the data analysis task became one of the investigators developing

their own categories into which to classify the highly diverse titles

given by the sub.iects.

The investigators felt they saw a common title of 11 Traffic Conditions"

among 75 different titles given in 90 responses. These were expressions con­

taining the words, "condition", "congestion", 11 delay 11, etc. Similarly, they

felt that "Warning 11 was a common title appropriate for the 106 different

titles given in 157 responses. The words involved "accident", "hazard", 11 cau­

tion11, 11warning 11 , 11 roadwork 11,

11 obstructions 11 , 11 obstacles 11 and many diverse

titles. Some of these titles did include vague self-warnings to "be careful",

but the abstraction of 11warning" was implicit at most in a majority of the titles.

224

Again, 25 different_ titles were given in 33 respo11sPs in ,rn i\t't';l clossifit'd

as 11 detour 11• The expression 11 road closed" was used by 13 and the inference might

be 11 detour 11, a word used by 11 subjects.

The word 11 slow 11 appeared in 43 different titles given in responses. In gen­

eral, they were advisories to reduce speed. But it should be noted that the in­

structions were to imagine how the condition might affect the trip one was making,

rather than to classify the expressions in terms of a title with a noun. So the

abstraction was often in terms of a verb telling what the driver should do!

The fifth category, "weather con di ti ons" was an abs traction given both to

factors affecting visibility and things on the road due to the weather. 11 Miscel­

l aneous" was a 11 left-over responses.

The resulting titles were more numerous than the original stimulus words

and the analysts then were required to do the abstracting. The classifi­

cation into the particular six categories was their decision, not the subjects

abstractions.

These six categories were further abstracted by another investigator into

4 categories. However, he then found that 25 of the 39 stimulus words given

locally were associated more often with "warnings". Only 6 were associated

most with "conditions", 2 the most with "detour" and 3 the most with 11 slow 11•

Sn his method of classification was quite different from the earlier analyst.

Unfortunately, this study forced the researchers to assign diverse titles

to the smallest number of categories with an abstract title. This exercise

did not really address the major issue, namely, "Can a single expression such

as "incident" be used in place of several words such as 11 truck overturned", 11 accident 11 and "breakdown" or is it important that each incident be described

uniquely so as to convey the severity? 11 It was thought that perhaps, SLOW

225

MOVING VEHICLES might be preferred to FUNERAL, CONVOY, BICYCLES, PARADE,

and other specific instances of slow traffic. Or that OBJECTS ON THE ROAD

might be preferred to TRASH, DEAD ANIMAL, SPILLED LOAD, etc.

The instructions which biased the subjects to relate how the condition

would affect him as a driver led to a different type of categorizing. The

11 detour 11 titles were probably due to the subjects evaluating the situation as

meriting diversion and the "slow (down)" titles were a similar evaluation of the

correct action to take.

In retrospect, if the study was desirous of a classification in term of

nouns to describe sets of incidents then the experimental questions should have

been stated in a different manner.

As the study was conducted it may not be possible to generate this

type of information from the data. Future research should probably ask direct

questions such as 11 00 you feel that the following expression aptly describes

the following situations?" A set of words would be shown. The next question

would be "Which of the words do you feel should be displayed as listed rather

than being described by the general expression above?"

In this approach the investigator would postulate, in a sense, a number

of titles for categories and the experiment would test whether or not subjects

agreed that the titles were valid substitutes for the individual incidents or

whether he felt the specific problem should be displayed instead.

It is true that the investigator takes the initiative in abstracting

commonalities among words rather than the subjects. He uses his expert opinion

and asks the subjects to concur or disagree. However, the open-ended question

runs the risk of generating highly diverse answers from the layperson and the

226

task of trying to synthesize these into incident categories is beyond the

capabilities of even the most astute analyst.

The major lesson learned from this study was in the area of methodology.

The task of abstracting commonalities among a long list of expressions is one

requiring the highest order of intelligence. Had this task been assigned to a

group of brilliant experts there would still likely have been disagreements

in classification and perhaps a need to apply the Delphi Method to arrive at

a set of abstract titles.

Granted there is a danger that the titles so generated mi~ht not be

understood by the lay public and, therefore, there would still be the need to

conduct an evaluation such as proposed above.

Conclusions ~ t/"

The test subjects in College Station and in Houston appear to need about

6 different categories to sort the 39 varigated incidents. Except for two

broad categories of 11 Conditions 11 and 11 Warnings 11 and two others of lesser signi-

ficance, 11 Detour11 and 11 Slow 11 these categories largely consist of re-statings

of the incident or commentaries on the incident, e.g. "should not happen on a

freeway". It was hoped that the subjects would group the incidents into briefly

worded categories that could be displayed in a CMS. This did not happen. What

appears to be emergent from the results of this study is that most of the inci-

dents are simply classified qS information of an advisory nature, or as situa-.

tions calling for a warning to the motorist about to encounter them. Whether

naming the incident conveys the warning or advisory, or whether it is necessary

to say something like "Freeway Advisory" or "Freeway Conditions" - "Congested"

or 11 Warning 11 -

11 Accident 11 is not addressed by this experiment in free-style

categorization.

227

The instructions may have induced this type of categorization by asking

the subjects to 11 Imagine how this condition might affect a trip you are

making 11• Perhaps it would have been better to have the subjects sort the

incidents without any set at all.

228

Study 2 - Priority of Incident Information

Objectives

(a) To determine which set of conman incidents was of sufficient im-

portance to merit being displayed on a CMS.

(b) To determine if the types of incidents selected differed under peak

and off-peak conditions.

Method

This study was conducted as part of the experiment reported in Topic Area

G-A. Briefly, 70 subjects were asked in Study G-A to select messages to be put

on a sign that would describe a congested freeway and an uncongested, alter­

native freeway during either a peak or an off-peak traffic period. Forty sub­

jects were in the group with off-peak traffic conditions and 30 were in the peak

traffic conditions group.

Next, subjects were given a list of 18 possible incidents (taken from the

list of incidents from Study 1). These incidents could be causing the congestion

ahead, discussed in Topic Area G-A. They were asked to indicate whether or not

each incident descriptor should be included in the sign they had 11 designed 11•

Table F-6 reproduces the answer sheet the subjects used to indicate their V"'

preferences. This study was conducted only in College Station.

Results

The preferences given by subjects in the "off-peak 11, "peak 11

, and combined

group data are summarized in Table F-7. The frequencies of "yes 11 vs. 11 no 11

responses were tested by Chi-square, with the probability given under a null

hypothesis of 11 no preference 11 for the proportions of each yes and no.

229

TABLE F-6 INCIDENT PREFERENCE ANSWER SHEET

INCIDENT TELL DRIVERS?

BREAKDOWN Yes( ) No(

STOPPED VEHICLE Yes( ) No(

ACCIDENT Yes( No(

TRUCK OVERTURNED Yes( No(

LOAD SPlLLED Yes( No( )

TRUCK WRECKED Yes( No( )

TRASH ON ROAD Yes( No(

DEAD ANIMAL Yes( No( )

ROADWORK Yes( No( )

SLOW MOVING VEHICLE Yes( ) No( )

PAVEMENT BROKEN Yes( ) No( )

BUMP IN PAVEMENT Yes( No( )

ICE Yes( No(

FLOODED Yes( No(

WATER ON PAVEMENT Yes( No(

SNOW Yes( No ( )

FOG Yes( No ( )

REDUCED VISIBILITY Yes( No(

230

TABLE F-7 FREQUENCIES WITH WHICH INCIDENTS WERE SELECTED FOR DISPLAY

Off-Peak (40) Peak (30) Combined

Incident Yes No Prob Yes No Prob Yes No -

BREAKDOWN 13 27* .05 13 16 26 53*

STOPPED VEHICLE 15 24 12 16 27 40

ACCIDENT 34* 6 .001 27* 2 .001 61* 8

TRUCK OVERTURNED 28* 11 .01 23* 6 .01 51* 17

LOAD SPILLED 29* 10 . 01 21* 7 .01 50* 17

TRUCK WRECKED 24 15 24* 3 .001 48* 18

TRASH ON ROAD 7 32* .001 11 16 18 48*

DEAD ANIMAL 7 32* .001 11 17 18 49*

ROADWORK 36* 4 .001 26* 2 .001 62* 6

SLOW MOVING VEHICLE 11 29* .01 15 14 26 43*

PAVEMENT BROKEN 21 19 21* 6 .01 42* 25

BUMP IN PAVEMENT 8 31* .001 14 13 22 44*

ICE 37* 3 .001 27* 2 .001 64* 5

FLOODED 38* 2 .001 26* 1 .001 64* 3

WATER ON PAVEMENT 17 22 16 13 33 35

SNOW ON PAVEMENT 28* 12 .02 21* 7 .01 49* 19

FOG 27* 12 .02 22* 7 .01 49* 19

REDUCED VISIBILITY 33* 7 .001 20* 7 .05 53* 14

* Significant at Probability Level Noted

Several subjects tended to leave blank those incidents they could not decide whether to display or not, hence, .the unequal cell frequencies in the table.

231

Prob

.05

.001

.001

.001

. 01

.001

.001

.001

.05

.05

. 01

.001

.001

.001

.001

.001

These data indicated that drivers would prefer seeing the following inci-

dents displayed during peak periods:

ACCIDENT TRUCK OVERTURNED TRUCK WRECKED LOAD SPILLED ROADWORK PAVEMENT BROKEN ICE FLOODED SNOW FOG REDUCED VISIBILITY

During off-peak, all of the above were desired with the exceptions of

TRUCK WRECKED and PAVEMENT BROKEN. These were still preferred by a majority,

but the margin of preference was not statistically significant.

ti on:

The following incidents were not selected for display under either condi-

BREAKDOWN TRASH ON ROAD DEAD ANIMAL SLOW MOVING VEHICLE BUMP IN PAVEMENT

Opinion was divided on the following incidents:

STOPPED VEHICLE WATER ON PAVEMENT

232

Discussion

As expected, the incidents which dealt with a major accident or with road­

work were deemed to be sufficiently important to merit display. Also, localized

effects due to the weather which reduce visibility or which make the surface

slippery or difficult to drive on are worthy of being communicated.

An. examination of the incidents which were not important enough to be dis­

played is equally interesting. Objects on the road such as trash or a dead

animal were rejected. Apparently, the subjects interpreted these as minor

obstacles. Trash could be grocery trash, not large boxes or disabling objects.

The animals were probably the typical game animals or domestic household pets,

rather than a large farm animal.

BREAKDOWN was rejected surprisingly. Again, it can only be surmised that

the vehicle was believed to be off of the pavement.

Unfortunately, SLOW MOVING VEHICLE was presented in the singular form.

One vehicle could easily be passed on the freeway and would understandably not

be necessary for display. However, a convoy or parade of vehicles might have

been deemed important enough for display.

The word, BUMP , perhaps is less formidable than a DIP in the pavement,

because a BUMP may be more localized. Still it is surprising they did not want

this information.

STOPPED VEHICLE is also ambiguous as to whether or not it was on the free-

way itself. STALLED VEHICLE ON FREEWAY might have been judged important enough

for display. WATER ON PAVEMENT is an innocuous statement unless the conno-

tation of being slippery or deep water is given.

233

In summary, eleven incident descriptors were judged to be important enough

for display when they result in congestion of a freeway. The categories of

information were as follows:

• Major Accident

• Roadwork

• Maintenance Needed (load spilled, pavement broken)

• Environmental Factors (creating driving hazards or reduced visibility)

Information not important includes minor objects on the freeway; a solitary

moving vehicle on the freeway, and presumably vehicles off the freeway. (The

latter was an inference only from the rejection of BREAKDOWN).

This study did not investigate specific wording of messages. However,

FLOODED, ICE, ACCIDENT, and ROADWORK met with near unanimous approval

and their brevity also is a point in their favor for their display. Stating

that the accident was an overturned or wrecked truck garnered less support

than the less specific and briefer word, ACCIDENT alone.

There is already considerable evidence that the driver wants to know the

cause of the problem even if the effects thereof are precisely described al­

ready. There is evidence that the word ACCIDENT will result in a considerable

amount of diversion even if there is no sign saying to divert. Describing the

incident may satisfy a human curiosity need, although how specifically it needs

be described was not investigated. Signs are limited in their display capacity,

while audio messages permit greater details. In general, it is probably better

to be brief in describing the incident and more detailed in describing the effects

in terms of delay and other changes in normal traffic patterns.

234

Topic Area A addressed the more basic question of how important it is to

know various types of information and reported that 11 nature of the incident" was I

most important. Therefore, the area of incident communication merits greater

attention in future research.

Design Recommendations

The results of Topic Area Fare incomplete in the area of incident types.

The methodology used in Study l was inappropriate for determining specifically

which types of incidents neeq not be displayed because they are only instances

of a class of incidents. Adqitional research is needed in this area before the

various specific incident messages can be finalized.

Study 2 results suggest that certain common words--ACCIDENT, ROADWORK,

ICE, and FLOODED--are strongly preferred for display, especially under peak

traffic conditions. Incident descriptors which were judged unimportant dealt

with obstacles which could be easily avoided or which introduced no serious

road hazards.

235

Objectives

X. TOPIC AREA G-A - TEMPORAL INFORMATION PREFERENCES IN RELATION TO OTHER INFORMATION ON A

CHANGEABLE MESSAGE SIGN

(a) To determine the types of information chosen for display on a CMS

to advise drivers of a freeway congestion condition ahead and of

an alternate route. Candidate types of information were the two

freeways (the primary and alternate); the level of operation of

each; delay, travel time, traffic speed, and general location of

the congestion.

(b) To determine the individual messages or levels of information pre-

ferred for each type of information. Delay and level of operation

messages were investigated in some depth.

(c) To ascertain the relative frequency with which the traffic state

of the primary and alternate routes are described by the messages

selected.

(d) To discover the degree to which different messages were selected as

a function of displaying the sign during peak and off-peak conditions.

(e) To select the most typical formats or ordering of messages under peak

and off-peak conditions.

(f) To determine the typical message length or number of individual

messages employed in constructing a message which would give the mo­

torist the minimum information he would require under peak and off­

peak conditions.

236

Background

The relative importance of temporal information, such as travel time,

delay, and speed, in comparison with other information on traffic state had

not been established at the beginning of the research program.

The question had been raised as to the degree to which a parametric

study of various temporal descriptors should be undertaken prior to the

establishment that this type of information was sought by motorists in po­

tential route diversion situations.

Therefore, a preliminary screening study was designed in which subjects

were given a smorgasbord of information about a freeway traffic problem ahead.

They were asked to select from the information the minimum information they

feel would be required by motorists approaching the traffic problem and, also,

approaching an intersecting freeway which could be selected as a route for

bypassing the congestion en route to their destination.

There were a variety of secondary objectives of this research, including

the degree to which traveling in peak or off-peak traffic would influence the

messages selected.

Although the subjects were to construct complete messages to advise the

motorists, this study was not designed to investigate all aspects of an

optimum message. For example, the 18 cards given each subject did not con­

tai'n any verbs, such as USE or TAKE which might be selected in directing

traffic to an alternate or diversion route without describing the status of

the route. The focus of the study was principally on the comparative frequency

of use of various traffic descriptors. Other issues relating to the need for

an advisory message were investigated in Topic Area J.

237

Method

This study was a preliminary investigation of information subjects

might choose to display on a CMS, regarding a freeway on which the sign

reader was traveling, and an intersecting freeway. Two main groups of

subjects were used: Group one was a "Peak Period'' of traffic groups;

Group two was an "Off-Peak Period" of traffic setting.

Unlike many of the other studies in this project, subjects in this study

were asked to imagine themselves in Houston and working as a traffic control

engineer. Each subject received a folder which took them through a traffic

game. They were presented a map (Figure G-A-1) which located them in Houston

near the interchange of I-10 and I-610 (a loop or beltway around Houston).

Subjects were told via written instructions that they were to control a

changeable message sign and place on it as much information as they felt

motorists on I-10 might need but no more. The subjects in Group 1 (Congestion)

were informed that their problem was:

11 It is 5 o'clock on Tuesday afternoon, and all of the plants in the

Industrial Park just off Interstate 10 have let out the first shift of workers.

These workers live in a lot of places in Houston, but the great majority are

ex-refinery workers who live on the east side of Houston in Jacinto City and

Galena Park.

"Notice that commuters to East Houston can use I-610 to get to their

homes. Here's the way travel times at 55 mph compare:

Point A to Point B via I-10 - 15 minutes

Point A to I-45 (Point C) via I-10 - 7 minutes

Point A to Point B via I-610 NORTH - 25 minutes

Point A to I-45 (Point 0) via I-610 NORTH - 12 minutes

238

N w l.O

/' .. /

.... ,_ "'~al. 10ll.

J~

':-..... .............. fi

"'-:-- ~-·,~ ~·~'

""'-,M1i'-'thH1 ', '1.q staifurd . -~ll~ A('>--, 'i>'i>fs

\ -'i>,. - .

t. &~--

'L::____

~,,,.,,

\~,1\l''I)

It!

\ HARRIS

.... .... (te1!I

c,.C:',·.t. BRAZORIA

ll)

\ \

HARRIS t LtGERTY

\--:--;-

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\ :"'!<) Baytown

j' __ ~ . ,,9 >' /

""'Y-~,, ( lu1r•a•

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I 1'1~) '-t"<.:::~"F=-----..._JLJl___ __ ~,~·"'~'!!' """''"""""-"v\-----ir- L.t Porte

FIGURE G-A-1 - MAP FOR SUBJECTS IN THE PEAK-TRAFFIC CONDITION

11 As the commuters leave their factories in the Industrial Park and get

on I-10 to go home, they see your sign as they approach the I-10 or I-610

interchange. 11

Subjects in the other group, Group two (Non-Congestion) were told

(See Figure G-A-2):

"It is 3 O'clock on Sunday afternoon and people are returning to

Houston and to places like Beaumont to the east of Houston on Interstate 10.

11 Notice that these travelers to the east of Houston can use I-610 to

get around Houston. Here's the way travel times at 55 mph compare:

Point A to Point B via I-10 - 15 minutes

Point A to I-45 (Point C) via I-10 - 7 minutes

Point A to Point B via I-610 NORTH - 25 minutes

Point A to i-45 (Point D) via I-610 NORTH - 12 minutes

11 As the travelers drive east on I-10, they see your sign as they

approach the 10 - 610 interchange.

Then the written instructions went on to say for either group, that

a spotter in a helicopter has called in to say:

MESSAGE

AT THIS TIME TRAFFIC IS FLOWING ABOUT AS USUAL ON INTERSTATE 610 NORTH

OF THE 10 - 610 INTERCHANGE ON THE WEST OF HOUSTON. TRAFFIC IS MORE CONGESTED

ON I-10, AND TRAFFIC HAS SLOWED TO 20 MILES PER HOUR. THE CARS ARE NOT

MOVING ALL THE TIME IN SOME LANES. THE CONGESTION ON I-10 IS BETWEEN I-610

AND I-45. TRAVEL TIME ON THIS DISTANCE IS ABOUT 30 MINUTES, OR ABOUT 23

MINUTES LONGER THAN USU/\L. I CAN'T TELL WHAT THE PROBLEM IS, BUT IT LOOKS

AS THOUGH IT'S GOING TO TAKE QUITE A WHILE TO CLEAR UP.

240

/"-,"-..

t',,,"'

"'----'-,_ c:>o·~N~".11.a..!b..\_·

J 1

HARRIS

/BRAZORIA

MAP FOR SUBJECTS FIGURE G-A-2 -

I . ; I

I l, ___ l \ --- - i

"'--..

\

TRAFFIC CONDITION IN THE OFF-PEAK

~·--

The subjects were then instructed to take out some Hollerith cards

to 11 program the sign computer. 11 The next steps are best described in the

original instructions:

11 Now please get out your card set from the pocket in this folder. Lay

the cards out so you can see all of them.

11 Noti ce that you have a card for I-10 and a card for I-610. Then you

have cards which can describe the traffic conditions. If you used all the

cards, you would make the computer light up a sign that would be too long to

read, and it would use a lot of energy. You can choose cards to describe

traffic on I-10 or on I-610, or on both I-10 and I-610. Pick the cards that

make up what these drivers on I-10 need to know before they get to the inter­

change. Put the cards with either I-10 or I-610, or both, so the computer

can show the information correctly.

11 Please turn back to the tab marked iMessage' and re-read the message

to be sure you understand the problem.

11 Now pick the parts of the message you think the drivers should see

on the sign you are controlling. Put these cards in the order in which you

want them to appear on the sign under the I-10, I-610, or both. Put the

first message under these cards, the next message directly under it, and so

on.

242

TABLE G-A-1

MESSAGES FOR PROGRAMMING 11 COMPUTER 11

I-10 (Freeway Designators) I-610

23 MINUTES NO DELAY DELAY (Delay) SHORT DELAY MODERATE DELAY LONG DELAY

NO CONG ES TI ON CONGESTION SLOW TRAFFIC (Levels of Operation) VERY SLOW TRAFFIC STOP-AND-GO TRAFFIC

12 MINUTES TO I-45 (Travel Times) 30 MINUTES TO I-45

20 MPH (Speeds) 55 MPH

AHEAD (Di stance)

243

technique which has been used so extensively in this project. There were

18 possible message elements to be combined. The cards were in a pocket of

the folder, in random order.

In a second part of the study, a list of possible incidents was given

to the subject, as though the helicopter pilot had swooped closer to the

trouble spot. Subjects were all asked to indicate for each incident

whether or not the problem should be displayed on the CMS. These findings

were reported earlier in Topic Area F, "Incident Descriptors."

37 subjects participated in Group I, the "Peak" conditions, and 37

different subjects were used in Group I I, the 11 0ff-Peak 11 condition. The

study was conducted in the laboratory on the campus of Texas A&M.

244

Results and Discussion

Table G-A-2 presents the frequencies of messages used by subjects during

the 11 Peak 11 traffic condition, during the 11 0ff-Peak 11 traffic condition, and

totals across both groups of subjects. Also, given within cells are the to­

tals by type of descriptor such as delay, level of operation, travel time, etc.

The major findings were as follows:

1. The types of descriptors used most often were the two freeways and level

of operation 1 with delay information a strong third. It should be noted,

however, that there were more options to choose from under level of oper­

ation and delay than under travel time and speed. While this may have

produced a bias it should also be noted that both SPEED and TRAVEL TIME

were mentioned in the message telling about the primary route and, also,

travel times between various points on I-10 and 610 were given in the

instructions. These things should have increased their potential use.

In contrast, DELAY was not specifically mentioned in the message except

indirectly that it may take a while for traffic to clear up.

2. The individual messages used most frequently presents a slightly different

picture. Again, the freeway routes, particularly the route with the con­

gestion, were used the most often. CONGESTION ranked third and the

distance descriptor, AHEAD was fourth. (These descriptors were often

used in sequence.) No other descriptors were used by as many as a third

of the subjects.

1 The 74 subjects mentiqned 1-10 63 times, but they mentioned levels of operation applicable to 1-10 (exclusive o'f "no congestion") on 86 occasions, several using two descriptors of level of operation. So collectively the descriptors of level of operation on the primary route exceeded the frequency with which the route was given by route number.

245

TABLE G-A-2 MESSAGES USED DURING PEAK AND OFF-PEAK INSTRUCTIONAL SETS

..

---

MESSAGES PEAK OFF-PEAK TOTAL

FREEWAY DESIGNATORS 55 53 109 1-10 29 34 63 1-610 26 19 46

-- --DEL/\Y 29 27 55 --23 Minutes 6 8 14 No Delay* 9 8 17 Delay 2 0 2 Short 2 2 4 Moderate 4 0 4 Long 6 9 15

LEVELS OF OPERATION 51 51 102 No Congestion* 8 8 16 Congestion 14 21 35 Slow Traffic 8 3 11 Very Slow Traffic 10 9 19 Stop-and-go Traffic 11 10 21

TRAVEL TIMES 21 7 28 12 Minutes to I-45* 5 0 5 30 Minutes to I-45 16 7 23

SPEEDS 14 14 28 20 MPH 10 8 18 55 MPH* 4 6 10

DISTANCE 12 18 32 Ahead 12 18 32

INCIDENTS (Not Applicable)

*Messages applicable to alternate. All others apply to the primary route.

246

3. Messages which applied to the primary route were used more often than those

applying to the alternate route except for the NO DELAY message, which was

approximately the same. At most 17 of the 73 subjects selected a descriptor

for alternate route status. Subsequent research (Topic Area J) has indicated

drivers prefer an advisory to USE or TAKE the alternate route after being

given the status of the primary route. However, this option was not part of

the experimental design.

4. "Peak" and "Off-Peak" frequencies of use were amazingly consistent with two

noteworthy exceptions: l) 78 percent of the peak subjects referred to

the primary route and 70 percent to the alternate. The off-peak equivalents

of subjects choosing these routes were 94 percent and 53 percent. It

would appear the status of the alternate route was less important during

off-peak. Off-peak drivers may not have viewed the problem as severe enough

to consider taking the alternate route.

Table G~A-3 presents Chi-squares between off-peak and peak selection

frequencies of I-10 and I-610. The table also presents X2 tests for the

other three messages chosen by 40 or more percent of the subjects in at

least one group. The results indicate no differences with the one possi­

ble exception. 30 MINUTES TO I-45 was a favorite message under peak

condition, but was seldom use off-peak. Table G-A-3 indicates a weak

significant difference between groups for this message. It is suggested

that the 30 MINUTE DELAY for 3:00 p.m. on Sunday afternoon may have

defied credibility criteria of the subjects.

5. Tables G-A-4, G-A-5, and G-A-6 present the lines on which the various mes­

sages appeared for the combined, off-peak, and the peak condittons. Note-

247

TABLE G-A-3

RESULTS OF CHI-SQUARE TESTS OF FREQUENCIES OF SELECTION OF MESSAGES (40% CHOSE OR MORE)

Peak vs. Off-Peak:

I-10 x2 = 0.55 df = 1

I-610 0.92 1

Congestion 1. 58 1

Ahead 1.36 1

30 Minutes to I-45 3.34 1

248

n.s.

n.s.

n.s.

n.s.

< 0.10

TABLE G-A-4 FREQUENCY OF SIGN MESSAGES FOR COMBINED CONDITION BY LINE ORDER

Line Order MESSAGES 2 3 4 5 6 7 8 Total

FREEWAY DESIGNATORS -----@ 1-10 3 9 8 l l

1-610 9 4 8 @ 6 l 3 ---

DELAY 23 Minutes 2 4 l 4 l 2 No Delay l 3 2 5 5 l Delay l l Short 2 l l Moderate 2 l l Long l 4 4 3 2 l

LEVELS OF OPERATION ----@ No Congestion 2 l l l 2

Congestion 8 @ 4 3 2 Slow Traffic 2 2 2 l 3 l Very Slow Traffic © 3 6 l Stop-and-go Traffic l ® 3 2 3 2 l

TRAVEL TIMES 12 Minutes to 1-45 - l 2 l l

~ 30 Minutes to 1-45 3 l 7 4 3 4 l

SPEEDS 20 MPH l 6 3 7 l 55 MPH 2 2 l l 3 l

DISTANCE Ahead 2 9 @ 2 l l

TOTAL LINE USAGE 74 74 69 60 42 18 10 4

Q= the line on which a message appeared with modal frequency. Messages with no frequency circled are more randomly appearing on lines.

249

63 46

14 17 2 4 4

15

15 35 11 19 21

5 23

18 10

29

TABLE G-A-5 FREQUENCY OF SIGN MESSAGE FOR OFF-PEAK CONDITION BY LINE ORDER

Line Order MESSAGES 2 3 4 5 6 7 8 Total

FREEWAY DESIGNATORS ----@ I-10 l 2 2 l

I-610 l 2 5 @ l l -

DELAY 23 Minutes l 3 l 3 No Delay 1 l 3 3 Delay Short l l Moderate Long 2 2 2 2 l

LEVELS OF OPERATION No Congestion l © l Congestion 3 @ l 3 l Slow Traffic 2 l Very Slow Traffic 0 l 2 Stop-and-go Traffic 4 3 2 l

TRAVEL TIMES 12 Minutes to I-45 30 Minutes to I-45 4 l l l

---SPEEDS 20 MPH l l 3 3 55 MPH l l l 3

DISTANCE Ahead l 3 @ l l

TOTAL LINE USAGE 37 37 34 31 20 7 2 2

0= the line on which a message appeared with modal frequency. Messages with no frequency circled are more randomly appearing on lines.

250

34 19

8

8

0 2 0 9

8

21 3 9

10

0 7

8

6

18

TABLE G-A-6 FREQUENCY OF SIGN MESSAGES FOR PEAK CONDITION BY LINE ORDER

Line Order MESSAGES 2 3 4 5 6 7 8 Total

FREHJAY DESIGNATORS 1-10 @ 2 7 6 l 1-610 8 2 3 6 5 l 2

DELAY --23 Minutes 1 l 1 l 2

No Delay 2 2 2 2 l Delay l 1 Short 2

Moderate 2 l l Long l 2 2 1

LEVELS OF OPERATION No Congestion 2 . 1 1 2 2 Congestion 5 5 3 l Slow Traffic l 2 l 3 l Very Slow Traffic 3 2 4 l ..

Stop-and-go Traffic l 5 2 l 1 l

TRAVEL TIMES 12 Minutes to I-45 l 2 l 1 30 Minutes to I-45 3 l 3 3 2 3 l

SPEEDS 20 MPH 5 4 1 55 MPH 2 1 l

DISTANCE Ahead 1 6 2 2 1

TOTAL LINE USAGE 37 37 35 29 22 12 8 3

c:::)= the line on which a message appeared with modal frequency. Messages with no frequency circled are more randomly appearing on lines.

251

29

26

6 9

2 2 4 6

8

14 8

10 11

5 16

10 4

12

worthy is that for both peak and off-peak, the primary route is preferred

on the first line. The off-peak and combined data suggest that the second

line should be for the level of operation (congestion, very slow, or stop­

and-go traffic) of the primary route. The third line should be used for

the distance (ahead), and the fourth line for the alternate route. If a

fifth line were used, the level of operation of I-610 (no congestion)

was preferred. The peak data was more random in the lines chosen. The

listing of the primary route prior to the alternate has been supported

by other research (See Topic Area J). It was especially noteworthy here

because the status of the alternate route was always given first in the

message to the subjects.

6. Tables G-A-4, G-A-5, and G-A-6 present on the bottom row the total numbers

of subjects using any message on a particular line. The data in Table

G-A-4 indicate all subjects built messages with at least two of the cards,

all except 5 used at least three cards, and all but 14 subjects used four

or more of the 18 cards in the deck. 57 percent of the subjects made

up messages with five or more cards, but only 24 percent used as many as

six. Analysis indicated five messages was the modal frequency of use.

The peak and off-peak totals shown in Tables G-A-5 and G-A-6 follow a very

consistent pattern with no one selecting more than 8 cards. The in­

structions were not to tell the motorist more than he needed to know

and to economize on electrical power. There were five types of traffic

information and four of the types had different messages applicable to

each route. Counting the 2 routes as 2 messages, subjects typically

selected 3 other messages from among the five types of information.

252

The finding of five messages as a modal frequency should not be

interpreted as generally applicable to any real-time signing situation.

Other ~tudies such as the Advanced Sign study (Topic Area H) and the

Format study (Topic Area J), which employed a similiar analysis of message

usage, have indicated the message length varies with the total message

cards available. The present study employed the most cards of any study

(18) and, hence, five messages may be an upper limit. It should be noted

also that the "messages" used in this study are actually message elements

with two or more elements required to convey a complete thought, e.g~,

I-10 - CONGESTION, I-610 - NO CONGESTION, and CONGESTION AHEAD are complete

status messages. Using this mode of interpretatin, the total information

transmitted is only two or three units.

Summary and Conclusions

1. In regard to Objective (a), the types of traffic state information men­

tioned most often were the level of operation and delay. Travel times

and traffic speeds were used less often despite the emphasis placed upon

travel times in the instructions.

The topic of incident types was investigated in a separate study

but was not considered in this study. Neither was specific distance infor­

mation which other studies have indicated is important (See Topic Areas J

and D). The general descriptor AHEAD was used frequently, however.

2. As a type of information, the primary and alternate route designators were

selected the most frequently, which suggests that motorists prefer these

in a sign message. One tempering observation on their importance should

be made. Subjects were instructed to "put these cards in the order in

which you want them to appear on the sign under the I-10, I-610, or both".

253

The instructions may have encouraged the use of at least one route desig­

nator and suggested the use of both with appropriate traffic state infor­

mation.

In light of this, the finding that 11 subjects (15 percent) did not

give the I-10 designator and that 28 (38 percent) did not give the I-610

designator is sobering. Subjects were not permitted to use familiar

designators such as NORTH LOOP instead of I-610 or KATY FREEWAY instead

of I-10. Subjects could select CONGESTION AHEAD without mentioning the

route by name.

3. Also, the question of presenting traffic state information regarding the

alternate route merits some consideration. Objective (c) was to determine

the comparative frequency of use of traffic state information for the

primary and alternate routes. For the four types of information, only

48 descriptors were chosen for the alternate route as opposted to 165 for

the same four types of information for the primary route (not including

AHEAD). While the findings are not conclusive as to whether alternate

route status was desired, it is evident that status of the primary route

was deemed more important. As noted previously, the experimental design

did not permit the selection of a simple advisory to "Use I-610" instead

of giving the traffic state of the route. Topic Area J is more conclusive

in its findings in this regard.

4 .. In regard to Objective (b), the individual messages most preferred in

addition to the route designators, were CONGESTION (35 choices) and AHEAD

(32 choices). Other messages used frequently were 30 MINUTES TO I-45 (23)

and STOP-AND-GO TRAFFIC (21).

254

Of the descriptors describing the traffic state on the alternate route

the favorites were NO DELAY (17) and NO CONGESTION (16), which ranked

9th and 10th in overall frequency of use. The fact that at most 23 per­

cent of the subjects selected a descriptor of the alternate route sup­

ports the point made earlier. However, if alternate route status is to

be displayed these messages were preferred to giving travel time or speed

on the alternate route.

Of the delay messages to describe the primary route, LONG DELAY (15)

and 23 MINUTE DELAY (14) were highly preferred to the other three messages,

although there was no strong support for any of the delay messages. Again,

it should be mentioned that the instructions did not specifically

mention "delay" and the choice of a descriptor, if any, was a deduction

by the subject.

5. With respect to the fourth objective of the research, subjects were very

consistent in their choice of both types of information and individual

messages regardless of whether the situation was described as a peak or

off-peak time. The one exception, as noted earlier, was travel time on

the primary route being selected principally during peak conditions.

6. With regard to Objective (e), the combined data for peak and off-peak

indicated some preferences for the line on which a particular message

should appear. However, the peak data only provided little consistency

other than that the first message should be the name of the primary route.

The combined data suggest the order of information should be as

follows:

(a) Primary route designator

(b) Level of operation - primary route

255

(c) Distance to the congestion

(d) Alternate route designator

(e) Level of operation of alternate route

The fifth line is very tentative, since only 15 subjects used the level

of operation of the alternate route.

7. 80 percent of the subjects used at least 4 of the 18 messages, while

57 percent used five or more messages. However, since two messages were

required to make a complete statement or unit of information,. the message

lengths typically were only two or three statements: primary route status

(and distance) and alternate route status. In general, only one status

descriptor for each route was deemed necessary on a particular display.

Message length was unaffected by the peak or off-peak conditions,

8. In general, there is sufficient support for delay information to merit

further study of this type of traffic descriptor. However, a parametric

study of traffic speeds and travel times does not appear to rank as high

in priority.

256

Discussion

The present study was a preliminary study to assess general areas of

temporal and traffic state information, rather than a study of detailed

message design. Any design recommendations must be viewed in the context

of the research and are tentative pending further study.

1. The preferred message, based on the present research, was as follows:

I-10 - CONGESTION AHEAD

I-610 - NO CONGESTION

or

I-610 - NO DELAY

2. Topic Area J has found a slight preference for CONGESTION ON I-10. (the

traffic problem prior to the route designator). This was not a candidate

in the present research since ON was not included in the cards.

3. NO CONGESTION was the only expression used to describe level of operation

on the recommended alternate route. Topic Area J used LIGHT TRAFFIC for

this application. The specific expression recommended is beyond the scope

of this study.

4. Similarly, NO DELAY was the only message used to describe delay status

of the alternate route. Other temporal studies in Topic Area G investigated

"Time Saved" and "Comparative Travel Time. 11

The present study did not address, also, the issue of whether or not

specific delay time (in minutes) is as effective as qualitative statements

of delay. The 23 MINUTE DELAY was among the preferred descriptors, but

LONG DELAY was equally preferred. No conclusions are made on this issue.

5. Travel Time and Traffic Speed are temporal information not recommended

for display in this context for the following reasons:

257

(a) Both descriptors refer to specific values which are easily verified

by the driver should he choose to remain on the primary route. The

credibility of the signing system and traffic control is challenged

if the message is in error.

(b) These parameters may be difficult to measure or estimate with accuracy

since they fluctuate from time to time and within sections of the

freeway.

(c) The parameters refer to absolutes, which are not especially meaningful

until they are translated into a form to which the driver can relate.

"Delay", 11Time Saved'' and 11 Comparative Travel Times" (on the two

routes) all present relative information in a directly useful form.

Because they are derived information they are also not easily dis­

proved by simple observations such as looking at a clock or a speed­

ometer.

(d) The finding in the present study that 23 subjects preferred travel

time and 18 preferred traffic speeds should be viewed in the context

of the instructions. As discussed earlier, the preliminary instruc­

tions gave specific travel time information to various locations on

both routes. The intent was to indicate that I-10 was initially the

best route and to provide a basis for subjects to interpret correctly

that 30 minutes was ~ubstantially longer than off-peak travel times.

However, inadvertently subjects may have been encouraged to 11Think

travel time 11• Also~ as pointed out earlier, the message was very

specific about travel time (30 minutes) and traffic speed (20 mph)

and cards were incl4ded with these specific values given. In contrast,

delay was not mentioned specifically. For these reasons, it is

258

suggested that travel time and to a lesser degree traffic speed were

somewhat higher than they might have been otherwise. Drivers, even

commuters, may not have specific point-to-point infonnation on travel

times stored in their memories and may reject such information prin­

cipally because they do not know what it means in terms of making

a diversion decision.

6. Of the types of information investigated, 4 or 5 messages, including the

route designators, is the maximum information preferred for a single CMS.

7. The optimum message for this application is beyond the scope of the study

since so many messages, irrelevant to the objectives of the study, were

not investigated.

There is some indication from this study that level of operation of

the primary route is more important in a CMS than giving a name or number

to the route on which the traffic is traveling. As noted, 11 subjects

did not give the route a name, while the level of operation was mentioned

more times (86) than there were subjects.

One might argue that in a sign it is obvious that all drivers reading

the sign are, in fact, on the route (I-10) and mentioning the route by

name is as formal and redundant as ca 11 i ng a friend on the telephone and

asking if Mr. Jones (the friend) would come to ones office. The personal

pronoun, 11you 11, is used instead in common syntax, but this may al so be

implied.

The upshot of this may be that the most informative message for the

application posed may be quite different from that recommended from the

research. For example, it might be as follows:

259

CONGESTION AHEAD

USE NORTH LOOP NEXT EXIT ' Since not all traffic may be traveling to Beaumont, Jacinto City, or

Galena Park (points east of Houston), as posed in this study, it may be

necessary to be more specific, for example:

CONGESTION - 2 MILES

CONGESTION - AT SHEFFIELD

These and related issues are discussed in other topic areas.

(See Topic Area J for advisory vs. status information and Topic Area D

for location of congestion information).

260

XI. TOPIC AREA G - TEMPORAL INFORMATION

Objectives

(1) To determine the expressed need for temporal information such

as delay, time saved, and travel time.

(2) To determine. the number of levels of delay or time saved which

should be displayed and the particular levels which are signifi-

cant to motorists in terms of diversion decision.

(3) To determine the rneanings of "major"and "minor" accident in terms

of delay.

(4) To detennine the specific meaning of the word, "delay", to freeway

motorists.

(5) To determine the preferred method for presenting verbal messages

Background

dealing with temporal infonnation about a congested freeway and a

temporary bypass around the incident. The candidate methods were

avoid delay, save time, and comparative travel times.

The literature is not consistent on the importance of temporal informa-. I

ti on .in comparison with other types of traffic descriptors. Heathington,

Worrall, and Hoff {l_) reported that "Delay" ranked fifth and "Travel Time"

sixth when compared with information on congestion level, cause of congestion,

speed, and stop-and-go traffic signing.

Case, Hulbert, and Beers {g_) reported "Delay Time" third in importance

to "Lane Blockage" and "Distance to the problem. 11 Dudek and Jones (3) found

expected delay time ranked s;xth while time saved by taking an altern~te route, '

travel time, and freeway speed ranked even lower in the order given.

261

Other investigators have reported more promising results for temporal

information. Gordon (1) has recommended the display of comparative travel

time information in point diversion situations. As indicated in the, TTI

State-of-the-Art survey, several cities currently display temporal informa­

tion on changeable message siqns (~).

The first study reviewed in the present series of temporal studies is a

further attempt to establish the expressed need of freeway motorists for

temporal information.

In the second study the investigators presumed that "delay" information

is desired and addressed the practical consideration of how much and what

parameters of delay should be displayed. An assumption was that if delay

durations are to be displayed they should result in some change in the driver

diversion decisions. In one of the regional studies, the expression, "time

saved 11 also was investigated in terms of the amount of savings which would

result in a diversion decision.

A third study investigated the meaning of certain incident expressions

in terms of delay.

11 Delay 11, expressed in minutes, appeared to be an inherently ambiguous

concept. In part, the lack of support for delay information reported in the

literature may be due to the motorists confusion as to what the message means.

In part, it may also be due to his questioning the ability of traffic control

to provide the kind of delay infonnation he requires.

A fourth study addressed the above problem by asking for the drivers

interpretation of a sign displaying "30 minutes delay".

262

As indicated above, 11 Delay 11 is only one way of expressing temporal infor-1

mation. Comparative travel times on the primary and alternative routes is

another way of expressing delay in somewhat less ambiguous terms. The time

saved by taking an alternate route is more positive, perhaps reinforcing

way of stating temporal information.

The final study in this topic area dealt with subjects preference for

these alternative ways of presenting temporal information and the reasons

given for their choices.

263

Study 1 - Expressed Need for Temporal Information

Objective

To detennine the expressed need for temporal information.

Method

In the first study, s4bjects were instructed that they should imagine

themselves on a freeway under time-critical conditions. An accident had

occurred one-half mile ahead of them and there were no exits available. (See

instructions in Volume 12).

The experimental task was to write down one question which they would ask

a police officer over their citizens band radio. Restricting the questions to

one would establish which single class of information was most important.

One hundred thirty-three subjects from Houston responded to the question.

Seven categories of subject responses were predetennined for classifying

the questions posed. These categories and examples of subject questions classi­

fied in each category are given in Figure G-1.

Results

Table G-1 summarizes the findings of the study in tenns of the number and

frequencies of questions which were classified in the seven categories.

Noteworthy for the first objective of this study was the finding that

20.3 percent of all subjects' questions related to the delay anticipated by

the accident. The percentage of subjects asking this question was second only

to "route continuation feasibility", which was asked by 25.6 percent.

Perhaps these data and the previous data reported in Topic Area F suggest

that in incident-type situations, delay information assumes greater importance.

264

Cat. I.

FIGURE G-1

CATEGORIES FOR CLASSIFYING QUESTIONS AND TYPICAL QUESTIONS

DELAY

How long the delay? How long will traffic be held up? (or blocked) How soon before traffic moves again? How long before I can get by?

Special type - Incident Clearance

How long before the accident is cleared (so traffic will move)? How soon will they clear the roadway?

Cat. I I. ROUTE CONTINUATION. FEASIBILITY

Can I get through? Is the road open? Can traffic get by or around the accident? Would I be allowed to drive around it or go through?

Special type - Traffic moving

Is there any traffic flow? Is traffic proceeding at slow speed?

Special type - Total blockage

Are all lanes blocked? Is traffic blocked at the accident site?

Cat. III. LANE GUIDANCE

Which lane should I be in to avoid delay? Which lanes are blocked? Are some lanes open? Which?

FIGURE G-1 (Cont.)

Cat. IV. ROUTE DIVERSION FEASIBILITY

Cat. V.

Is there an exit open? Direct me to the nearest exit? Which exit to take? Is there a cross-street or cross-over I can take? How can I 11 get to 11 the streets?

BEST ACTION ADVICE

Tell me what to do? Would it be better to exit, to get in a lane & continue, or will

the accident clear soon? Should I take another route or wait? Should I go through the traffic or let it clear?

Cat. VI. BEST ROUTE ADVICE

What is the best way to go to (destination)? (Implies that driver could get off freeway and is selecting an

alternate route)

Cat. VII. MISCELLANEOUS RESPONSES

Give me a police escort; give me clearance; help! What happened at accident? Any help needed? Change my appointment time. How about a helicopter lift?

DELETE

1 Totally illegible (to several scorers) 1 Duplicate (answered twice) 1 No answers 1 Include all others under miscellaneous

Cat I

Cat II

Cat III

Cat IV

Cat V

Cat VI

Cat VI I

TABLE G~ l FREQUENCY AND PERCENTAGE OF QUESTIONS

BY CATEGORY

_L

DELAY 27 (All Varieties)

ROUTE CONTINUATION FEASIBILITY 34 (Including all lanes blocked)

LANE GUIDANCE 10

ROUTE DIVERSION FEASIBILITY 20 (Where can I exit?)

BEST ACTION ADVICE 8 (Wait, Continue, Divert)

BEST ROUTE ADVICE 20 (Assuming Diversion)

MISCELLANEOUS RESPONSES 14 (Contingency action, curiosity, aid, etc.)

N = 133

267

.%

20.3

25.6

7.5

15.0

6.0

15.0

10.5

99.9

These data should be interpreted in the light of the information already

given to the subjects in the instructions. For example, the nature of the

problem -an accident- was given and the location of the problem (one-half mile

ahead) was also given. Although the time of day was not given, congestion was

apparently assumed. Therefore, the options open for questions were somewhat

constrained.

Subjects were told there were no exits so that questions would focus on

the traffic problem, rather than simply asking: "Where can I exit?". Despite

the instructions, 15 percent asked that type of question, and 15 percent also

asked for a best route, which implied they could get off the Interstate (con­

trary to instructions). Few asked for accident severity when limited to one

question.

The nature of the situation posed was one in which there was just enough

time to keep an important appointment. Therefore, any event which would com­

promise this goal would be expressed more likely in terms of delay.

Although the study results should not be construed to mean that "Delay"

is the most important thing that comes to mind when traveling on freeways

in general, the data do substantiate other studies in underscoring the importance

of delay when time is critical. Therefore, the feasibility of displaying

delay information (and how to display it) is a subject meriting further

research.

268

Study 2 - Delay Duration and Diversion

Objective

The second study involved questioning subjects as to how much delay they

would tolerate before they would divert from a freeway. A design implication

from the results would be that particular delay periods may be used to induce

various degrees of diversion. Also, it may be that there is no need to display

numbers or levels of delay which would have no effect on their driving behavior,

i.e., if a fewer number of delay durations will suffice, these only should be

displayed.

Method

The method employed did not directly establish the numbers and levels of

delay required, but the method was designed to determine levels of delay not

required and, by deduction, pennit the estimation of the former.

The subjects were told to imagine themselves on Loop 610 in Houston,

headed for the Astrodome. One group was presented a picture of light traffic

and the other heavy traffic, as the situation in which they were traveling.

The subjects were then presented in random order with seven cards, each

card representing a different delay period. Five different types of incidents

were also investigated using an independent group's design.

An incident word appeared first on each card. The incidents were as

follows: ACCIDENT, RAIN, ROADWORK, TRUCK OVERTURNED, and ICE. Following each

incident, one of the seven delay periods was given.

The delay periods were as follows: {5, 10, 15, 20, and 30 minutes,

1 hour, and 2 hours).

269

The experimental task was to check on an answer sheet one of two

alternatives for each sign presented. The alternatives were "Stay on Free­

way" or 11 Get off Freeway 11• The subjects went through the card deck reading

the signing messages and deciding if they felt the combination of delay

period - incident - traffic situation merited diversion.

There were 240 subjects assigned to the five incident groups as shown v

in Table G-2. The study Wgs conducted locally in College Station.

Results

The results of the secqnd study are presented in Table G-2 and in

Figures G-2 and G-3. Frequencies in the 11 Yes 11 columns of Table G-2

indicate the number of subjects who elected to stay on the freeway and

frequencies in the 11 No 11 columns are subjects electing to divert under the

displayed conditions. Those not answering were omitted, but may be cal-

culated by deduction.

The results indicate the same pattern of Yes/No responses to the delay

periods regardless of the type of incident presented or the level of con­

gestion pictured. Figure G-2 also indicates that for all incidents the

50th percentile diversion occurs at between 15 and 20 minutes of delay.

At this delay, subjects shift from a decision to stay on the freeway to a

decision to divert. Longer periods of delay result in proportionally larger

numbers diverting while peripds of less than fifteen minutes result in

proportionally fewer subjects diverting.

At the bottom of Table G-2 are the totals combined across incident type

and traffic levels. The results indicate one and two hour delays are not

significantly different in terms of percentage diverting. Thus, at most six

270

TABLE G-2 FREQUENCIES OF A DIVERSION DECISION AS A FUNCTION OF INCIDENT

TYPE, DELAY PERIOD, AND TRAFFIC CONDITIONS

Would you stay on the freeway?

Light Traffic Frequency

Heavy Traffic Frequency

Light Traffic Frequency ..._

Heavy Traffic Frequency

Light Traffic Frequency

Heavy Traffic Frequency

Light Traffic Frequency

Heavy Traffic Frequency

Light Traffic Frequency

Heavy Traffic Frequency TOTAL

ACCIDENT

5 M{nute 10 Minute 15 Minute 20 Minute 30 Minute 1 Hour 2 Hours Del av Del av Del av Del av Del av Del av Delay

Yes No Yes No Yes No Yes No Yes No Yes No Yes No

35* 5 32* 9 23 18 13 28* 9 33* 3 39* 2 40*

38* 5 33* 11 24 22 15 29* 6 41* 1 43* 5 40*

N = 87 RAIN

5* 1 5* l 4* 2 4* 2 l 5* 0 6* l 5*

12* 2 10* 3 9* 6 7 7 6 7* 5 8* 5 9*

N = 21 ROADWORK

•.

18* 1 15* 4 14* 5 9 10* 3 17* l 19* 1 17*

19* 3 15* 7 9* 5 3 19* 5 19* l 22* 2 19*

N = 44 TRUCK OVERTURNED

26* 3 21* 7 22* 6 13 15* 9 20* 1 27* 0 28*

20* 0 17* 2 16* 6 10 11* 1 21* 2 20* l 21*

N = 51 ICE

N = 37

21 * 2 21* 3 21* 4 12 13* 7 17* 3 22* 0 22*

10* 2 9* 3 8* 3 5 7* 3 9* l 11* 1 11*

204 24 178 50 148 77 91 141 50 189 18 217 18 212

* Asterisks indicate a significant difference (p>.05) between ·the "Yes" and "No" responses in each cell. (Chi-square test)

271

N ""-J N

100

90

80 ROADWORK

70 ---

z 60 0 U) 0::: 50 UJ > 0 40 ~ 0

30

20

10 OVERTURNED

10 20 30 40 50 60

DELAY IN MINUTES

Figure G-2 - Effect of Incident Type and Delay Duration on Percent Diversion (College Station)*

10{)

90

80

70

z 60 0 U) ,!.-rLIGHT er: 50 LaJ I

> I I

0 40 I

~ I

0 I I

30 • I I

I 20 '/

I I

/ 10

10 20 30 40 50 60

DELAY IN MINUTES

Figure G-3 - Effect of Traffic Conditions and Delay Duration on Percent Diversion (College Station)

*Based on data collected only in Bryan-College Station area

levels of delay are meaningful Jn terms of getting any differences in drivers'

responses.

The traffic engineer may manipulate the proportion of traffic diverting

by selecting levels of delay appropriately.

Figure G-2 illustrates that incidents dealing with RAIN and ICE did

not result in complete diversion even up to one hour delay. This could be

due to an unwillingness of some subjects to believe that traffic conditions

would be better on an alternate route. Figure G-3 indicates a very slight

but consistent tendency to divert at a lower level of delay in heavy traffic

than in light traffic. Again, this may be due to some questioning the

credibility of delay durations when traffic appears to be moving smoothly.

Regional Studies

Stud~1 was replicated in St.

in Los Anget{s with 40 subjects.

in the numbers of incidents used.

RAIN was employed.

V"" Paul, Minnesota with 184 subjects and

The only difference in methodology was

In Minnesota, all descriptors except

As indicated in Figure G-4 the data points for Minnesota almost exactly

coincide those for College Station up to 60 percent diversion. Based on these

findings, the decision was made to replicate the study in Los Angeles using

only the descriptor, ACCIDENT. These data are also shown in Figure G-4.

Again, the diversion percentages are comparable up to the extremes when a

difference of a few subjects diverting would magnify the percentage values.

Table G-3 summarizes the data from the three studies in tabular form.

Note that for each of the three sets of data, the cross-over between a

majority diverting and a majority not diverting occurred between 15 and 20

minutes.

273

Figure G-5 and Table G-3 also summarize the data across regions. Figure

G-3 presents a composite, best estimate function for the effects of delay on

a diversion decision.

274

z 0 (/)

0::: w > 0

N ~ ....... 0 U'1

100

90

80

LOS ANGELES • - - - :- _-::------::-_,, (ACCIDENT ,. - ...'~ST PAUL

ONLY) I ,'/ ~4 DESCRIPTION) ! /•, COLLEGE STATION

J / (ALL DESCRIPTORS)

70 J ~: 7 COLLEGE STATION

/ (ACCIDENT DESCRIPTORS)

60

.50

40

30

20

10

0 10 20 30 40 50 60

DELAY IN MINUTES

Figure G-4 - Regional Differences in Diversion to Delay Durations

100

90

80

70

z 60 0 (/)

0::: 50 w > 0 40

'fl. 30

I

I I

20 I

I

10 I /' 0

,

10

I I I

I. I

I I

I /

?" /

,, .,

/ ,, ...-

__ .... .,-

I ALL STUDIES COMBINED ,, I I I I I

20 30 40 50 60

DELAY IN MINUTES

Figure G~5 - Effects of D~lav Ouration on Percent Diversion (all studies)

TABLE G-3

PERCENT DIVERTING TO DELAY MESSAGES IN THREE LOCATIONS

A~ California Study

DELAY STAY ON FREEWAY GET OFF FREEWAY PERIOD Number Percent Number Percent 5 Min. 40 100.0 0 o.o

10 Min. 36 90.0 4 10.0 15 Min. 26 65.0 14 35.0 20 Min. 11 27.5 29 72.5 30 Min. 2 5.0 38 95.0 1 Hr. l 2.5 39 97.5 2 Hr. 0 0.0 40 100.0

B. Minnesota Study -

DELAY STAY ON FREEWAY GET OFF FREEWAY PERIOD Number Percent Number Percent 5 Min. 173 94.0 11 6.0

10 Min. 155 85.2 27 14.8 15 Min. 126 67.0 62 33.0 20 Min. 66 35.7 119 64.3 30 Min. 25 14.6 146 85.4 1 Hr. 4 2.2 179 97 .8 2 Hr. 2 1.1 18l 98.9

c. College Station Study (Heavy & Light)

DELAY STAY ON FREEWAY GET OFF FREEWAY PERIOD Number Percent Number Percent 5 Min. 204 89.5 24 10.5

10 Min. 178 78. l 50 21.9 15 Min. 148 65.8 77 34.2 20 Min. 91 39.2 141 60.8 30 Min. 50 20.9 189 79.1 1 Hr. 18 7.7 217 92.3 2 Hr. 18 7.8 212 . 92.2

D. All Studies Combined

DELAY STAY ON FREEWAY GET OFF FREEWAY PERIOD Number Percent Number Percent 5 Min. 417 92.3 35 7.7

10 Min. 369 82.0 81 18.0 15 Min. 300 66.2 153 33.8 20 Min. 168 36.8 289 63.2 30 Min. 77 17 .1 373 82.9 1 Hr. 23 5.0 435 95.0 2 Hr. 20 4.4 433 95.6

276

Study 3 - Time Saved and Diversion

Objective

"Time Saved" is another way of expressing temporal information. The

experimental question was whether the same durations expressed in terms of

"time saved" would have a similar e.ffect.

Method

Since the local study indicated that the type of incident was not related

to a diversion decision, the number of incidents was reduced to ACCIDENT, ROAD­

WORK and TRUCK OVERTURNED. The severe weather incidents were less applicable

to this driving population, also.

Another difference was that the instructions specified only "heavy traffic."

The three incident-type messages were assigned to independent groups each

comprised on two sessions. Following the incident was the message: USE TEMPORARY

BYPASS TO THE ASTRODOME - SAVE x MINUTES. Again, the message cards were in

random order and instructions were to indicate whether or not they would divert

to the message. A total of 127 subjects participated in the study conducted .,/

in Los Anqclcs.

Rcsul ts

The findings of the "Time Saved" study in Los Angeles are summarized in

Table G-4 and Figures G-6 and G-7. As with the "delay" results, the type of

incident had little effect on the decision to divert (except that there were a

"hard core" group of five in the TRUCK OVERTURNED sample who refused to divert

regardless of the time saved duration).

277

N ........ CX>

TIME SAVED (MIN)

5

10

15

20

30

1 HOUR

2 HOURS

TABLE G-4

FREQUENCIES OF DIVERSION DECISION AS A FUNCTION OF INCIDENT TYPE AND TIME SAVED DURATION (LOS ANGELES)

TRUCK OVERTURNED (N=46 ACCIDENT (N=40) ROADWORK (N=41) TOTAL (N=127)

STAY ON % DIVERT % STAY ON % DIVERT % STAY ON % DIVERT % STAY ON % DIVERT

28 61 18 39 22 55 18 45 24 59 17 41 74 58 53

17 37 29 63 17 43 23 57 18 44 23 56 52 41 75

14 30 32 70 8 20 32 80 13 32 28 68 35 28 92

12 26 34 74 5 13 35 87 8 20 33 80 25 20 102

6 13 40 87 1 3 39 97 3 7 38 93 10 8 117

6 13 40 87 2 5 38 95 2 5 39 95 10 8 117

5 11 41 81 1 3 39 97 1 2 40 98 7 6 120

%

42

59

72

80

92

92

94

N '-I l.O

100

90

80

70

z 60 0 (/)

ex: 50 w > 0 40 ~ 0

30

20

10

• .,,,. .. ,,

ACCIOENT'i' 0,... -, / , ~TRUCK .. ,

OVERTURNED

0 10 20 30 40 50 60

TIME SAVED IN MINUTES

Figure G-6 - Effect of Incident Type and Time Savings on Percent Diversion*

* Based on data collected only in Los Angeles

100

, ..... -- - - ---90

/ /

/ 80 I

! 70 I

I I ALL INCIDENT TYPES z 60 • 0 I

(/) I ex: 50 I w > I 0 40 J ~ 0

30

20

10

0 10 20 30 40 50 60

TIME SAVED IN MINUTES

Figure G-7 - Summary of Percent Diversion to Time Savings

Another finding was that a savings of over 30 minutes resulted in a virtual

asymptote in numbers diverting. Therefore, the display of 30 minutes or 2 hours

would have no difference in effect on percentage diverting. In the local sample

only 1 and 2 hour delays were synonymous in diversion percentages (30 minutes

delay resulted in significantly fewer diverting).

A major finding was that the cross-over in time saved between a majority

of subjects staying and a majority diverting was somewhat lower than with

the delay studies. Note that for each sample, a 10 minute savings resulted

in about 60 percent diverting whereas with 5 minute savings, 40 percent

diverted. In the delay studi~s the cross-over was between 15 and 20 minutes.

The finding is illustrated more dramatically in Figure G-8 which presents the

composite curve for the delay studies in comparison with that for the time­

saved study.

However, before it can be concluded that the method of presenting the

temporal information was the primary contributor to the differences in

diversion it should be noted there was the one major methodological dif­

ference. In the time-saved study, a temporary bypass route was recommended

which may well have accounted for subjects diverting at a lower duration

of time whereas in the delay studies no alternate route was specifically

defined. For a more direct comparison, both groups should be given the

temporary bypass option with the avoidance of periods of delay being the

manipulated variable for one group and time saved, the variable for the

other.

280

100

90 CJ .... .... "' TIME SAVED /

(FIG _..........

G-7) / 80 IJ

I I

70 J ' I I

z 60 ri 0 I (/)

ct: 50 I w I >

CJ/ 0 40 I ~ 0

30

20

10

10 20 30 40 50 60.

TIME IN MINUTES

Figure G-8 - Comparison of Time Saved and Delay in Terms of Percent Diversion

281

Study 4 - Major and Minor Accidents and Delay

Objective

A related mini-study was conducted in Dall~ to determine the meaning

of two incident expressions, MAJOR ACCIDENT and MINOR ACCIDENT. While Study

2 had indicated no significant difference between ACCIDENT, RAIN, ROADWORK,

TRUCK OVERTURNED and ICE in terms of diversion decision, it was felt that

the adjectives, 11 major 11 anct 11minor 11, might well imply different levels of

severity and expected delay durations. By reference to the data in Tables G-2

and G-3, it would be feasible to infer also whether subjects would divert to

such a message.

Method

Forty subjects were administered the test with the adjective MAJOR and

twenty subjects with the adjective MINOR. They were told they were driving on

a freeway 1

in Dallas and they see a sign on the freeway which stated MAJOR (MINOR)

ACCIDENT -- nothing more. They were asked to indicate the delay they expected

by checking one of seven categories.

There was one important difference in the task for the major and minor

accident groups. The major group was asked to indicate the number of

minutes or more they felt the message implied whereas the minor group was

asked to indicate the number of minutes or less they felt was implied. Thus,

the median values reported have slightly different meanings. For the minor

group the value refers to the maximum delay they could conceive of whereas

for the major group the value given is the minimum delay i~plied by the

message.

282

The.results of the study are presented in Table G-5. The data cledrly

indicates that the median response, shown by arrow, corresponds to slightly

over 10 minutes delay for MINOR ACCIDENT and slightly over 20 minutes delay for

a MAJOR ACCIDENT. The data are shown graphically in Figure G-9.

The difference is the experimental tasks pose a question in inter­

pretation of the data. Had the subjects in both groups been asked for a

best estimate of the delay implied, the value would have been greater for

MAJOR ACCIDENT and less for MINOR ACCIDENT than that reported. Plotting

the data in the manner shown in Figure G-9 would imply the functions are

quite different.

/IEhaugh subjects were not asked in this study if they would divert to

the message itself, the findings of Study 2 with respect to delay tolerance

.indicate that a large proportion would divert to MAJOR ACCIDENT, but would not

divert to MINOR ACCIDENT.

283

TABLE G-5

DELAY DURATIONS ASSOCIATED WITH MAJOR AND MINOR ACCIDENTS

DELAY MAJOR ACCIDENT MINOR ACCIDENT

N % Cum % N % Cum %

5 Minutes 3 7.5 7.5 4 20 100

10 Minutes 3 7.5 15.0 5 25 80 .............

15 Minutes 5 12.5 27.0 3 15 55

20 Minutes 6 15. 0 - 42.5 7 35 40 -30 Minutes 16 40.0 82.5 0 0 0

1 Hour 5 12. 5 95.0 1 5 5

2 Hours 2 5.0 100.0 0 0 0

Total 40 100 20 100

......C = Median delay associated with incident message.

284

t­z w u 0:: w a..

w > t== C( ...J ::> 2 ::> u

100

40 50 ANT IC I PATED DELAY (MINUTES)

Figure G-9 - Maximum delay durations implied by a Minor Accident Message and minimum delay durations implied by a Major Accident Message for various percentages of subjects

285

Study 5 - Meaning of Delay

Objective

Subjects• responses in Study 1 suggested that even when they express a

desire for Delay information, the kinds of questions they expect to answer

from this information are often different. Therefore, should a s~gn display

DELAY :- x MINUTES motorists may interpret the message quite differently.

A questionnaire study was conducted in Los Ange{e's to determine which of

five possible interpretations of a 30 minute delay message the subjects felt

most strongly that the message meant. Also, of interest was the degree to

which subjects could not decide among the interpretations, suggesting ambiguity

of meaning.

Method

Forty-one subjects were administered the questionnaire in two groups in

separate sessions with a different random order of the alternate meanings in

session 1 and session 2. Figure G-10 presents the questions in order 1 and

Figure G-11 presents the questions in order 2.

The subjects task was to check on a Likert-type scale the extent to which

he agreed or disagreed with the interpretation of delay given. The five cate-

gory scale ranged from 11 strongly agree 11 to 11 strongly disagree 11 with 11 undecided 11

the middle category.

As shown in Figures G-10 and G-11 the five interpretations may be para­

phrased as follows:

1. Arrive at work 30 minutes later than usual

2. 30 minutes before accident is removed

286

FIGURE G-10 - QUESTIONNAIRE FOR DELAY MEANING (ORDER 1)

Suppose you are approaching a freeway on your way to work. You are told that there is an accident on the freeway and to expect a 30 minute delay.

1. To me, this means that I will be completely stopped in traffic on the freeway for 30 minutes.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

2. To me, this means that my travel on the freeway will be 30 minutes longer than usual. /

Strongly Agree Agree Undecided Disagree

Strongly Disagree

3. To me, this means that I will have to travel in bumper-to-bumper traffic on the freeway for 30 minutes.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

4. To me, this means that it will be 30 minutes before the accident is removed from the freeway.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

5. To me, this means that I will arrive at work 30 minutes later than usual.

Strongly Agree Agree Undecided

287

Disagree Strongly Disagree

FIGURE G-11 - QUESTIONNAIRE FOR DELAY MEANING (ORDER 2)

Suppose you are approaching a freeway on your way to work. You are told that there is an accident on the freeway and to expect a 30 minute delay.

1. To me, this means that I will arrive at work 30 minutes later than usual.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

2. To me, this means that it will be 30 minutes before the accident is removed from the freeway.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

3. To me, this means that I will have to travel in bumper-to-bumper traffic on the freeway for 30 minutes.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

4. To me, this means that my travel on the freeway will be 30 minutes longer than usual.

Strongly Agree Agree Undecided Disagree

Strongly Disagree

5. To me, this means that I will be completely stopped in traffic on the freeway for 30 minutes.

Strongly Strongly Agree Agree Undecided Disagree Disagree L~~~__.__~~_._~~---''--~~--

288

3. Travel 30 minutes in bumper-to-bumper traffic

4. Freeway travel will be 30 minutes longer than usual

5. Completely stopped in traffic for 30 minutes. I

Subjects were assigned a score of 11 111 for "strongly agree 11 with the

statement and a score of 11 511 for "strongly disagree" .. Therefore, the smaller

the score (or average score), the greater the agreement with the statement.

The strongest agreement would be a total of 40 and the strongest disagreement

would be 200.

A subject could choose to indicate the same degree of agreement with two

or more meaning statements. Failure to discriminate meanings would be an indi­

cation of the ambiguity of the statements.

Results and Discussion

The results of the Los Angeles study are presented in Table G-6. The

most popular interpretations were: 1) that freeway travel will be 30 minutes

longer than usual and 2) that he will arrive at work 30 minutes later than

usual (both have essentially the same meaning).

The mean rating of 2.2 for the first interpretation was made up of

9 subjects strongly agreeing and 20 subjects agreeing with the meaning.

Only 3 subjects disagreed, none strongly. The other 9 were undecided.

A test of significance indicated the differences were statistically

significant at the .05 level (F4, 156 = 5.59). Although significantly

different, the pattern of responses did not reflect strong disagreement

with any of the interpretations.

Five of the 41 subjects marked all categories with the same rating.

Nine subjects marked all but one category the same.

N> \0 0

( 1 ) Work Arrival Later than Usual

:E:R 95

TABLE G-6

TOTAL RATINGS AND MEAN RATING OF FIVE MEANINGS OF DELAY (N=41)

(2) (3) (4) (5) . Accident Bumper-to- Fwy Travel Stopped in

Removed Bumper Traf- longer than Traffic fie Usual

119 114 88 125

R 2.375 2.975 2.85 2.2 3.125

::ER= Sum of rating scores

R = Average rating

Total

541

2.7

Study 6 - Modes of Presenting Temporal Information

Objective

In addition to a statement of delay time, at least two other alternative

modes of expressing temporal information exists when there is an alternate

route also under traffic control and surveillance.

Study 6 was a preference study of the three modes of presenting temporal

information: 1) avoiding a 15 minute delay by taking a bypass; 2) saving

15 minutes (driving) time by taking a bypass; 3) again, saving 15 minutes

or avoiding 15 minutes delay as shown by travel times of 25 minutes on the

freeway and 10 minutes on the bypass.

Method

Two identical surveys were conducted at a local shopping mall. The first

had a sample of 18; the second, 52. Subjects were told they were traveling on

a freeway in heavy congestion during rush hours. A lighted sign flashed on

advising them or congestion and telling them to get off and take a temporary

bypass. The bypass would rejoin the freeway at White Bear Avenue, which was

beyond the congested area.

The subjects were told this information would appear on the sign and,

in addition, the sign woulq give them 11 an advantage 11 to taking the bypass.

They were told three different messages would appear on 3 cards, each giving

an advantage to leaving the freeway. Their task was to read each sign message

carefully and answer a set of seven questions as follows:

(1) Check the message most likely to convince you to get off the freeway.

(2) Give a reason you preferred the message.

291

(3) Check the message least likely to convince you to get off.

(4) Give a reason you disliked it.

(5) Do you feel the three messages are telling you the same thing,

but in a different way? (Yes/No)

(6) If the answer was 11 no 11 to question 5, tell which message was

different from the other two.

(7) In what way was it different?

The three cards were shuffled so that the order of appearance of messages

was randomized across subjects. In addition, the answer sheet for questions

No. l and No. 3 had the three alternative messages in a counterbalanced order,

so that each message appeared with equal frequency in each serial position.

Results

The results of the study are presented in Table G-7. The findings fail

to support a strong preference for any one of the three modes. The 11 Avoid

Delay 11 message was preferred by 38.6 percent, the others approximately 30

percent each.

Although preferences were divided, a majority of the subjects were in

agreement as to the message that would least likely get them to divert. Com­

parative travel time was th~ least preferred by 56.9 percent of those answering.

The reasons given for messages being preferred were classified by: 1) com-' I

pleteness, 2) giving time saved directly or indirectly, and 3) other messages

giving too much information. However, these reasons were given to varying

degrees as reasons for preferring each alternative.

The major reason for not liking comparative travel time was it took

longer to read. Twenty three of the 52 subjects offered this reason while

12 subjects reported the message was confusing.

292

N '.£)

w

TAGLE G-7

FREQUENCY OF SELECTING ALTERNATIVE WAYS OF DEPICTING TEMPORAL INFORMATION SURVEY 1 (N=18); SURVEY 2 (N=52)

Congestion Ahead Congestion Ahead Congestion Ahead Use Temporary Bypass Use Temporary Bypass Use Temporary Bypass To White Bear Avenue To White Bear Avenue To White Bear Avenue No Avoid 15 Minute Delay Save 15 Minutes Travel Time Answer

' 1-94 25 Minutes Temp.Bypass 10 Minutes

QUESTIONS SURVEY SURVEY SURVEY SURVEY % 1 2 TOTAL % 1 2 TOTAL % l 2 TOTAL 1 2

1. What rressage would most likely convince you to get off the 38.6 6 21 27 30.0 4 17 21 31.4 8 14 22 0 0 freeway?

2. Reason: a) Message more complex 1 9 10 1 2 3 2 6 8 b) Specifies time saved 2 7 9 3 5 9 5 4 9 c) Other conditions con-

tain too much infer- 2 5 7 0 9 9 1 4 5 l 0 mat ion

3. What rressage would least likely convince you to get off the 17.0 2 9 11 26. 1 6 11 17 56.9 7 30 37 3 2 freeway?

4. Reason: a) Sign is too confusing 0 3 3 2 5 7 3 9 12 b) Not enough information l 2 3 1 2 3 3 0 3 c) Takes longer to read 0 2 2 0 0 0 3 20 23 3 1 d) Wording sounds

erroneous 0 2 2 3 3 6 0 1 l 5. Do the three messages say the same

thing? (1) YES=l6, NO=l, No Answer =l (2) YES=46, N0=5, No Answer=l

6. If No, check the message that is different N = 2 N = 2 N = 2

(1) Negative Connota- (1) Does not give act- ( 1) Gives travel time 7. In what way is this message ti on ual travel time

different? (2) Delay avoided 1' (2) Could be shorter (2) Presents choice time saved route regardless rather than giving

of congestion directions status

Sixty-two (89 percent) of all respondents felt the messages said the same

thing in a different way. Six subjects stated one message was different from

the other two and two subjects did not answer. Table G-7 presents the ways in

which the few subjects felt particular messages differed from others.

In summary, the two surveys failed to indicate there was a strong

preference for any one of the three modes of depicting temporal information

and, in fact, approximately 9 out of 10 drivers surveyed felt the modes

had displayed the same message in a different way. However, a majority

of the subjects liked comparative travel time the least primarily because

the message took longer ta reao and was confusing to some.

294

Summary and Conclusions

1. Approximately one subject in five asked for temporal information given

that he was in a time-critical situation and given that there was an

accident and no opportunity to exit the freeway. However, 30% continued

to ask for advisory information suggesting the need to be told what to

do takes priority. The results of audio studies reported in Volume

12 also suggest that temporal information is recalled less well than

is the problem and the action the driver shoulrl take.

2. Given that delay information is presented along with type of incident

and level of congestion drivers seemed to respond more to the duration

of delay in making a decision to divert. Three studies in different

geographical regions indicate that the median subject will divert to

a delay message of between 15 and 20 minutes. The drivers responded

in differing proportions to six levels of delay but indicated 1 and

2 hours delay were synonymous.

3. There is some evidence that expressing temporal information in terms

of time saved may result in diversion at from 5 to 10 minutes. However,

this conclusion applies when a temporary bypass route is given in the

ad vi s·ory message.

4. Dallas drivers indicateq MINOR ACCIDENT meant 12 minutes delay or less

whereas MAJOR ACCIDENT meant 22 minutes delay or more. However, there

was considerable variability in interpretation.

5. A delay of X minutes was referenced to the driver's normal travel time,

i.e., it meant more often that the travel time on the freeway would be

that much longer than usual or that they would arrive at work that much

later. Delay information did not necessarily imply stopped traffic

295

or bumper-to-bumper traffic nor did they think that the accident

itself would necessarily be on the freeway for the indicated period.

6. Three:modes of presenting temporal information were viewed as essentially

synonymous and no strong preferences were indicated. However, comparative

travel time was disliked more often because the message required more time

to read and was somewhat confusing. Essentially, the driver must subtract

one value from the other to obtain the benefits of taking an alternate

route.

Design Recommendations

1. Temporal information may be displayed on a CMS or presented by other

means as an amplification of the meaning of an incident or congestion.

2. When pnly two messages may be presented the messages should be the !

problem {accident, congestion) and the advisory {where to exit or what

action to take).

3. Temporal information, in terms of delay, has been found to be an effective

method for traffic control to induce various proportions of traffic to

divert. Five or six levels may be employed. In the larger cities dis­

play of over 30 minutes delay is not effective in inducing more diversion.

The recommended levels qf delay are as follows:

(a) 5 minutes = 10 percent diversion

{b) 10 minutes = 20 percent diversion

{c) 15 minutes = 40 percent diversion

(d) 20 minutes = 60 percent diversion

{e) 30 minutes - ao percent diversion

{f) l hour = 95 percent diversion.

296

The traffic engineer may select from 1 to 6 levels for display depending

upon his objectives. Increasing the delay period beyond one hour will

not insure complete diversion.

4. Under the conditions of research, there was no indication that five

types of incidents investigated resulted in differences in the pro­

portion diverting over and above that reported for the delay duration

alone. However, do not expect complete diversion regardless of the

delay period. Some drivers may question the credibility of taking an

alternate route to RAIN incident messages and may question long delay

messages when they are currently driving in light traffic conditions.

5. Temporal information, in terms of time saved, may be displayed provided

an advisory to an alternate route is given. Under these conditions median

diversion will occur between 5 and 10 minutes and 92 percent diversion

with 30 minutes savings.

6. There are some indications that drivers interpret mild and severe accidents

differently in terms of the delay implied. The message, MAJOR ACCIDENT

meant at least 22 minutes delay to a typical driver and data from Study

2 indicate that 20 minutes delay may result in at least 60 percent

diversion. The message, M~NOR ACCIDENT meant 12 minutes of delay or less

which was associated with only 20 to 25 percent diversion. Generalizing

from the Study 2 data one may assume that traffic may well divert in

different proportions to the two messages.

7. Drivers interpret a delay message as relative to the normal travel time

required to transverse the freeway or arrive at their destination. There­

fore, a delay m~ssage should not be used unless there is evidence from

traffic control that t.he "average driver" will be delayed the indicated

297

duration. The validity may easily be checked by reference to a watch

or clock, and major deviations may weaken themessage•s credibility.

8. Temporal messages should be brief and should be used only when the

traffic is advised to take an alternate route. The delay is a plausible

incentive for diverting. The messages may be in several formats:

I.

(a) Problem, e.g. Accident

(b) X Minute Delay

(c) Advisory to divert

(Delay here is an effect associated with the problem on the primary

facility)

I I.

(a) Problem

(b) Advisory to divert

(c) Avoid X minute delay

(If 11 avoid 11 is used the message should appear after the advisory since

it applies to the alternate route}

III.

(a) Problem

(b) Advisory to divert

(c) Save X minutes

(Again, "Saving time" shpuld appear after the advisory since the time

savings are with reference to the alternate route}.

A problem with the Formats II and III is that many advisories require

two 11nes. If a displayed message consisted of two exposures of two-line

messages, and if the 11 savings 11 message filled the last of the four lines,

298

then the two-line advisory would be displayed with one line at the bottom

of the first exposure and the next line at the top of the second exposure.

Breaking up an advisory message in this manner would make it less meaning­

ful.

Another problem with Format II is that AVOID xx MIN. DELAY will

require two lines on matrix signs, less than 18 characters long. If the

total message were restricted to 4 lines and the problem requires one

line this would limit the advisory to one line and leave insufficient

space for the destination. (Example is ACCIDENT AHEAD/USE FITZHUGH/AVOID

30 MIN/DELAY. )

These limitations make Format I the preferred message when space is

at a premium on a matrix sign. For rotating drums and audio messages,

Formats II and III are equally effective.

299

1.

2.

3.

4.

5.

REFERENCES

Heathington, K.W., Worrall, R.D., and Hoff, G.C. 11 An Analysis of Driver Preferences for Alternative Visual Infonnation Displays. 11 Highway Research Record 303, pp. 1-16, 1970.

Case, H.W., Hulbert, S.F., and Beers, J. 11 Research Development for Changeable Messages for Freeway Traffic Control. 11 University of California, Los Angeles, UCLA-ENG-7155, Aug. 1971.

Dudek, C.L. and Jones, H.B. 11 Real-Time Information Needs for Urban Freeway Drivers. 11 Texas Transportation Institute, Texas A&M University, Research Report 139-3, August 1970.

Gordon, D. 11 Design of a Diversion Sign - Baltimore Point Diversion Study. 11 Draft report, Traffic Systems Division, Federal Highway Administration, undated.

Dudek, C.L. Human Factors Requirements For Real-Time Motorist Infor­mation Displays. Vol. 2, 11 State of the Art: Messages and Displays in Freeway Corridors. 11 Final Report, Texas Transportation Institute, February 1978.

300

APPENDIX A

QUALITY CONTROL PROCEDURES

In order to insure that the objectives of the Task B laboratory experi­ments are accomplished, the following procedures for implementing the experi­ments will be adopted:

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

Study Teams review Conceptual Experiments and develop design strat­egies.

A Conceptual Design meeting will be held to clarify any misunder­standing regarding the objectives and scope of the experiments. The PI and CO-PI will be present.

Study Teams will design experiments in detail including independent variables (e.g., messages), measures, research strategy, instructions to subjects, and type of data analysis planned.

Detail Design is approved by PI or CO-PI. To expedite approval, it would be desirable to send a copy to the PI and CO-PI before any discuss ion.

Slide Coordinator is contacted by Study Leader. Study Leader may wish to review artwork before it is sent to photography.

Mediamaster is programmed; instructions are taped; and laboratory is set up. Upon receipt of slides, all final preparations are made by the mediamaster team.

Ordinarily, 48-hours before the beginning of the next scheduled block, there will be a dress rehearsal (dry run) in which the PI and CO-PI will review the experiments from a subject's standpoint. Ordinarily, changes recommended will be minor at this point in time.

On Monday of each week following the first week of run, the Laboratory Coordinator or his alternate will notify the PI or CO-PI as to the number of subjects run, number of cancellations, and any problems in meeting the test schedule. The Subject Coordinator will provide all subjects and will be contacted directly if substitutes are necessary.

When an experiment in the next block is dependent upon the results of an experiment in progress, the data must be analyzed immediately after data run (in some cases, it may be tallied during this run period).

When a major decision must be made on which content items will be included in an upco~ing experiment, the PI and CO-PI should be noti­fied of the results of the study as soon as possible. In addition. any experiment which appears to be taking too long or which is not

301

yielding usable data should be brought to the attention of the PI or CO-PI.

11. As soon as the data has been analyzed, the results and discussion as applicable should be forwarded to the PI and CO-PI.

302

Age Groups

18-24 25-34 35-44 45-54 55-64 Over 64

Total

18-24 25-34 35-44 45-54 55-64 Over 64

Total

GRAND TOTAL

APPENDIX B

APPENDIX TABLE B-1 PERCENT OF PERSONS 18 YEARS OF AGE AND OLDER

COMPLETING EDUCATION LEVEL SHOWN (URBAN AND RURAL)*

MALES

Elementary High School College

1-3 4 1-3 4 or more

3 5 3 2 1 1 1 3 1 2 1 1 2 1 1 2 2 2 1 1 2 1 1 1 1 3 1 1 0 0

Males 12 11 12 6 6

FEMALES

3 5 4 2 0 I

1 2 4 1 1 1 2 3 1 1 2 2 3 1 1 2 1 2 1 0

4 1 1 1 0

Females 13 13 17 7 3

25 24 29 13 9 ·-

Totals

14 8 6 8 6 5

47

14 9 8 9 6 7

53

100

* Adopted from United States Statistical Abstract, U. S. Bureau of the Census, Washington, D. C., U.S. Printing Office, 1971

303

Age Groups

18-24 25-34 35-44 45-54 55-64 Over 64

Total

18-24 25-34 35-44 45-54 55-64 Over 64

Total

GRAND TOTAL

APPENDIX TABLE B-2 PERCENT OF PERSONS 18 YEARS OF AGE AND OLDER

COMPLETING EDUCATION LEVEL SHOWN (URBAN)*

MALES

.Elementary High School College

1-3 4 1-3 4 or more

3 5 3 2 1 1 1 3 1 2

1 1 2 1 1 2 2 2 1 1 2 1 1 1 1 3 1 1 0 0

Males 12 11 12 6 6

FEMALES

2 5 4 2 1 1 2 4 1 1 1 2 3 1 1 2 2 3 1 1 2 1 2 1 0

4 1 1 1 0

Females 12 13 17 7 4

24 24 29 13 10

Totals

14 8 6 8 6 5

47

14 9

8 9

6 7

53

100

*Adopted from United States Statistical Abstract, U. S. Bureau of the Census, Washington, D. C., 0. S. Printing Office, 1971.

304

w 0 <.Tl

APPENDIX TABLE B-3 SUBJECT DEMOGRAPHIC DATA

TOPIC AREA A - MINIMUM TRAFFIC STATE MINIMUM INFORMATION REQUIREMENTS Study N location

Study 1 - Information Requested by the Unfamiliar Driver (Severe Traffic Problem) College Station 112

Study 2 - Effect'of Driver Familiarity • Familiar (Severe Traffic Problem) Houston 51 • Unfamiliar (Severe Traffic Problem) Houston 43

Study 3 - Effect of Traffic Problem Severity • Unfamiliar (Severe Traffic Problem) Houston 43 • Unfamiliar (Minor Traffic Problem) Houston . 41

*N.A. = Data Not Available

Average Average Sex Distribution Age Education

Level % No Range Completed % Female % Male Response

25-34 N.A.* 46 54 0

25-34 N.A. 37 53 10 25 .. 34 N.A. 37 54 9

25-34 N.A. 56 44 0

25-34 N.A. 56 44 0

w 0 O'I

APPENDIX TABLE B-3 (Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA B - TRAFFIC STATE DESCRIPTORS Study N Location

Study 1 - Number of Discriminable Traffic States College Station 89 Houston 60

Study 2 - Descr1ptors for Extreme States College Station 89

Study 3 .. Verbal Uescriptors of Level of Service College Station 60 Houston 43

-Total 103

Study 4 - Verbal Descriptors of Level of Service -Follow-up

• Slide 1 College Station 52 Houston 34

St. Paul 62 Los Angeles 44

-Total 192

• Slide 2 College Station 41 Houston 27 St. Paul 25

Los Angeles 37 -

Total 130

Average Age

Range

N.A. 25-34

25-34

25-34 25-34 --25-34

25-34 25-34 25-34 25-34 --25-34

25-34 35-44 25-34 25-34 --25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

N.A. N.A. N.A. N.A. 13 38 62 0

13 49 51 0

14 50 50 0 14 43 57 0 -- -- -- --

14 47 53 0

12 35 65 0 14 37 53 0 13 56 42 2 13 39 52 9 -- -- -- --13 43 54 3

13 50 50 0 14 46 54 0

13 33 63 4 14 43 46 11 -- -- -- --

13 44 52 4

APPENDIX TABLE B-3 (Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA B - TRAFFIC STATE DESCRIPTORS (CONTINUED) Study N Location

• Slide 3 Co 11 ege Station 58 Houston 48 St. Paul 55

' Los Angeles 55

-Total 216

Average Age

Range

25-34 25-34 25-34 25-34 --· 25_.34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

13 39 61 0 13 50 50 0 14 55 45 0 13 47 34 19 -- -- --

13 47 48 5

w 0 (X)

APPENDIX TABLE B-1 (Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA C - TRAFFIC STATE CODING Study N Location

Study 1 - Preliminary Screening of Traffic State Coding Methods

. "Traffic" College Station 46 Houston 56

-Total 102

• "Congestion" College Station 42 Houston 60

-Total 102

Study 2 - Traffic State Coding Methods • Sign Design 1 --- 46 • Sign Design 2 --- 45 • Sign Design 3 --- 45 • Sign Design 4 --- 45 • Sign Design 5 --- 51 • Sign Design 6 --- 85 • Sign Design 7 --- 39

Average Age

Range

25-34 25-34 --25-~4

25-34.

25-34 --25-34

25-34 25-34 25-34 25-34 25-34 25-34 25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

10 28 72 0 13 41 59 0 -- -- -- --

12 35 65 0

12 52 48 0 14 38 62 0 -- -- -- --

13 44 56 0

13 42 58 0 13 44 47 9

14 49 51 0 13 40 56 4 13 41 53 6 13 49 39 12 13 54 46 0

w 0 \.0

APPENDIX TABLE B-3 {Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA D - LOCATION AND LENGTH OF CONGESTION Study N Location

Study 1 - Descriptors for Congestion Location -Non-Cormluters

• Condition A-1, B-1 College· Station 39 • Condit1on A-2, B-2 College Station 37

Study 2 - Descriptors for Congestion Location -· Commuters

• Section 1 Questionnaire Los Angeles 39 • Section 2 Questionnaire (Cross Street

First) Los Angeles 44 • Section 2 Questionnaire (Distance First) Los Angeles 39

Average Age

Range

25-34 25-34

25-34

25-34 25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

13 45 30 25 13 30 49 21

13 47 53 0

13 39 52 9

13 43 45 12

APPENDIX TABLE B-3 (Cont.)

·SUBJECT DEMOGRAPHIC DATA

TOPIC AREA E - LANE BLOCKAGE <CLOSURE> AND AVAILABILITY DESCRIPTORS Study N Location

Study 1 - Verbal and Coding Methods - Understanding of and Preferences for Messages

• Part 1- College Station 70 • Part 2 College Station 79 • Part 3 College Station 79 • Part 4 College Station 79

Study 2 - Verbal and Coding Methods - Understandin of Signs College Station 79

Study 3 - Verbal and Coding Methods - Follow-up • Sign Design 1 --- 40 • Sign Design 2 --- 46 • Sign Design 3 --- 46 • Sign Design 4 --- 46 • Sign Design 5 --- 37 • Sign Design 6 --- 47 • Sign Design 7 --- 39 • Sign Design 8 --- 39 • Sign Design 9 --- 38 • Sign Design 10 --- 52 • Sign Design 11 --- 51

Average Age

Range

25-34 25-34 25-34 25-34

25-34

25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

13 47 53 0 13 41 54 5 13 41 54 5 13 41 54 5

13 41 54 5

13 57 43 0 13 51 49 0 13 43 46 11 14 49 51 0 13 51 46 3 13 39 55 6 13 50 44 6 14 49 51 0 14 37 55 8 13 42 55 3 13 55 45 0

w ...... ......

APPENDIX TABLE B-3 {Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA E - LANE BLOCKAGE <CLOSURE> AND AVAILABILITY DESCRIPTORS Study N Location (CONTINUED)

Study 4 - Driver Interpretation of "Blocked" Versus "Closed" Messages

• Phase 1 (Closed) Los Angeles 43 • Phase l {Blocked) Los Angeles "76

Average Average Sex Distribution Age Education

Level % No Range Completed % Female % Male Response

25-34 13 47 40 13 .25-34 13 49 46 5

w ...... N

TOPIC AREA F - INCIDENT TYPES

Study 1 - Categorization of Verbal

.

APPENDIX TABLE B-3 (Cont.) SUBJECT DEMOGRAPHIC DATA

Study N Location

Messages College Station 61 Houston 36

-Total 97

Study 2 - Prfority of lncident Infonnation • Peak College Station 30 • Off-Peak College Station 40

-Total 70

Average Age

Range

25-34 35-44 --25-34

25-34 25-34 --25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

14 52 44 4 14 32 68 0 -- - -- --

14 45 54 1

12 53 47 0 12 40 60 0 -- -- -- --

12 48 52 0

APPENDIX TABLE B-3 (Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA G A TEMPORAL INFORMATION - -· PREFERENCES IN RELATION TO OTHER Study INFORMATION ON A CHANGEABLE MESSAGE Location N

~TfiN

. Peak Condition College Station 37

. Off-Peak Condition College Station 37

'

Average Average Sex Distribution Education Age Level % No Range Completed % Female % Male Response

25-34 12 56 44 0

25-34 12 42 58 0

APPENDIX TABLE B-3 (Cont.) .SUBJECT DEMOGRAPHIC DATA

TOPIC AREA G - TEMPORAL INFORMATION Study N Location

Study 1 - Expressed Need for Temporal Information Houston 133

Study 2 - Delay.Duration and Diversion • Accident (Heavy Conditions) College Station 45 • Rain (Heavy Conditions) College Station 14 • Roadwork (Heavy Conditions) College Station 22 • Truck Overturned (Heavy Conditions) College Station 22 • Ice (Heavy Conditions) College Station 12

-Total 115

• Accident (Light Conditions) College Station 42 ·Rain (Light Conditions)· College Station 9 • Roadwork (Light Conditions) College Station 20 • Truck Overturned (Light Conditions) College Station 28 • Ice (Light Conditions) College Station 25

-Total 124

• Accident (Heavy Conditions) St. Paul 39 • Roadwork (Heavy Conditions) St. Paul 54 • Truck Overturned (Heavy Conditions) St. Paul 41 • Ice (Heavy Conditions) St. Paul 50

-184

Average Age

Range

N.A.

25-34. 35-44 25-34 25-34 35-44 --25-34

25-34 25-34 25-34 25-34 35-44 --25-34

25-34 25-34 25-34 25-34 --25-34

Average Sex Distribution Education

Level % No Completed % Female % Male Response

N.A. N.A. N.A. N.A.

12 49 51 0 12 50 50 0 11 45 55 0 12 45 55 0 12 42 58 0 -- -- -- --

12 47 53 0

12 48 52 0 14 44 56 0 13 50 50 0 12 32 68 0

12 30 70 0 -- -- -- --

12 40 60 0

12 64 36 0 13 54 46 0 14 44 54 2 14 52 48 0 -- -- -- --

13 53 46 1

APPENDIX TABLE B-3 (Cont.) SUBJECT DEMOGRAPHIC DATA

TOPIC AREA G - TEMPORAL INFORMATION Study Average .N Age

(CONTINUED) Location Range

• Accident (Heavy Conditions) Los Angeles 40 25-34

Study 3 - Time S~ved and Diversion • Accident (Heavy Conditions) Los Angeles 40 25-34 • Roadwork (Heavy Conditions) Los Angeles 41 25-34 • Truck Overturned (Heavy Conditions) Los Angeles 46 25-34

- --Total 127 25-34

Study 4 - Major and Minor Accidents and Delay • Major Dallas 40 N.A. • Minor Dallas 20 N.A.

Study 5 - Meaning of Delay • Order 1 Los Angeles 21 25-34 • Order 2 Los Angeles 20 25-34

- --Total 41 25-34

Study 6 - Modes of Presenting Temporal lnfonnation • Survey 1 College Station 18 N.A. • Survey 2 College Station 52 N.A.

- --Total 70 N.A.

Average Sex Distribution Education

Level % No Completed % Female % Male Response

13 50 50 0

13 43 45 12 13 45 45 10 14 48 52 0 -- -- -- --

13 45 49 7

N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A.

12 43 40 17 14 33 67 0 -- -- -- --

13 39 52 9

N.A. 43 57 0 N.A. 54 46 0 -- -- -- --

N.A. 52 48 0

6 6

I I

Questions Regarding

Lane Blockage

4

e 7

24 50%

I

4 1

14

@> 3

APPENDIX C

I

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10 21~

l)uestions Regarding

De I a Status

APPENDIX FIGURE C-1

\ I

@ @ 1 "

"INCIDENT FIRST" CATEGORY INFORMATION FLOW

I I

ee 1 3

N=64 N=28 (44•)

Questions Regarding

ane Blockage

10

I e 11

15

@ 4

1

Speed Status Due to

Blocked Lanes l

4

N=ll (17~.)

Questions Regarding

Congestion Status

4

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8 4

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® 2

N=9 (14t)

Questions Regarding

Delay Status

I I

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Congestion Information

Exit -Incident

nfonnation 2

I I

® "

I I

e 4

APPENDIX FIGURE C-2

RANDOM CATEGORY IlffORMATION FLOW

N=2 (3%) N=5 (8%) N=3 ( 5~;) Ques ti ans Questions Regarding Regarding Location Exit

of Incident Information

I I I I I I

® e e 1 6 1

w -co

\

Questions Regarding

Lane Blockage

~ 2

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11 58%

3

Questions Regarding

Congestion Status

I I e 2

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APPENDIX FIGURE C-3

INCIDENT FIRST CATEGORY INFORMATION FLOW - (Houston - Familiar)

I I I ee 3 1

N"32 N~7 (22%)

I

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2

@ 0

Speed Status Due to

Blocked Lanes 0

I I

N"9 (28~)

2

I

N=6 (19n Questi ans Regarding

Qelay

I I

Congestion Information

xit-Inciden Information

I

N=2 (6~)

Questions Regarding

Speed Status

8 dv e dv I! 2 0

APPENDIX FIGURE C-4

RANDOM CATEGORY INFORMATIOU FL0\4 (Houston - Familiar)

N=J ( 3';) N=3 (9%) N=4 (13~)

Questions Questions Questions Regarding Regarding Regarding Location Exit Other

of Incident Jnformat ion Interest Factors

I I

9 e 6

w N 0

N=24

8

\ \

Questions Regarding

Lane Blockage

2 2

e 3

I

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ch 2

4%

Questions Regarding

Congestion Status

I

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4%

Questions Regarding

Delay Statu

\ ee 1 ,,

APPENDIX FIGURE C-5

I I

INCIDENT FIRST CATEGORY INFORMATION FLOW (Houston - Unfamiliar)

I I

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w N I-'

N=19 N=4 21-.: Quest1 ons Regarding

Lane Blocka e

I

9 1

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Speed Status Due to

Blocked Lanes I

N=7 37~

Questions Regarding

Congestion Status

I I e 5

I

@ 1

N=l 15':'' Questions Regarding

Delay Status

I I

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Confounding Factors

2

Congestion Information

Exit Incident

Info 2

I I

e APPENDIX FIGURE C-6

RANDOM CATEGORY INFORMATION FLOW (Houston - Unfamiliar)

N=2 11% N=3 16% N=2 (11%

Quest ions Questions Questi ans Regarding Regarding Regarding Location of Exit Other Incident Information Interest

Factors

I I I

@ e 4 3

14 0

Questions Regarding

Lane Blockage

e 1

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3 { \Q·,)

2 0

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e e I

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APPENDIX FIGURE c~7 INCIDENT FIRST CATEGORY INFORMATION FLOW

{Severe Problem)

I I

88

w N w

N=l2 N=4 (33o) f)ues ti ons Regarding

Lane Blocka e

Speed Status Due to

Blocked Lanes

Incident Status

Congestion

I e 2

N=J (2S~

Questi ans Regarding

Conges~ion

Status

0 uest1ons

Regarding Delay

Confounding Factors

Congestion Information

Exit Incident

Info,

0 0 f Quest i or.s ~st ions

ReS~~~~ng 1 Regarding

Locat1 on of tat us Incident

Congestion.,._-~!

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Other Info

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APPENDIX FIGURE C-8

RANDOM CATEGORY INFORMATION FLOW (Severe Problem)

1

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Questions Regarding Exit Info

I I e 0

N=3 (25~)

2

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Questions Regarding

lane Blockage

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3 (20%) (7%)

Return Related to

Dela * Exit I

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APPENDIX FIGURE C-9

INCIDENT FIRST CATEGORY INFORMJ\TION FLOW (L1 qht Prohl em)

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N=26 N=6 23%

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I 2

@ 2

N=3 12'.'f N=S 19': N=2 (8~,)

Questions Questions Questions Regarding Regarding Regarding

Congestion Delay Status Speed Status Status

Congestion

I I I I

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I I I I I l e ~ e e e e

1 I! 1 1 2 1

APPENDIX FIGURE C-10 RANDOM CATEGORY INFORMATION FLOW

(Light Problem)

N=5 197, N=l 4% N=4 {15%) Questions Questions Questions Regarding Regarding Regarding Location Exit Other

of Incident Information Interest Factors

!Dciden Status

3

Location

I I I

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w N m

Descriptor

APPENDIX D

APPENDIX TABLE 0-1 PERCENTAGE ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

COLL:GE STATION ·---..-

Slide l Slide 2

Better Same Worse N Better Same Worse N Better

LIGHT CONGESTION 42 35 23 52 66 34 0 41 88 MODERATE CONGESTION 17 39 44 52 34 56 10 41 57 HEAVY CONGESTION 0 0 100 52 0 20 80 41 2 UNCONGESTED 63 29 8 52 76 17 7 41 87 CONGESTED 2 8 90 52 15 56 29 41 17 VERY CONGESTED 6 6 88 52 4 20 76 41 3 LIGHT TRAFFIC 90 8 2 52 83 15 2 41 93 MODERATE TRAFFIC 19 62 19. 52 68 29 3 41 76 HEAVY TRAFFIC 0 4 96 52 0 49 51 41 3 FREE FLOWING TRAFFIC 58 39 3 52 86 12 2 41 90 STOP-AND-GO TRAFFIC 10 5 85 52 5 32 63 41 16 JAMMED TRAFFIC 0 0 100 52 3 7 90 41 5

Slide 3

Same Worse N

9 3 58 3E 7 58 45 53 58 10 3 58 64 19 58 41 55 58 2 5 58

22 2 58 71 26 58 5 5 58

24 60 58 7 88 58

w N '-I

Descriptor

APPE~DIX TABLE D-2 SIGNIFICANT ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES

AS DETERMINED BY INSPECTION -COLLEGE STATION

Slide 1 Slide 2 Slide 3

Better Same Worse Better Same Worse Better Same

LIGHT TRAFFIC * * * UNCONGESTED * * * FREE FLOWING TRAFFIC * * * * LIGHT CONGESTION * * * * MODERATE TRAFFIC * * * MODERATE CONGESTION * * * * * * * CONGESTED * * * * HEAVY TRAFFIC * * * * HEAVY CONGESTION * * * VERY CONGESTED * * * JAMMED TRAFFIC * * STOP-AND~GO TRAFFIC * *

Worse

* * * *

w N OJ

Descriptor

APPENDIX TABLE D-~ PERCENTAGE ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES -

HOUSTON

Slide 1 Slide 2

Better Same Worse N Better Same Worse N Better

LIBHT CONGESTION 20 24 56 34 85 4 11 27. 75 MODERATE CONGESTION 0 24 76 34 22 59 19 27 48 HEAVY CONGESTION 0 15 85 34 4 11 85 27 2 UNCONGESTED 35 56 9 34 82 I 11 7 27 90 CONGESTED .. 0 12 138 34 7 44 49 27 8 VERY CONGESTED 0 12 88 34 4

I 7 89 27 0

LIGHT TRAFFIC 50 41 9 34 89 7 4 27 88 MODERATE TRAFFIC 9 44 47 34 33 52 15 27 79 HEAVY TRAFFIC 0 12 88 34 0 44 56 27 4 FREE FLOWING TRAFFIC 41 53 6 34 74 19 7 27 83 STOP-AND-GO TRAFFIC 0 9 91 34 0 30 70 27 6 JAMMED TRAFFIC 0 9 91 34 0 7 93 27 0 FREEWAY OK 26 65 9 34 67 22 11 27 92 NO DELAY 38 53 9 34 74 15 11 27 96 DELAY 0 12 88 34 4 33 63 27 6 EXTRA DELAY 0 12 88 34 0 7 93 27 6 MOVING WELL 24 65 11 34 70 19 11 27 77 NORMAL TRAFFIC 9 65 26 34 67 22 11 27 60

Slide 3

Same Worse N

23 2 48 44 8 48 17 81 48 10 0 48 38 54 48

6 94 48 12 0 48 21 0 48 44 52 48 17 0 48 40 54 48 4 96 48 8 0 48 2 2 48

46 48 48 8 85 48

21 2 48 38 2 48

w N <..O

Descriptor

APPENDIX TABLE D-4 SIGNIFICANT ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES

AS DETERMINED BY INSPECTION -HOUSTON

Slide 1 Slide 2 Slide 3

Better Same Worse Better Same Worse Better Same

FREE FLOWING TRAFFIC * * * ' * LIGHT TRAFFIC * * * * NO DELAY * * * * UNC:ONGFSTED * * * * FREEWAY OK * * * MOVING WELL * * * NORMAL TRAFFIC * * * * LIGHT CONGESTION * * * * MODERATE TRAFFIC * * * * * MODERATE CONGESTION * * * * CONGESTED * * * * DELAY * * * * HEAVY TRAFFIC * * * * STOP-AND-GO TRAFFIC * * * EXTRA DELAY * * HEAVY CONGESTION * * JAMMED TRAFFIC * * VERY CONGESTED * *

-

Worse

* * * * * * * *

APPENDIX TABLE D·5 PERCENTAGE ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES - ST. PAUL

Descriptor Slide 1 Slide 2 Slide 3

Better Same Worse N Better Same Worse N Better Same Worse N

LIGHT CONGESTION 34 38 28 60 73 27 0 22 82 18 0 55 MODERATE CONGESTION 4 41 55 58 38 58 4 24 58 42 0 if 52 HEAVY CONGESTION 0 2 98 58 0 26 74 23 0 49 51 53 UNCONGESTED 67 33 0 61 81 19 0 21 83 13 4 54 CONGESTED 0 7 . 93 59 13 70 17 23 9 74 17 53 VERY CONGESTED 0 4 96. 55 0 38 62 26 4 49 47 55 LIGHT TRAFFIC 75 23 2 60 87 13 0 23 87 13 0 54 MODERATE TRAFFIC 18 67 15 60 64 32 4 22 85 15 0 54 HEAVY TRAFFIC 2 2 96 58 12 56 32 25 6 72 22 54 FREE FLOWING TRAFFIC 49 49 2 61 86 14 0 22 91 9 0 54 STOP-AND-GO TRAFFIC 0 9 91 58 5 43 52 23 11 62 27 53 JAMMED TRAFFIC 0 2 98 57 0 12 88 26 0 22 78 55 FREEWAY OK 37 63 0 60 80 20 0 20 80 20 0 54 NO DELAY 43 57 0 61 82 18 0 22 91 9 0 53 DELAY 0 2 98 57 4 60 36 25 11 54 35 55 EXTRA DELAY 0 2 98 59 0 48 52 23 4 30 66 53 MOVING WELL 32 68 0 62 78 18 4 23 91 9 0 54 NORMAL TRAFFIC 20 78 2 61 80 20 0 20 87 13 0 53 FREE MOVING TRAFFIC 44 56 0 63 86 14 0 22 93 7 0 54 FREEWAY OPEN 64 34 2 62 78 22 0 23 82 18 0 51 FREEWAY CLEAR 88 10 2 60 91 9 0 23 90 10 0 52 MOVING AT SPEED LIMIT 27 73 0 62 59 41 0 22 91 7 2 53 NO CONGESTION 7l 29 0 56 74 26 0 23 89 11 0 54 CONGESTION 0 5 95 57 12 56 32 25 11 78 11 53 MODERATELY CONGESTED 9 40 51 57 38 54 8 24 51 47 2 55 CONGESTED TRAFFIC 0 3 97 58 14 52 34 21 7 63 30 54 HEAVILY CONGESTED 0 0 100 59 0 32 68 25 2 42 56 53 SLOW TRAFFIC 2 17 81 54 17 58 25 24 17 78 5 54 SPEEDS REDUCED 7 22 71 58 4 71 25 24 21 72 7 53 MOVING BELOW SPEED LIMIT 0 18 82 56 12 72 16 25 20 62 18 55 TRAFF! C STOPPED 0 2 98 59 0 8 92 24 2 9 89 55 TRAFFIC JAM 0 0 100 59 0 28 72 25 0 38 62 53 FREEWAY JAMMED 0 0 100 59 0 12 88 25 0 22 78 54 FREEWAY BREAKDOWN 2 2 96 59 0 17 83 23 0 19 Bl 53 MINOR DELAY 0 11 89 56 29 38 33 24 35 50 15 54 MAJOR DELAY 0 0 100 59 0 16 84 25 0 15 85 53 FREEWAY GRADE A 63 33 4 52 40 50 10 10 65 31 4 26 FREEWAY GRADE F 4 24 72 53 8 58 34 12 8 58 34 26

330

APPENDIX TABLE D-6 SIGNIFICANT ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES

AS DETERMINED BY INSPECTION - ST. PAUL

---- ~-

Descriptor Slide l Slide 2 Slide 3

Better Same Worse Better Same Worse Better Same Worse ----- --

FREEWAY CLEAR * * * LIGHT TRAFFIC * * * NO CONGESTION * * * U~CQ~GESIED * * * FREE FLOWING TRAFFIC * * * * FREE MOVING TRAFFIC * * * * FREEWAY OK * * * * FREEWAY OPEN * *' * * NO DELAY * * * * LIGHT CONGESTION * * * * * -MODERATE TRAFFIC * * * MOVING WELL * * * NORMAL TRAFFIC * * * MOVING AT SPEED LIMIT * * * *" MODERATE CONGESTION * * * * * * MODERATELY CONGESTED * * * * * * MINOR DELAY * * * * * * rnNGESTED * * * CONGESTED TRAFFIC * * * * CONGESTION * * * * HEAVY TRAFFIC * * * * STOP-AND-GO TRAFFIC * * * * DELAY * * * * * MOVING BELOW SPEED LIMIT * * * SLOW TRAFFIC * * * s.e.E.E.!2S_R.ID ll. Fn * * * EXTRA DELAY * * * * VERY CONGESTED * * * * * HEAVILY CONGESTED * * * * HEAVY CONGESTION * * * * TRAFFIC JAM * * * * FREEWAY BREAKDOWN * *

..

* FREEWAY JAMMED * * * JAMMED TRAFFIC * * * MAJOR DELAY * * * IRAEFIC STOPPED * * * FR>>WAY GRADE A * * * * * FREEWAY GR{\DE F * * * * *

331

APPENDIX TABLE D-7

PERCENTAGE ASSOCIATION OF DESCRFTORS ·10 TRAFFIC STATES - LOS ANGELES

Descriptor Slide l Slide 2 Slide 3

Better Same Worse N Better Same Worse N Better Same Worse N

LIGHT CONGEST ION 15 22 63 41 72 22 6 36 78 20 2 51 MODERATE CONGESTION 7 14 79 42 26 61 13 38 66 34 0 53 HEAVY CONGESTION 0 0 100 44 0 12 88 34 0 22 78 55 UNCONGESTED 49 51 0 41 92 2 6 36 85 15 0 53 CONGESTED 0 2 98 41 5 53 42 38 9 50 41 55 VERY CONGESTED 0 0 100 44 0 14 86 35 4 24 72 55 LIGHT TRAFFIC 52 41 7 44 90 5 5 36 87 13 0 54 MODERATE TRAFFIC 16 57 27 44 43 54 3 35 75 25 0 51 HEAVY TRAFFIC 0 0 100 42 5 41 54 37 0 51 49 55 FREE FLOWING TRAFFIC 42 58 0 '\3 86 11 3 35 91 9 0 55 STOP-AND-GO TRAFFIC 0 0 100 42 2 42 56 36 11 45 44 55 JAMMED TRAFFIC 0 0 100 43 0 11 89 36 0 5 95 55 FREEWAY OK 23 77 0 43 81 14 5 36 87 13 0 ·52 NO DELAY 49 51 0 41 91 3 6 34 90 10 0 52 DELAY 0 2 98 44 10 37 53 38 6 47 47 55 EXTRA DELAY 2 2 96 43 3 28 69 36 5 15 80 55 MOVING WELL 28 72 0 43 83 14 3 36 93 7 0 55 NORMAL TRAFFIC 28 65 7 43 71 21 8 38 83 17 0 52 FREE MOVING TRAFFIC 47 53 ·o 43 84 11 5 37 91 9 0 55 FREEWAY OPEN 60 40 0 42 89 11 0 35 88 12 0 52 FREEWAY CLEAR 68" 32 0 44 89 8 3 37 89 11 0 53 MOVING AT SPEED LIMIT 30 70 0 44 83 n 6 36 89 11 0 55 NO CONGESTION 45 55 0 44 90 ·i5 5 36 87 13 0 55 CONGESTION 0 0 100 42 3 50 47 36 5 67 28 55 MODERATELY CONGESTED 7 7 86 41 24 66 10 38 61 37 2 51 CONGESTED TRAFFIC 0 0 100 43 3 38 59 37 4 60 36 55 HEAVILY CONGESTED 0 0 100 44 0 8 92 37 0 9 91 55 SLOW TRAFF! C 0 5 95 44 11 62 27 37 29 60 11 55 SPEEDS REDUCED 3 12 86 44 16 61 23 38 25 56 19 55 MOVING BELOW SPEED LIMIT. 4 14 82 44 14 59 27 37 40 45 15 55 TRAFFIC STOPPED 0 0 100 44 0 3 97 35 2 5 93 55 TRAFFIC JAM 0 0 100 44 0 24 76 37 0 18 82 55 FREEWAY JAMMED 0 0 100 43 0 6 94 35 l 4 95 55 FREEWAY BREAKDOWN 0 5 95 43 0 3 97 36 0 9 91 55 MINOR DELAY 2 7 91 42 26 34 40 35 48 48 4 52 MAJOR DELAY 2 0 98 44 3 8 89 36 l 4 95 55 FREEWAY GRADE A 47 35 17 34 54 46 0 24 33 67 0 42 FREEWAY GRADE F 0 26 74 34 10 52 38 21 5 70 25 40 TRAFFIC CONDITION A 49 30 21 33 58 31 11 26 36 56 8 45 FREEWAY CONDITION C 5 41 54 37 21 71 8 24 26 70 4 47 TRAFFIC CONDITION F 0 17 83 35 13 35 52 23 9 61 30 46

332

I I

I I

l I

I I

' I :

I

, I .1

! I

APPENDIX TABLE 0-8 SIGNIFICANT ASSOCIATION OF DESCRIPTORS TO TRAFFIC STATES

AS DETERMINED BY INSPECTION - LOS ANGELES

-- --Descriptor Slide 1 Slide 2 Slide 3

-----r-----.----- -·--Better Same Worse Better Same Worse Better Same ------ ··---

FREEWAY CLEAR * * * ·-FREE FLOWING TRAF~IC * * * * FREE MOVING TRAFFIC * * * * FREEWAY OPEN * * * * LIGHT TRAFF! C * * * * NO CONGESTION * * * * NO DELAY * * * * IJJ@rjfillli_f) * * * * FREEWAY OK * * * MOVING. AT SPEED LIMIT * * * MOVING WELL * * * NORMAL TRAFF! C * * * MODE8ATE TRAFFJC * * * * LIGHT CONG ES TI ON * * * CONGES'rION * * * * --MINOR-DELAY * * I * * * * MODERATE CONGESTION * * * * MODERATELY CONGESTED * * * * t:.1QY.U1G.....B.Uilli....S.H£.O_L IM IT * * * * --~-SLOW TRAFFIC * * * SPEEDS REDUCED * * * CONGESTED * * * * CONGESTED TRAFFIC * * * * DELAY * * * * HEAVY TRAFFIC * * * * STOP-AND-GO TRAFFIC * * * * EXTRA DELAY * * FREHIAY BREAKDOWN * * FREEWAY JAMMED * * HEAVILY CONGESTED * * JAMMED TRAFFIC * * MAJOR DELAY * * TRAFFIC JAM * * TRAFFIC STOPPED * * VERY CONGE.SIFD * * FREEWAY CONDITION C * * * * -- --- -FREEWAY GRADE.A * * * * * * FREEWAY GRADE F * * * * TRAFFT c rnNDTTTON A * * * * * * * TRAFFIC CONDITION F * * * *

333

~Jorse

* * * * * * * * * * * * * *

APPENDIX E INCIDENT CLASSIFICATION FROM TOPIC AREA F

UNRESTRICTED SUBJECTS CONDITIONS

traffic conditions 5 information 1 general conditions 1 bad roadway conditions 1 bad road conditions 1 road condition 3 bad traffic conditions 1 roadside conditions 1 off road problem 1 road information 1 roadside distractions 1 congestion 5 heavy congestion 1 backed up 1 heavy traffic 4 freeway congestion 1 congestion accident 1 crowded conditions 1 traffic congestion 1 jammed 1 traffic stop conditions 1 stop and go traffic 1 bumper to bumper 1 exit jammed (move to left

lane if not exiting) 1 condition affect travel

in one or more lanes 1 lane closed 1 lane limited 1 traffic lanes 1 conditions that will directly

affect trip - change in plans 1 delay 3 possible delay 1 conditions causing brief delay 1 traffic stopped temporarily 1 traffic stopped indefinitely 1 temporary delay 1 can expect reasonable delay 1 definite delay 1 delaying conditions 1 long delays 1

334

CONDITIONS - Continued

delayers 1 hinderance to traffic flow 1 minor hinderance or distraction 1 difficult driving conditions 1 severe conditions might cause

accident or chain accident 1 condition closing freeway

travel time for short amount of time 1

condition closing freeway for long periods of time 1

temporary condition affecting speed of travel 1

things that affect.moving traffic 1

trip stoppers 1 cause problems but could continue 1 condition of pavement 1 conditions cause me to drive

more carefully 1 group inconveniences 1 minor inconveniences 1 worst condition·could cancel trip 1 no appreciable time/speed loss 1 conditions not directly affecting me 1 no effect on travel 1 no effect on conditions 1 doesn't affect you 2 no effect on me 1 condition probably will not concern

traffic flow on my side 1 conditions not affecting driver

indirectly 1 partly out of order 1 limited access to freeway 1 affects performance·of driver & auto

but can stop 1 affects performance of driver & auto

but can't stop 1 natural 1 normal movement 1 rather normal 1 normal travel 1 important information help flow

of traffic 1 hazard movement 1 unusual situations 1

TOTAL 90

335

WARNING

accidents 11 accident of freeway 1 large accident 1 accident on opposite side

of road 3 accident ahead 2 accident traffic stopped

or slowed 1 hazard 1 misc. hazards 1 road hazards 1 definite hazard 1 dangerous driving 1 dangerous conqitions 2 hazardous driving conditions 2 possible hazard 2 highway open but dangerous 1 freeway hazard or damage 1 hazard on freeway 1 breakdown 3 needs close watch 1 warning 1 traffic stop 1 caution warning 1 extreme caution and leave extra

room between cars 1 merge 1 extreme hazard 1 must stop and wait 1 traffic must stop 2 caution 8 be prepared to stop 2 be alert 1 do not enter 1 no go or do not enter 1 watch for - extra caution 1 stop and wait it out 1 beware 1 quick stop 1 stop 2 vehicle stopped 2 prepare to stop if necessary 1 caution temporary stop 1 reduce speeq 3 no reroute 1 watch out for actions of other

drivers in my lane 1

336

.-·.:·

WARNING - Continued

drive with caution 1 not passing condition 1 probable stop 1 caution and be prepared to stop 1 stop all traffic 1 proceed with caution 1 constant extra caution 1 extra caution 1 little extra caution 1 road repair 2 roadwork 3 construction 4 freeway construction 1 repairs · 1 hole in road 1 road damage 1 road narrows 1 pavement unsatisfactory 1 uneven pavement 1 pavement broken 2 pavement problem 1 rough pavement 1 stop and seek advice 1 take care 1 watch for stops 1 be careful 1 be extra careful 1 things to look for 1 road obstructions 1 traffic hazards 1 natural obstruction 1 obstructions 2 objects in or by road 3 moving obstacles 2 stationary obstacles 1 obstacles on freeway 2 objects on pavement 1 trash 2 debris 1 garbage container 1 possible obstruction 1 minor obstacles 1 obstacles 1 truck loses load 1 road 1 i ttered 1 warning of something ahead moving

slow 1 something in road 1

337

WARNING - Continued

animals animals, army, obstructions animals on pavement (or some

temporary obstruction) cause of freeway congestion people bicycles and people bicycles pedestrians vehicle procession funeral non motorists parade

1 1

1 1 3 1 1 3 1 1 1 1

people on road convoy

other car - slow stop 1

non vehicular traffic tunnel information

TOTAL

3 1 2

157

DETOUR

closed 1 closed conditions· 1 closed lanes 1 closed road 1 change planned course 1 demand reroute 1 detour 5 detour conditions 1 detour if in a hurry 1 divert 1 freeway closed 4 freeway closed (traffic must

detour!} 1 major detours 1 major slowdown - possible detour 1 means detour 1 procession detour 1 reroute 1 road cannot be traveled 1 road closed 1 road closed or need to bypass

or exit 1 route is closed 2 situation causing rerouting 1 stop-detour 1 use another route 1 would leave freeway 1

TOTAL ~

339

SLOW

be prepared for others to slow down to look 1

caution - slow 1 continue s1owly 1 drive slow suddenly 1 drive slow because of traffic 1 drive slow because you can't see 1 expect stop and go conditions also

moving slowing 1 go slow 1 major.slowdown 1 means slowdown 1 move slowly with caution 1 possible slow traffic 1 possibility of need to slow down 1 road struct~r~l conditions slow

slightly 1 temporary slowdown 1 traffic· slowed down 1 semi-normal but slow 1 slow 1 slow down 3 slow down considerably 4 slow down a little 1 slow down & make room 1 slow down and be prepa.red to stop

suddenly 1 slow down and try to get off

freeway 1 slow down and try to get into free

lane 1 slow to a crawl and try to get·in

free lane 1 slow down and wonder what to do 1 slow care watching 1 slow for short time with added

attention 1 slow moving conditions 1 slow traffic on freeway 1 slow traffic 6 slow moving traffic 4 slow traffic reduce speed 1 slow warning 1 slow for unknown distance unprotected

lives at stake 1 slow moving vehicles 2 unusually slow traffic 1 unknown sized lane slow down 1

340

SLOW - Continued

very slow 1 very slow traffic 1 very slow and avoid obstacles 1 would slow trip down 1

TOTAL sr-

341

WEATHER CONDITIONS

bad weather 1 bad weather condition 1 flooded 1 flooded (or water on road)· 1 fog 2 hazards caused by weather 1 icy conditions 1 ice 1 ice (or freezing water on road) 1 obstructions due to weather 1 road flooded 1 slick or wet pavement 1 slippery 1 snow 1 snow and ice 1 water on road 1 water hazards 1 weather 3 weather affects freeway 1 weather conditions 7 weather conditions on freeway 1 werather conditions North 1 weather conditions needing amount

of severity 1 weather conditions and pavement 1 weather conditions - slow · 1 weather problem 1 visibility 3 low visibility 2 reduced visibility 3

TOTAL 43

342

MISCELLANEOUS

unrelated to other groups 1 operates sees 1 large moving group 1 miscellaneous 1 nice to know 1 no necessary at all 1 miscellaneous - didn't fit above 1 in trouble 1 cancel trip 1 this should not happen on a

freeway 1 place to put trash 1 do not worry 1 personal automobile failure only

slight interest 1 have to change plans but can keep

going 1 have to change plans and perhaps

can't get to where you are going 1

TOTAL 15

343