otrec counting-bikes&peds

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We are Traffic: Creating Robust Bicycle and Pedestrian Count Programs

Krista Nordback, Ph.D., P.E.Oregon Transportation Research and Education Consortium (OTREC)

Portland State University

Overview

• Introduction

• Traffic Monitoring Programs

• Non-Motorized Count Programs

• Conclusions & Recommendations

INTRODUCTION

Why measure walking & biking?

Why measure walking & biking?

• Funding & policy decisions

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

• Facility design

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

• Facility design

• Planning (short-term, long-term, regional…)

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

• Facility design

• Planning (short-term, long-term, regional…)

• Economic impact

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

• Facility design

• Planning (short-term, long-term, regional…)

• Economic impact

• Public health

Why measure walking & biking?

• Funding & policy decisions

• To show change over time

• Facility design

• Planning (short-term, long-term, regional…)

• Economic impact

• Public health

• Safety

How many bike and walk?

• Surveys

– National

– Regional

– Local

• Counts

– Permanent

– Short duration

TRAFFIC MONITORINGPROGRAMS

State Traffic Monitoring

Metro Count Accessed 6/13/13 http://mtehelp.tech-metrocount.com/article.aspx?key=mc5805

Commonly inductive loops

Permanent Counters

Short Duration Counters

Commonly pneumatic tubes

Colorado’s Permanent Counters

Colorado’s Short Duration Traffic Counts

CDOT OTIS Accessed 6/18/13 http://dtdapps.coloradodot.info/Otis/HighwayData#/ui/0/1/criteria/~/184.667/210.864

Permanent Counter

DataAnnual Average

Daily Traffic (AADT)

Vehicle Miles

Traveled (VMT)

Short Duration Counts

Use AADT to Estimate VMT

Sum (AADT X Segment Length) over network to compute Vehicle Miles Traveled (VMT)

COLORADO HIGHWAYS

Can we apply these methods to biking and

walking?

Compute

Annual Average

Daily Bicyclists

(AADB)

AADT for bicyclists!

Traffic Monitoring Guide 2013:

Chapter 4 for Non-motorized Traffic

NON-MOTORIZED COUNT PROGRAMS

The TMG 2013 Approach

The TMG 2013 Approach

National Bicycle and Pedestrian Documentation Project

Manual Counts:

2 hours

5 to 7pm

Tues, Wed, or Thurs in

mid-September

http://bikepeddocumentation.org/

Passive Infrared Counters

Inductive loop counters in bike lanes

Combined Bicycle and Pedestrian Continuous Counter

The TMG 2013 Approach

Permanent Count

Program

Permanent Count

Program

Geographic/Climate Zones

Urban vs. Rural

Annual Average Daily Bicyclists (AADB)

Volume

Categories

0 500 1,000

AADB

Co

nti

nu

ou

s C

ou

nt

Stat

ion

s

Medium

High

600

200

Low

Traffic Monitoring Guide 2013 Update, Chapter 4.

Permanent Count

Program

Daily Patterns

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

% o

f A

AD

B

Colorado Example (Bikes only)

Hourly Commute Pattern

0%

5%

10%

15%

20%

25%1

2:0

0 A

M

1:0

0 A

M

2:0

0 A

M

3:0

0 A

M

4:0

0 A

M

5:0

0 A

M

6:0

0 A

M

7:0

0 A

M

8:0

0 A

M

9:0

0 A

M

10

:00

AM

11

:00

AM

12

:00

PM

1:0

0 P

M

2:0

0 P

M

3:0

0 P

M

4:0

0 P

M

5:0

0 P

M

6:0

0 P

M

7:0

0 P

M

8:0

0 P

M

9:0

0 P

M

10

:00

PM

11

:00

PM

% o

f A

AD

B

City of Boulder Example (Bikes only)

Hourly Non-commute Pattern

0

50

100

150

200

250

300

350

400

0:0

0

1:0

0

2:0

0

3:0

0

4:0

0

5:0

0

6:0

0

7:0

0

8:0

0

9:0

0

10

:00

11

:00

12

:00

13

:00

14

:00

15

:00

16

:00

17

:00

18

:00

19

:00

20

:00

21

:00

22

:00

23

:00

Ave

rage

Ho

url

y V

olu

me

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Source: Pam Johnson, PSU

Permanent Count

Program

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns 2 Weekly Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns 2 Weekly Patterns

Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns 2 Weekly Patterns

Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns 2 Weekly Patterns

Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between

3 Daily Patterns 2 Weekly Patterns

Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

Commute

Urban PlainsNon-commute

Mountain Non-commuteHigher

Week-ends?

Rural MtnTrail?

Weekly Pattern

Location

YesYes

NoNo

Permanent Count

Program

Factoring Method

Adapted from Traffic Monitoring Guide

AADB = Cknown* D * M

Cknown = 24-hour count

D = Daily Factor

M = Monthly Factor

Factoring Method

Adapted from Traffic Monitoring Guide

AADB = Cknown* D * M

Cknown = 24-hour count

D = Daily Factor

M = Monthly Factor

Monthly Factor

M = AADB

MADB

where

MADB = Ave daily bike count in that month

Monthly Factor

M = AADB

MADB

where

MADB = Ave daily bike count in that month

June

= 5001,000

Monthly Factor

M = AADB

MADB

where

MADB = Ave daily bike count in that month

June

= 5001,000

= 0.5

Monthly Factor

M = AADB

MADB

where

MADB = Ave daily bike count in that month

June

= 5001,000

= 0.5

Daily counts in June are twice AADB.

Groups:

MountainNon-

Commute

Front RangeNon-

Commute Commute

January 3.90 1.54

February 3.15 2.00

March 1.26 1.23

April 2.16 1.07 1.05

May 1.04 0.75 0.93

June 0.52 0.76 0.71

July 0.42 0.76 0.82

August 0.51 0.74 0.67

September 0.71 0.76 0.78

October 1.73 0.99 1.04

November 1.46 1.36

December 2.52 2.28

Colorado Monthly Factors

Groups:

MountainNon-

Commute

Front RangeNon-

Commute Commute

January 3.90 1.54

February 3.15 2.00

March 1.26 1.23

April 2.16 1.07 1.05

May 1.04 0.75 0.93

June 0.52 0.76 0.71

July 0.42 0.76 0.82

August 0.51 0.74 0.67

September 0.71 0.76 0.78

October 1.73 0.99 1.04

November 1.46 1.36

December 2.52 2.28

Colorado Monthly Factors

Permanent Count

Program

How many counters/group?

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 1 2 3 4 5 6 7 8 9 1011121314

Pre

cisi

on

of

Mo

nth

ly F

acto

rs

Number of Counters

Non-CommuteFactors

Commute Counters

Average

Permanent Count

Program

The TMG 2013 Approach

The TMG 2013 Approach

The TMG 2013 Approach

Short Duration

Count Program

Short Duration

Count Program

Turning Movement Counts

Segment Count

A

B

Short Duration Counters• Pedestrian

• BicycleInfraredManual

Manual Pneumatic Tube Counters

Traffic Monitoring Guide 2013 Update, Chapter 4.

Short Duration

Count Program

Potential Selection Criteria

• Variety of facility types

– On-street

– Path

• Variety of land uses

– Central business district

– Residential

– School/University

• Technology related criteria

Short Duration

Count Program

Count Duration

0%

10%

20%

30%

40%

50%

60%

70%

0 200 400 600

Ave

rage

Ab

solu

te %

Dif

fere

nce

Count Duration (hours)

1 week

Short Duration

Count Program

Schedule Counts

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10 11 12

Ab

solu

te %

Err

or

in A

AD

T Es

tim

ate

Month

May to October best for Colorado

The TMG 2013 Approach

Factoring Method

Adapted from Traffic Monitoring Guide

AADB = Cknown* D * M

Cknown = 24-hour count

D = Daily Factor

M = Monthly Factor

AADB

VMT for

bicycles

CONCLUSIONS & RECOMMENDATIONS

Summary

• Traffic Monitoring Guide Approach:

– Permanent Count Program

– Short Duration Count Program

– Compute AADT for Bikes and Pedestrians

On-line Guide

www.pdx.edu/ibpi/guide-to-bicycle-pedestrian-count-programs

Recommendations

• Both permanent and short duration count programs are needed.

• Continuous counters are needed!

• Prefer 1 week short count

• Short duration counts in high volume months

– summer

• Integrate bike/ped counts into traffic data for preservation and access

Balance Permanent and Short Duration Programs

PERMANENT

COUNT

PROGRAM

SHORT

DURATION

COUNT

PROGRAM

Iterative Process

Iterative Process

Example

1st Year

PERMANENT

COUNT

PROGRAM

SHORT

DURATION

COUNT

PROGRAM

1 Permanent Counter 20 Manual Counts

2nd Year

PERMANENT

COUNT

PROGRAM

SHORT

DURATION

COUNT

PROGRAM

1 Permanent Counter 24 Automated Short Duration Sites(one week per site)

Rotate 1 counter all summer

3rd Year

PERMANENT

COUNT

PROGRAM

SHORT DURATION

COUNT PROGRAM

5 Permanent Counters 48 Automated Short Duration Sites(one week per site)

Rotate 2 counters all summer

4th Year

PERMANENT

COUNT

PROGRAM

SHORT DURATION COUNT

PROGRAM

6 Permanent Counters 120 Automated Short Duration Sites(one week per site)

Rotate 5 counters all summer

10th Year

PERMANENT COUNT

PROGRAM

SHORT DURATION COUNT

PROGRAM

12 Permanent Counters 720 Automated Short Duration Sites(one week per site) on 3 year rotation

Rotate 10 counters all summer on 3 year rotation

On-going Work

• Colorado, Vermont, Minnesota, Oregon, North Carolina, Washington State DOT’s are developing programs.

• TRB Bike/Ped Data Subcommittee

• FHWA to include bike/ped counts in Travel Monitoring Analysis System (TMAS)

• OTREC’s Bike/Ped Data Archive

Questions?

Krista Nordback

Nordback@pdx.edu

503-725-2897

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