How Do People Choose a Travel Mode? Factors Associated with Routine Walking & Bicycling

How Do People Choose a Travel Mode? Factors Associated with Routine

Walking & Bicycling

Robert Schneider, Ph.D. Candidate

UC Berkeley Department of City and Regional PlanningMay 2011

Outline

• Background & research question

• Core quantitative & qualitative research

• Contributions to the planning field

US Communities with Complete Streets Policies(Data Source: Complete Streets Coalition, January 2011)

0%

5%

10%

15%

20%

25%

30%

Pedestrian & Bicycle Mode Shares in Selected CountriesSources: Bassett, Pucher, Buehler, Thompson, and Crouter (2008); NHTS (2009)

Walk

Bicycle

Source: Basset et al. “Walking, Cycling, and Obesity Rates in Europe, North America, and Australia(2008)

U.S. Shopping Trip Mode Share (2009)

(Home-Based Shopping Trips)Source: Federal Highway Administration, National Household Travel Survey, 2009.

Hayward

Pedestrian

8%Bicycle

1%

Transit

2%

Automobile

89%

How do you travel to the store?

Mission Street, SF

San Carlos

Influences on Walking & Bicycling

Social Interaction

Exercise

Inexpensive

Easy

Altruistic

Work Responsibilities

Takes too Long

Fun

Bad Weather

Too Far

Family Responsibilities

Physical limitations

Traveling with Other People

Crime Risk

Crash Risk

HabitNo Emissions

Too Much TrafficFast Traffic

Carrying ThingsNo Sidewalks,

No Bike Lanes

Research Question

What factors are associated with walking and bicycling for routine travel?

Mission Street, SF

Core Research Components

1) Factors associated with walking and bicycling on routine tours

2) Characteristics of shopping districts that encourage walking rather than driving

3) Theory of mode choice decision process

Conceptual Framework for Data Collection & Analysis

Travel Characteristics

(distance, time, trip-chain, bags)

Mode ChoiceWalkBicycleTransit

Automobile

Socioeconomic Characteristics (gender, age, income)

Attitude Characteristics

(enjoy walking, environmentalist)

Perception Characteristics (crash risk, crime risk)

Shopping District Characteristics

(density, mix, facilities, parking)

Methodology

Study Area:San Francisco Bay Area

• 20 shopping districts

• Cluster analysis identified four types of shopping districts

– Urban Core (3)

– Suburban Main Street (8)

– Suburban Thoroughfare (7)

– Suburban Shopping Center (2)

Retail Pharmacy Store Customer Survey

• Intercept survey

• 20 stores in SF Bay Area

– Same national chain

– Different neighborhoods

– ~50 customers per store

• Weekday: 4-6 p.m.

• Saturday: afternoon

• 8/29/09 to 12/9/09

Daly City

Survey Instrument (front side)

Survey Instrument (back side)

Survey Participants

• 4,585 customers invited to participate

• 1,003 survey participants (22%)

• Participant characteristics– 59% female

– 31% age 18-34, 13% age 65+

– 73% shopped alone, 7% in groups of 3 or more

– 9% took Spanish-language survey

Mission Street, SF

Important Travel Definitions

• Routine: Travel involving stopping at activity locations (e.g., not purely exercise/recreation)

• Trip: A movement between a pair of activity locations, or stops (e.g., store to office).

• Stage: A movement made using a single mode of transportation. All trips have at least one stage.

• Tour (Trip-Chain): The set of all trips that a person makes from leaving home until returning home.

Example: Tour

Graphic source: McGuckin, N. & Y. Nakamoto. Trips, Chains, and Tours—Using an Operational Definition, 2004.Available online: http://onlinepubs.trb.org/onlinepubs/archive/conferences/nhts/McGuckin.pdf

Example: Trips


Example: Stages


Example Tour: San Mateo shopping district




Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store

Google Earth Image


Home

Store


Primary Tour Mode (N=959)

Pedestrian

21.3%

Bicycle

2.2%

Transit

9.9%

Automobile

66.6%

Primary Tour

Mode Share by

Shopping District

Pedestrian

Bicycle

Transit

Automobile

Mode

Pop. Density (2000)

1) Factors associated with walking & bicycling on shopping district tours

Market Street, SF

Potential Explanatory Variables

• Travel factors (11)

• Socioeconomic factors (21)

• Attitude & perception factors (10)

• Shopping district factors (26)

Base Map Source: Google Maps, 2010

The utility of a respondent choosing each mode (i = 1, 2, 3) to travel to and from a particular

store was expressed in the following equations:

��1� = �1 + 1�1� + �1��1 + 12�� + ��1� (1)

��2� = �2 + 2�2� + �2��2 + 12�� + ��2� (2)

��3� = �3 + 3�3� + �3��3 + ��3� (3)

�

Mixed logit model: Utility equations



��1� = �1 + 1�1� + �1��1 + 12�� + ��1� (1)

��2� = �2 + 2�2� + �2��2 + 12�� + ��2� (2)

��3� = �3 + 3�3� + �3��3 + ��3� (3)

�


Mode 1 (Walk)

Mode 2 (Transit)

Mode 3 (Auto)



��1� = �1 + 1�1� + �1��1 + 12�� + ��1� (1)

��2� = �2 + 2�2� + �2��2 + 12�� + ��2� (2)

��3� = �3 + 3�3� + �3��3 + ��3� (3)

�


Explanatory variables and

associated parameters



��1� = �1 + 1�1� + �1��1 + 12�� + ��1� (1)

��2� = �2 + 2�2� + �2��2 + 12�� + ��2� (2)

��3� = �3 + 3�3� + �3��3 + ��3� (3)

�


Unobserved correlated

error between people who

took survey at same store



��1� = �1 + 1�1� + �1��1 + 12�� + ��1� (1)

��2� = �2 + 2�2� + �2��2 + 12�� + ��2� (2)

��3� = �3 + 3�3� + �3��3 + ��3� (3)

�


Correlated error between

choice of Mode 1 & Mode 2

(Mode 1 & 2 Nest)

Mixed LogitModel

(N = 388)

(Walk, Transit, Automobile)

Mode ChoiceWalk

TransitAutomobile

Mixed logit model results: Factors associated with walking on tours to and from shopping districts

(N = 388)

Statistical significance:

*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)

Travel (+) number of stops***, no bags*

(-) distance in shop. dist.*, time***

Socioeconomic (+) group house***,

Spanish-speaker*, student***, low-income***

(-) physical disability*

Mode ChoiceWalk

TransitAutomobile


(N = 388)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)






Attitude(+) enjoy walking*

Perception(+) perceive crash risk***

Mode ChoiceWalk

TransitAutomobile


(N = 388)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)








Mode ChoiceWalk

TransitAutomobile


(N = 388)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)








Shopping District (+) population density*,

employment density***, tree canopy***

(-) survey store parking spaces***



Mode ChoiceWalk

TransitAutomobile






Shopping District (+) population density*,

employment density***, tree canopy***



(N = 388)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)

Mixed LogitModel

(N = 959)

(Walk, Bike, Transit,

Automobile)

Mode ChoiceWalk

BicycleTransit

Automobile

Mixed logit model results: Factors associated with bicycling on tours to and from shopping districts

(N = 959)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)

Travel

(-) distance***, Saturday***

Socioeconomic (+) Spanish-speaker*, student***,

no auto***, no children*

(-) female***, physical disability*

Mode ChoiceWalk

BicycleTransit

Automobile


(N = 959)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)

1) All bicycle respondents

enjoyed bicycling.

Travel





Attitude(+) enjoy bicycling1

Perception(-) perceive crime risk*

Mode ChoiceWalk

BicycleTransit

Automobile


(N = 959)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


enjoyed bicycling.

Travel







Mode ChoiceWalk

BicycleTransit

Automobile


(N = 959)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


enjoyed bicycling.

Travel







Shopping District (+) bicycle facilities**, bike parking

spaces *, employment density***, metered parking*


Travel


Mode ChoiceWalk

BicycleTransit

Automobile






Shopping District (+) bicycle facilities**, bike parking

spaces *, employment density***, metered parking*



(N = 959)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


enjoyed bicycling.

2) Walk vs. Drive within store area?

San Mateo

Mixed LogitModel

(N = 286)

(Walk, Automobile)

Travel (+) shopping alone*

(-) time***, 2+ bags*

Socioeconomic (-) physical disability

Mixed logit model results: Factors associated with walking within shopping

districts(N = 286)

Mode Choice

Walkvs.

Automobile


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)

Attitude

Perception


districts(N = 286)

Mode Choice

Walkvs.

Automobile


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


(-) time***, 2+ bags*


Attitude

Perception


districts(N = 286)

Mode Choice

Walkvs.

Automobile


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


(-) time***, 2+ bags*


Mode Choice

Walkvs.

Automobile

Attitude

Perception


districts(N = 286)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


(-) time***, 2+ bags*


Shopping District (+) multi-store shopping complex***,

metered street parking*

(-) driveway crossings***, commercial road speed limit*

Mode Choice

Walkvs.

Automobile

Attitude

Perception

Shopping District (+) multi-store shopping complex***,

metered street parking*

(-) driveway crossings***, commercial road speed limit*


districts(N = 286)


*** (p < 0.05)

** (0.05 < p < 0.10)

* (0.10 < p < 0.20)


(-) time***, 2+ bags*


3) Mode Choice Decision Process

El Cerrito

In-Depth Interviews

• 26 of the survey participants

• Spring and Summer 2010

• Conducted by phone

• 30 to 60 minutes

5) Habit(People who choose a particular mode

regularly are more likely to consider it as an option in the future)

2) Basic Safety & Security(People seek a mode that they perceive to provide a basic

level of safety from traffic collisions and security from crime )

3) Convenience & Cost (People seek a mode that will get them to an activity using an

acceptable amount of time, effort, and money)

4) Enjoyment(People seek a mode that provides personal (e.g., physical, mental, or emotional), social, or environmental benefits)

Pedestrian, Bicycle, Transit, or Automobile?

1) Awareness & Availability(People must be aware of the mode and have it available as

an option to travel to an activity)

Theory of Routine Mode Choice Decisions

Situational Tradeoffs













Socioeconomic Factors

(Explain differences in how people respond to each step)















Quotes: Awareness & Availability

• “He rides his bike because the cost of gas and he’s an environmental major…his attitude really did change when he became aware.” --Female, Age 52, San Carlos

• “Working people that are driving…don’t have the mind to think, ‘Am I doing things right?’ You are just surviving.” --Male, Age 30-39, Berkeley

• “So if one person starts cycling, and everyone starts seeing it, everyone will start cycling.” --Male, Age 40-49, Pleasanton

• “I am unemployed and can’t afford to buy a bicycle.” --Female, Age 20-29, San Francisco Market Street















Quotes: Basic Safety & Security

• “I can’t walk there because of the cars that are speeding on Bayshore…and it really bothers me because it’s the one little green open space that I could walk to…within 500 yards of my house, but I can’t get there because of the traffic.” --Female, Age 40-49, San Francisco Third St.

• “If there was less traffic…I probably would walk even more.” --Male, Age 30, San Francisco Fillmore Street

• “I’m not a skilled bicyclist…on the road, so I don’t really feel safe at all.” --Female, Age 30-39, Daly City

• “Right now I wouldn’t bicycle. I had a neighbor who had a terrible accident on a bicycle…” --Female, Age 52, South San Francisco

• “Bicycling itself…I would do it if I wasn’t right up next to cars.” --Female, Age 52, South San Francisco

Quotes: Basic Safety & Security

• “That’s how I got mugged, walking from my car to my house…I thought I might be walking more, but when I actually [moved] here, I realized that I couldn’t.” --Female, Age 40-49, San Francisco Third Street

• “When you are walking in this neighborhood, there’s nobody else walking. You look like a target here.” --Female, Age 40-49, San Francisco Third Street

• “We don’t live in a world that is as safe as it used to be…That’s why most parents don’t have their children biking around or walking out on the streets alone.” --Female, Age 40-49, Danville

• “There’s sometimes a fear of being stranded and not being able to get back, and you are at a distance from your home…I think a car gives you a feeling of security.” --Male, Age 60-69, Brentwood















3) Convenience & Cost

Accessibility of Activity Locations

Short distances to activities decrease and long distances to activities increase barriers to

walking and bicycling:

Availability and Price of Automobile Parking

Limited automobile parking increases and plentiful parking decreases barriers to driving:

• Planning time• Travel time• Physical effort• Packages• Bad weather

• Hills• Lack of lighting• Traffic risk• Sterile streets

• Planning time• Travel time

(searching for spot & walking from parking)

• Price (limited parking is often expensive)

Interview Quotes about Accessibility& Parking


"The next grocery store is about 4 to 5 miles away, and I wouldn't think about walking or bicycling."--Female, Age 40-49, Pleasanton

“Everything for us is like almost walking distance of where we go. I never drive."--Male, Age 30, SF Fillmore Street


"Living here in the suburbs...you get really used to parking not being an issue. Wherever you go, you can park."--Female, Age 60-69, South San Francisco


"I travel less. Because I know coming home, there won't be parking."--Female, Age 40-49, SF Third Street
















Quotes: Enjoyment

• “I have noticed that my stress level has gone down since I have walked and bussed more than I drive.” --Male, Age 30, Burlingame

• “It’s a beautiful block with beautiful trees, and I love walking down that street. I wish every street had trees.” --Female, Age 40-49, San Francisco Third Street

• People bicycle “for exercise, for convenience, and for fun.” --Female, Age 20-29, San Francisco Market Street

• “[Bicycling is] a good way to get some exercise, and it’s less pollution…part of it may be that it’s kind of trendy.” --Male, Age 30, San Francisco Fillmore Street















Quotes: Habit

• “I think that getting into the habit of [walking and bicycling] early makes one I think more likely to continue doing them into their later years.” --Male, Age 55, San Francisco Third Street

• “I’m used to using a car. It’s easy. I can get in; I can park in my driveway at night. I get in, I go.” --Male, Age 55, San Francisco Third Street

• “The younger ones—a lot of them drive their cars to high school or to college…That’s probably all they know, really.” --Male, Age 30, Burlingame

• “In the United States actually, we tend to think about the car being the first and the only mode of transportation, and we need to get out of that mindset.” --Female, Age 40-49, Pleasanton

1) Awareness & Availability(Institute individualized marketing programs, bicycle give-away

programs, community-wide education campaigns, Bike to Work Day, Walk to School Week, and other encouragement programs)

5) Habit(Offer information to people who move & change job locations; Explore roadway and

parking pricing strategies)

2) Basic Safety & Security(Construct sidewalks and bicycle paths; Improve pedestrian

crossings; Designate roadway space for bicycles; Design roadways for slower automobile speeds; Educate pedestrians, bicyclists, and drivers on safe behaviors; Enforce traffic laws; Improve roadway

lighting; Provide secure bicycle parking )

3) Convenience & Cost(Allow higher population and employment densities and a finer mix of land uses; Reduce building setbacks; Reduce automobile lanes;

Reduce off-street parking and provide market-rate on-street parking)

4) Enjoyment(Plant street trees and landscaping; Zone for ground-level stores

adjacent to sidewalks; Design public streets for slow-speed activities; Promote environmental & social benefits of walking and bicycling)

Strategies to Increase Walking & BicyclingPedestrian, Bicycle,

Transit, or Automobile?

1) Awareness & Availability

Bike to Work Week; Bike Month Walk to School Day

Bicycle Give-Aways

Photo Credit: City of Rockville, MD

Photo Credit: Jennifer Toole

City of Portland, OR

Individual Marketing


Wayfinding Signs; Walk & Bicycle Maps

Photo Credit: City of Seattle

2) Basic Safety & Security

Safer Street & Intersection Facilities Pedestrian Crossing Safety Treatments

Designated Space for Bicycling


Driver, Pedestrian, & Bicyclist Education

Credit: DC, VA, MD Street Smart


Enforcement of Crime & Traffic ViolationsBetter Lighting at Night

Photo Credit: Dan BurdenPhoto Credit: Ron Bloomquist, pedbikeimages.org


Decrease distances to activities by changing land uses

Photo Credit: Bing Maps









Provide bicycle parking


Provide bicycle parking

Limit and price automobile parking

4) Enjoyment

Advertise social & environmental benefitsProvide comfortable facilities

Plant street trees

Photo Credit: Cynthia Cluck

5) Habit

Influence from family & close friendsSafe Routes to School programs

Price changes; Home & work changes

Photo Credit: Associated Press

Survey Support for the Theory

Relationship within Mode Choice Decision Process Supported?


� Bike available � More likely to consider bicycle Yes***

� Auto available � More likely to consider automobile Yes***

5) Habit

� Typically walk � More likely to walk Yes***

� Typically bike � More likely to bike Yes***

Difference between binomial proportions : *** indicates p < 0.05; ** indicates 0.05 < p < 0.10;

* indicates 0.10 < p < 0.20; (Yes) = Relationship is found in survey data, but not statistically-significant.

Four Contributions

1) Controlled for attitudes, perceptions, and local environment factors within model structure

2) Identified local environment characteristics associated with walking and bicycling

3) Documented & analyzed short pedestrian trips

4) Developed theory to explain pedestrian & bicycle mode choice process

Four Contributions








Automobile





Automobile







Automobile


Attitude Characteristics

(enjoy walking, environmentalist)

Perception Characteristics (crash risk, crime risk)



Mode Share Forecast (N = 388)

0%

10%

20%

30%

40%

50%

60%

70%

Less Multimodal Base More Multimodal

Mo

de

Sh

are

fo

r To

urs

to

an

d f

rom

Sh

op

pin

g D

istr

icts

1) Less Street Tree Canopy

2) Larger Parking Lots

3) Lower Population &

Employment Density

1) More Street Tree Canopy

2) Smaller Parking Lots

3) Higher Population &

Employment Denisty

Transit

Walk

Auto


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Mo

de

Sh

are

fo

r Tr

ips

Wit

hin

Sh

op

pin

g D

istr

ict

1) Free Street Parking

2) Faster Speed Limit

3) Separated Stores

4) More Driveway Crossings

1) Metered Street Parking

2) Slower Speed Limit

3) Stores w/ Shared Parking

4) Fewer Driveway Crossings

Walk

Auto


0%

10%

20%

30%

40%

50%

60%

70%

80%


Mo

de

Sh

are

fo

r Tr

ips

Wit

hin

Sh

op

pin

g D

istr

ict

1) Lower Population &

Employment Density

2) Larger Parking Lots

3) No Street Bicycle Facilities

4) No Bicycle Parking

5) Free Street Auto Parking

1) Higher Population &

Employment Density

2) Smaller Parking Lots

3) New Street Bicycle Facilities

4) New Bicycle Parking

5) Metered Auto Parking

Bicycle

Transit

Walk

Auto

Four Contributions





Significant Local Environment Characteristics in Models

Associated with Walking Associated with Bicycling

Population Density (+)Employment Density (+)

Employment Density (+)

Tree Canopy (+)Multi-Store Shopping Complex (+)Metered Street Parking (+)Survey Store Parking Spaces (-)Driveway Crossings (-)Speed Limit (-)

Bicycle Facilities (+)Bicycle Parking (+)Metered Street Parking (+)Survey Store Parking Spaces (-)

Perceived Crime (-) Perceived Crime (-)

Significant Local Environment Characteristics in Models

Associated with Walking Associated with Bicycling

Population Density (+)Employment Density (+)

Employment Density (+)

Tree Canopy (+)Multi-Store Shopping Complex (+)Metered Street Parking (+)Survey Store Parking Spaces (-)Driveway Crossings (-)Speed Limit (-)

Bicycle Facilities (+)Bicycle Parking (+)Metered Street Parking (+)Survey Store Parking Spaces (-)

Perceived Crime (-) Perceived Crime (-)

Four Contributions





Mode Share Measures for All Survey Respondents

Mode Share Measures for All Survey Respondents

Respondent Pedestrian Path DensityUrban Core Shopping District (Market Street, San Francisco)

Urban Core Shopping District (Mission Street, San Francisco)

Respondent Pedestrian Path Density

Suburban Main Street Shopping District (Burlingame)


Suburban Main Street Shopping District (Richmond)


Suburban Thoroughfare Shopping District (Brentwood)


Suburban Thoroughfare Shopping District (El Cerrito)


Four Contributions





5) Habit(People are more aware of the mode when

they use it; People are less likely to consider modes that they do not use)

2) Basic Safety & Security(People perceive that the mode will provide a basic level of

safety from traffic collisions and security from crime )

3) Convenience & Cost (People calculate that the mode will get them to an activity in

an acceptable amount of time, cost, and effort)

4) Enjoyment(People derive satisfaction from their own physical, mental, or emotional response to the mode and/or its benefit to society)


1) Awareness & Availability(People are aware of the mode and have it available as an

option to travel to an activity)

Theory of Routine Mode Choice DecisionsSocioeconomic Factors



Important Considerations

• Small bicycle sample size

• Fair weather conditions only

• Tour purpose not controlled in secondary model (N=959)

• Exploratory-level statistical significance

• Cross-sectional data

• Mode choice theory based on San Francisco Bay Area subjects and applies to routine travel

Thank you

• United States Environmental Protection Agency

• University of California Transportation Center

• Advisors: Robert Cervero, Elizabeth Deakin, Elizabeth Macdonald, Joan Walker

• Research assistants: Carlos Velasquez & Melissa Chinchilla

• Walgreens Corporation: Bill Hose, Michael O’Brien

Questions?

Walgreens is Everywhere

Previous discrete choice modeling studies with pedestrian & bicycle modes

• Purvis (1997)

• Bowman & Ben-Akiva (2000)

• Jonnalagadda et al. (2001)

• Berrigan & Troiano (2002)

• Cervero & Duncan (2003)

• Walton & Sunseri (2007)

• Ryley (2008)

• Kim & Ulfarsson (2008)

• Handy et al. (2010)

Value of Time (N=388)

• Analysis of tours that had all stops within shopping district (½-mile of store)

• Included travel time and out-of-pocket cost in model instead of tour distance, metered parking, zero vehicles & bus pass

• Value of time

– Automobile tours = $14.41/hour

– Public transit tours = $9.23/hour

– BATS 1990 shopping trips in 2009 dollars = $10.90/hour

Bicycle Facility Tradeoffs (N=959)

• Analysis of all respondent tours (not just to and from shopping district)

• Value of bicycle facilities

– Each additional mile of bicycle facilities in the shopping district was associated with respondents bicycling 1.6 miles further

– Each additional bicycle parking space at the survey store was associated with respondents bicycling 0.5 miles further

Automobile Facility Tradeoffs (N=286)

• Analysis of walk vs. drive within shopping districts

• Value of automobile facilities

– Shopping districts with metered parking were associated with respondents walking 2.5 minutes longer

– 10 fewer commercial driveway crossings along the main shopping district roadway were associated with respondents walking 1.0 minutes longer

Auto Mode Share Under Different Scenarios

40%

45%

50%

55%

60%


Au

tom

ob

ile

Mo

de

Sh

are

fo

r S

am

ple

of

Su

rve

y R

esp

on

de

nts

Double Population

& Employment Density

Half Population


Double Parking Lot

Automobile Spaces

Half Parking Lot

Automobile Spaces

Half Street

Tree Canopy

Double Street

Tree Canopy

N = 388

Walk Mode Share Under Different Scenarios

35%

40%

45%

50%

55%


Wa

lk M

od

e S

ha

re f

or

Sa

mp

le o

f S

urv

ey R

esp

on

de

nts

Double Population


Half Population


Double Parking Lot

Automobile Spaces

Half Parking Lot

Automobile Spaces

Half Street

Tree Canopy

Double Street

Tree Canopy

N = 388

Transit Mode Share Under Different Scenarios

0%

5%

10%

15%

20%


Tra

nsi

t M

od

e S

ha

re f

or

Sa

mp

le o

f S

urv

ey R

esp

on

de

nts

Double Population


Half Population


Double Parking Lot

Automobile Spaces

Half Parking Lot

Automobile Spaces

Half Street

Tree Canopy

Double Street

Tree Canopy

N = 388

Attitudes & Perceptions Related to Walking

Primary Tour Mode

Pedestrian

Bicycle

Transit

Automobile

Attitudes & Perceptions Related to Bicycling

Primary Tour Mode

Pedestrian

Bicycle

Transit

Automobile

Respondents who Perceived High Bicycle Crash Risk

33%36%

22%

15%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Urban Core Suburban Main Street Suburban Thoroughfare Suburban Shopping Center

Su

rve

y R

esp

on

de

nts

wh

o P

erc

eiv

ed

Bic

ycl

ing

in

Sh

op

pin

g D

istr

ict

to h

av

e H

igh

Cra

sh R

isk

Respondents who Considered Walking or Bicycling to Store

80%

62%

35%

49%

12%15%

21%

27%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Su

rve

y R

esp

on

de

nts

wh

o C

on

sie

red

Wa

lkin

g o

r B

icy

clin

g t

o S

urv

ey

Sto

re

Considered Walking

Considered Bicycling

Respondents who Enjoyed Walking or Bicycling

94%

87%

84% 84%

64% 63%

58% 55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Su

rve

y R

esp

on

de

nts

wh

o R

ep

ort

ed

En

joy

ing

Wa

lkin

g o

r B

icy

clin

g

Enjoyed Walking

Enjoyed Bicycling

How Do People Choose a Travel Mode? Factors Associated with Routine Walking & Bicycling

Documents

travel mode

routine travel

incomeattitude characteristics

participant characteristics

shopping trip mode share

suburban shopping center

suburban main street

tour tripchain