National Household Travel Survey

California Data (NHTS-CA)

Planning HorizonsDecember 11, 2013

10:00-12:00

Office of Travel Forecasting and AnalysisCaltrans, Division of Transportation

Planning

IN ANTIQUITY

Man Asked:• Who am I ?• Where am I ?• How did I get here?• How Do I Get There?

Who - Socio-economic characteristics of Persons, Households, Workers and Drivers Where – Live, Work, Shop, Play Why – Activity, Origin/DestinationWhat – Vehicles, Transportation Issue When – Time , Day of the Week How - Mode, VMT (how far - miles), VHT (how long – hours) mode

Today, these questions and a lot more are answered in the Household Travel

Surveys

Who Are We? – Age/Gender

5 6-15 16-20

21-25

26-30

31-35

36-40

41-45

46-50

51-55

56-60

61-65

66-70

71-75

76-80

81-85

86-88

89+0

500

1000

1500

2000

2500

3000

Male Female

Who Are We? - Lifecycle

0 5 10 15 20 25

2+ adults, retired, no childrenone adult, retired, no children

2+ adults, youngest child 16-21one adult, youngest child 16-21

2+ adults, youngest child 6-15one adult, youngest child 6-15

2+ adults, youngest child 0-5one adult, youngest child 0-5

2+ adults, no childrenone adult, no children

Percent of Households by Lifecycle

Household Income Distribution

> = $100,000$80,000 - $99,999$75,000 - $79,999$70,000 - $74,999$65,000 - $69,999$60,000 - $64,999$55,000 - $59,999$50,000 - $54,999$45,000 - $49,999$40,000 - $44,999$35,000 - $39,999$30,000 - $34,999$25,000 - $29,999$20,000 - $24,999$15,000 - $19,999$10,000 - $14,999

$5,000 - $9,999< $5,000

0 300 600 900 1,200 1,500 1,800 2,100 2,400 2,700Total Households (Thousands)

Distribution of Incomes for One Adult, Youngest Child 0-5 Households

> = $100,000$80,000 - $99,999$75,000 - $79,999$70,000 - $74,999$65,000 - $69,999$60,000 - $64,999$55,000 - $59,999$50,000 - $54,999$45,000 - $49,999$40,000 - $44,999$35,000 - $39,999$30,000 - $34,999$25,000 - $29,999$20,000 - $24,999$15,000 - $19,999$10,000 - $14,999

$5,000 - $9,999< $5,000

0 5 10 15 20 25 30 35

Who Are We? – Job Category

5,412

1,9643,451

6,672

213

Total Workers by Job Cat-egory

Sales / serviceClerical / admin supportManuf, construct, maintenance, or farmingProfessional, managerial, or technicalOther

One Adult, Youngest Child 0-5 Households by Job Category

Sales /

servi

ce

Clerical

/ admin su

pport

Manuf, c

onstruct,

main

tenance

, or fa

rming

Professional,

man

ageria

l, or te

chnica

lOther

01020304050 44.6

17.8 15.121.8

0.5

Perc

ent

Households by Household Vehicle Count

What are We Driving?

DODGEFO

RD

CHEVROLE

TGMC

VOLKSWAGEN

BMW

NISSAN / D

ATSUN

HONDA

MERCED

ES BEN

Z

TOYOTA

LEXUS

0500

1,0001,5002,0002,5003,0003,5004,0004,500

1,053

3,0912,405

525 457 476

1,263

2,713

493

4,112

477

Total Vehicles by Vehicle Make

Tota

l Veh

icle

(Th

ousa

nds)

What Type of Vehicle?

12,525

1,757

4,186

3,69751 167 685 3 23

Vehicles by Vehicle TypeAutomobile/car/station wagonVan (mini, cargo, passenger)Sports utility vehiclePickup truckOther truckRV (recreational vehicle)MotorcycleGolf cartOther

< $5,000

$5,000 - $9,999

$10,000 - $14,999

$15,000 - $19,999

$20,000 - $24,999

$25,000 - $29,999

$30,000 - $34,999

$35,000 - $39,999

$40,000 - $44,999

$45,000 - $49,999

$50,000 - $54,999

$55,000 - $59,999

$60,000 - $64,999

$65,000 - $69,999

$70,000 - $74,999

$75,000 - $79,999

$80,000 - $99,999

> = $100,000

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Average Annual Vehicle Miles Traveled (VMT) by Income Distribution

Average Minutes Spent Driving Per Person, Per Day Sacramento, Los Angeles, San Diego and San Francisco

by Household Composition

one adult, no ch

ildren

2+ adults, n

o child

ren

one adult, youngest

child

0-5

2+ adults, y

oungest ch

ild 0-5

one adult, youngest

child

6-15

2+ adults, y

oungest ch

ild 6-15

one adult, youngest

child

16-21

2+ adults, y

oungest ch

ild 16-21

one adult, retired, n

o child

ren

2+ adults, re

tired, no ch

ildren

0

20

40

60

80

100

120

Los Angeles Sacramento San Diego San Francisco

Highway conge

stion

Access

to / ava

ilabilit

y of public

transit

Lack of w

alkways o

r sidewalks

Price of t

ravel

Aggressive / d

istracte

d drivers

Safety co

ncerns

0%5%

10%15%20%25%30%35%

23%

9%2%

29%

15% 15%

Importance of Transportation Issues

0%20%40%

12% 7% 2%

39%21% 19%

Fresno

0%20%40%

11% 3% 3%31%

17%34%

Imperial

0%10%20%30%

15%28%

2%

22% 18% 15%

San Francisco

Traffic Congestion Issue

> = $100,000$80,000 - $99,999$75,000 - $79,999$70,000 - $74,999$65,000 - $69,999$60,000 - $64,999$55,000 - $59,999$50,000 - $54,999$45,000 - $49,999$40,000 - $44,999$35,000 - $39,999$30,000 - $34,999$25,000 - $29,999$20,000 - $24,999$15,000 - $19,999$10,000 - $14,999

$5,000 - $9,999< $5,000

0 10 20 30 40 50 60 70 80

Respondent's View on Traffic Congestion by IncomeA big issue A moderate issue A little issue

Percent

20

Objective of SCAG Study• Is to use NHTS data to provide updated travel characteristics for

SCAG region. • This presentation includes results of following analysis:1. Overall demographics and travel characteristics2. Relation between residential location and commuting3. Assimilation of Hispanic immigrants’ travel behavior4. Income interaction with land use – transportation relation

• Results will be provided to SCAG modelers and planners for their analysis.

Source:

Residential Land Use, Travel Characteristics, and Demography of Southern California – presented by the Southern California Association of Governments

2121

Travel by Age

• Daily trips and travel distance are the highest for the working age population (25-64).

• The elderly still rely on a car, but drive less.

* Demographics & Travel

0%10%20%30%40%50%60%70%80%90%

100%

< 16 16-24 25-49 50-64 65-74 > 74

Driver Passenger

Auto Use by Age

Daily Trips and Distance by Age

22

Travel by Age (Elderly)

• 20% - 33% of the elderly did not travel on the survey day.

• However, when they travel, their trips are no less than the younger. Non-work Trips by Age

% of Persons Did Not Travel

0%

5%

10%

15%

20%

25%

30%

35%

40%

Below16 16-24 25-49 50-64 65-74 75+

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Below16 16-24 25-49 50-64 65-74 75+

* Demographics & Travel

2323

Time of Day by Purpose

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 1 2 3 4 5 6 7 8 9 10 1112 13 14 15 16 17 18 19 20 21 22 23

Time of Day by HBW

HBW

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 1 2 3 4 5 6 7 8 9 10 11 12 1314 15 16 17 18 19 2021 22 23

Time of Day by NHB

NHB

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 1 2 3 4 5 6 7 8 9 10 11 12 13 1415 16 17 18 19 20 21 2223

Time of Day by HBO

HBO

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 1 2 3 4 5 6 7 8 9 1011 12 13 14 15 16 1718 19 20 21 2223

Time of Day by HB Shopping

HBSHOP

school

lunch

open hoursschool

* Demographics & Travel

2424

Residential Density & Commuting Distance

• Living in higher density neighborhoods:• Shorter commuting distance.

• Commuting time is about the same for all density.

* Residential Location and Commuting

0

5

10

15

20

25

30

35

0

2

4

6

8

10

12

14

16

18

20

<2 2-6 6-18 18-38 38-100 100+

Commuting Distance and Time

DISTtoWK

TIMEtoWK

Density from low to high

School Trips by Distance and Mode

Uses for O & D Survey Data Sets .

Household Origin and Destination Surveys help transportation analysts understand people's travel choices:

1. What trips or tours do people make (origins and destinations)

2. Why they travel (purposes or activities)

3. Travel patterns (amounts by household or person characteristics and by places they go)

4. How travel would change under different circumstances (travel models)

These surveys provide the detailed information about the large number of choices travelers make. Those explanations are most usefully expressed in transportation models which in turn allow analysts to estimate travel under changed circumstances, usually alternate land use and transportation system scenarios.

•School and Commute distances and modes•Non-driving trips by distance and home region•Reasons for not walking more•Reasons for living where they do•Trip purposes and start and end times•Medical conditions affecting mobility•Use of mobility devices•Internet use: frequency, purchases, delivery

Some Travel Pattern Descriptions

Region to Region Trips (Annual 000)

Destination Region Origin Region

MTC

Sierra

North State

SACOG/

TMPO

SJ Valley

SCAG

Central

Coast

San Diego

MTC 8,608,133 4,150 4,481 41,437 33,162 7,457 21,774 3,619

Sierra 4,923 577,586 6,699 17,745 12,496 250 732 142

North State 5,735 6,607 819,901 2,753 . 4,040 106 23

SACOG/TMPO 39,667 19,664 3,567 2,608,636 17,413 5,782 1,870 20

SJ Valley 32,532 17,650 178 17,962 4,179,801 16,021 4,502 1,226

SCAG 7,244 320 3,959 6,153 18,589 19,757,130 12,980 67,591

Central Coast 21,204 732 106 1,734 4,095 14,260 1,520,237 605

San Diego 3,407 245 267 20 717 64,882 888 3,478,987

Sample Mode PercentagesRegion=MTC Miles=2-3

Mode Percent LowerCL UpperCL RowPercent RowLowerCL RowUpperCL

Missing 0.0174 0.0000 0.0400 0.1781 0.0000 0.4102

Drive/Driven 8.5533 7.8840 9.2226 87.3816 84.6328 90.1304

Other 0.1949 0.1010 0.2887 1.9909 1.0244 2.9574

Bus 0.5317 0.2910 0.7724 5.4318 2.9465 7.9172

Rail 0.0858 0.0212 0.1505 0.8767 0.2109 1.5426

Air . . . . . .

Bicycle 0.1606 0.0837 0.2375 1.6409 0.8684 2.4135

Walk 0.2447 0.1681 0.3213 2.4998 1.7276 3.2721

Total 9.7884 9.1414 10.4355 100.000 _ _

• Bike and Pedestrian Hours by Caltrans District

District WalkHrs BikeHrsD01 Eureka 814,064 78,704D02 Redding 1,089,364 74,542D03 Marysville 5,923,755 896,778D04 Oakland 16,427,130 2,524,209D05 San Louis Obispo

3,364,097 518,854

D06 Fresno 4,027,689 647,768D07 Los Angeles 21,980,348 3,251,802D08 San Bernardino 7,238,376 1,101,887D09 Bishop 97,662 10,116D10 Stockton 3,210,006 516,364D11 San Diego 6,526,006 794,366D12 Irvine 5,033,585 872,235

FHWA Contract In 2008, NHTS invited state DOTs to

supplement the sampling in their areas

Caltrans allocated $3.15 million to survey additional households and ask additional travel and attitudinal questions about biking and walking

California Original Samples – 3,000

California Add-On Samples – 18,000 to total - 21,000 (Oversampling in San Diego County to 5,500)

Areas with Supplemental Samples

Geography Total Sample (Households)

California 21,225District 1 - Eureka 255District 2 - Redding 326District 3 - Marysville 1,609District 4 - Oakland 3,808District 5 - San Luis Obispo

735

District 6 – Fresno 990District 7 – Los Angeles 3,767District 8 – San Bernardino

1,566

District 9 – Bishop 22District 10 - Stockton 815District 11 – San Diego* 6,050District 12 – Irvine 1,282*District 11 (San Diego) has a supplement of 4,600 households

Data FilesSETS

Information About # Observations # Variables

Households 21,225 79

Persons 44,957 245

Vehicles 44,526 96

Trips 171,661 183

Locations 171,661 36

Geographic Designations National Region State MSA/CMSA/CBSA County City Census Tract/Block Latitude/Longitude

coordinates

Customized Areas – Under Construction

Traffic Analysis Zone (TAZ)

Air Quality Conformity Regions

Analysis Tools SAS MS Access Statistical Tool on Oakridge Lab website – output is Excel and HTML

Services Analysis on Request

Consultation

Data Downloads

How to get Data or Analyses

NHTS Website: http://nhts.ornl.gov/

California Household Travel Survey (CHTS)http://dot.ca.gov/hq/tsip/otfa/tab/chts_travelsurvey.html

Caltrans DOTP Website:www.dot.ca.gov/hq/tsip/otfa

Leonard Seitz:Leonard.Seitz@dot.ca.gov(916) 654-2610

Diana PortilloDiana.Portillo@dot.ca.gov(916) 653-3182

Soheila Khoii (CHTS)Soheila.Khoii@dot.ca.gov

Caltrans Planning Horizons ForumDecember 11, 2013Deborah Salon, PhDInstitute of Transportation StudiesUniversity of California, Davis

Estimating total miles walked and biked by census tract in california

Vehicle activity is an output of travel models, but detailed estimates of bicycle and pedestrian activity are often not available.

Good estimates of the total amount of cyclist and pedestrian activity on our roads are useful for: Informing demand-based investments in bicycle and pedestrian infrastructure

Identifying dangerous locations for potential road safety investment

MOTIVATION

What are the total miles walked by pedestrians and total miles biked by cyclists living in each census tract in California?

Important Note: The estimates presented here are not of miles walked and biked within the geographic area of each tract, but we expect them to be highly correlated with these values.

RESEARCH QUESTION

1. Assign census tracts to neighborhood types based on built environment characteristics

2. Calculate miles biked and miles walked for each respondent in the 2009 NHTS and the 2010-2012 CHTS (all results presented are from NHTS)

3. Assign each survey respondent to their age-gender-home neighborhood category

4. Calculate average miles biked and miles walked for each age-gender-home neighborhood category

5. Use these averages with census data to expand travel survey data to population totals

METHOD

Cluster analysis of 10 variables yielded 4 neighborhood types: Population Density Road Density Local Job Access Regional Job Access Restaurants Within 10

Minute Walk Pct. Walk/Bike Commuters Pct. Single Family Detached Pct. Old Housing Pct. New Housing Median House Value

NEIGHBORHOOD TYPE CLASSIFICATION

SAN FRANCISCO BAY AREA

LOS ANGELES AREA

010

2030

Perc

ent

0 2 4 6 8 10Miles Walked Per Pedestrian

NHTSTotal N (weekday)

34,123

N biked 773N walked 7,891% biked 2.3%% walked 23.1%

SURVEYED INDIVIDUAL MILES WALKED AND BIKED

010

2030

40Pe

rcen

t

0 10 20 30 40 50Miles Biked Per Cyclist

Categories based on:GenderAge Group (5 groups, chosen based on biking and walking distance distributions across ages)

Home Neighborhood Type (4 Types)Yields 40 Categories

SURVEY RESPONDENT CATEGORIES

Gender Age Group NH Type0

0.2

0.4

0.6

0.8

1

1.2

1.4

5-9 10

-17

18-

59 60-7

475

+

Cent

ral C

ityUr

ban

Subu

rbRu

ral

AVERAGE MILES WALKED BY SURVEY RESPONDENT CATEGORY

M F

Gender Age Group NH Type0

0.05

0.1

0.15

0.2

0.25

5-9

10-3

435

-59

60-6

970

+

Cent

ral C

ityUr

ban

Subu

rbRu

ral

AVERAGE MILES BIKED BY SURVEY RESPONDENT CATEGORY

M

F

Simple Expansion Formula:

where i indexes gender-age group categories.

SURVEY-TO-POPULATION ESTIMATION METHOD

EXAMPLE OF USE FOR PEDESTRIAN INFRASTRUCTURE ANALYSIS

05

1015

Perc

ent

0 200 400 600 800 1000Miles Walked Per Walkable Road Mile

EXAMPLE OF USE FOR CYCLING INFRASTRUCTURE ANALYSIS

05

1015

Perc

ent

0 100 200 300Miles Biked Per Non-Highway Road Mile

TRACT-LEVEL WALKING ESTIMATES: SAN FRANCISCO

Weekday Miles Walked Per Non-HighwayRoad Mile

TRACT-LEVEL WALKING ESTIMATES: LOS ANGELES

TRACT-LEVEL BIKING ESTIMATES: SAN FRANCISCO

Weekday Miles Biked Per Non-HighwayRoad Mile

TRACT-LEVEL BIKING ESTIMATES: LOS ANGELES

TRACT-LEVEL BIKING ESTIMATES: LOS ANGELES

EXAMPLE USE FOR SAFETY ANALYSIS

02

46

810

Perc

ent

0 .0001 .0002 .0003 .0004 .0005Accidents Per Mile Walked

EXAMPLE USE FOR SAFETY ANALYSIS

05

1015

Perc

ent

0 .001 .002 .003Accidents Per Mile Biked

MAP OF ACCIDENTS PER DISTANCE WALKED IN SAN FRANCISCO

Annual SeverePedestrian Accidents Per1000 Weekday Miles Walked

MAP OF ACCIDENTS PER DISTANCE WALKED IN LOS ANGELES

The method used here can provide estimates of cyclist and pedestrian activity based on travel survey and census data, without a full travel model

The estimates here of miles of activity per road mile are highly correlated with tract population density

The CHTS data produce somewhat lower estimates of bike/walk activity

It would be interesting to compare these results with those from a full travel model, if available

Contact: ddsalon@ucdavis.edu

CONCLUSIONS

Questions/Comments