Sep 22, 2004

Austin Commuter Austin Commuter Survey: Findings and Survey: Findings and RecommendationsRecommendations

Dr. Chandra BhatDr. Chandra Bhat

The University of Texas at The University of Texas at AustinAustin

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THE CONTEXTTHE CONTEXT

An average Austin area rush hour commuter An average Austin area rush hour commuter spends 50 hours annually just sitting in traffic spends 50 hours annually just sitting in traffic and takes 30% longer to get from point A to and takes 30% longer to get from point A to point B.point B.

Traffic delay per rush hour traveler has risen by Traffic delay per rush hour traveler has risen by 250% in the past decade in Austin250% in the past decade in Austin

Need to design and implement bold, creative, Need to design and implement bold, creative, coordinated and proactive strategiescoordinated and proactive strategies

Congestion alleviation strategies may be Congestion alleviation strategies may be broadly grouped into the following categories:broadly grouped into the following categories:

Increase supply/vehicular carrying capacity of Increase supply/vehicular carrying capacity of roadwaysroadways

Influence vehicular traffic patternsInfluence vehicular traffic patterns Change commuter travel patternsChange commuter travel patterns

Accurate analysis of the potential effectiveness Accurate analysis of the potential effectiveness of these strategies is criticalof these strategies is critical

This requires examination of commuter travel This requires examination of commuter travel behavior – commute periods being the most behavior – commute periods being the most congested times of the weekdaycongested times of the weekday

REPORT OBJECTIVESREPORT OBJECTIVES

ExamineExamine demographic, employment and overall demographic, employment and overall travel characteristics of Austin area commuters travel characteristics of Austin area commuters and and analyzeanalyze how these characteristics impact how these characteristics impact commute travel choices and perceptionscommute travel choices and perceptions

Develop a frameworkDevelop a framework for evaluating the effect for evaluating the effect of alternative strategies on commute mode of alternative strategies on commute mode choice to enable policy analysischoice to enable policy analysis

Highlight the needHighlight the need to identify and implement a to identify and implement a coordinated, balanced, multi-modal, and integrated coordinated, balanced, multi-modal, and integrated land use-transportation plan to control trafficland use-transportation plan to control traffic

AUSTIN COMMUTER SURVEY AUSTIN COMMUTER SURVEY (ACS)(ACS)

Endorsed by Clean Air Force (CAF) of Central Endorsed by Clean Air Force (CAF) of Central Texas and supported by NuStats Inc.Texas and supported by NuStats Inc.

Web-based survey hosted by UT AustinWeb-based survey hosted by UT Austin

Publicity and recruitmentPublicity and recruitment CAF email messages to Austin area employersCAF email messages to Austin area employers

Radio and TV mediaRadio and TV media

Austin Chamber of Commerce article in newsletterAustin Chamber of Commerce article in newsletter

Color posters at strategic public placesColor posters at strategic public places

Posters handed out to individuals at public locationsPosters handed out to individuals at public locations

SURVEY CONTENTSURVEY CONTENT

ScreeningScreening

Introduction and Travel opinionsIntroduction and Travel opinions

Work-related characteristicsWork-related characteristics

Commute travel experience by:Commute travel experience by:

DriveDrive Share-rideShare-ride BusBus WalkWalk BicycleBicycle

Stated preference gamesStated preference games

Demographic dataDemographic data

Commute and midday stop-makingCommute and midday stop-making

DATA PREPARATIONDATA PREPARATION

Geo-coded home and work locationsGeo-coded home and work locations Overlaid geo-coded locations with CAMPO’s zonal Overlaid geo-coded locations with CAMPO’s zonal

configuration to assign appropriate zonesconfiguration to assign appropriate zones Appended LOS attributes to each individual’s record – Appended LOS attributes to each individual’s record –

extracted from CAMPO’s network skimsextracted from CAMPO’s network skims Ensured consistency through several cleaning and Ensured consistency through several cleaning and

screening stepsscreening steps

Final sampleFinal sample• 699 commuters who reside and work within 3-699 commuters who reside and work within 3-

county area of Hays, Williamson and Traviscounty area of Hays, Williamson and Travis• Weighted by race, income, gender, household Weighted by race, income, gender, household

size, household type and commute travel mode size, household type and commute travel mode choicechoice

DEMOGRAPHIC AND SOCIO-DEMOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICSECONOMIC CHARACTERISTICS

Household characteristicsHousehold characteristics

Individual characteristicsIndividual characteristics

Demographic characteristicsDemographic characteristics

Socio-economic characteristicsSocio-economic characteristics

Work characteristicsWork characteristics

COMMUTE TRAVEL COMMUTE TRAVEL CHARACTERISTICSCHARACTERISTICS

Travel PerceptionsTravel Perceptions

Commute DistanceCommute Distance

Nonwork stopsNonwork stops

Commute ModeCommute Mode

Commute DurationCommute Duration

Commute Time-of-DayCommute Time-of-Day

CONCLUSIONSCONCLUSIONS

Increasing diversity of household structures – increasing participation in nonwork activities during commute and midday

It is important to pursue an integrated and coordinated land-use and transportation plan to address congestion problems

Addressing traffic congestion problems requires a balanced and multimodal transportation plan – infeasible to even maintain today’s congestion levels into the future by focusing on only one strategy

The “Big Picture” FindingsThe “Big Picture” Findings

CONCLUSIONSCONCLUSIONS

Need to also focus attention on modifying work Need to also focus attention on modifying work arrangements as a means to alleviating arrangements as a means to alleviating congestion – currently only 2.5% of the congestion – currently only 2.5% of the commuters telework on any given daycommuters telework on any given day

Reliability of travel time plays an important role Reliability of travel time plays an important role in commute mode choice decisions – in commute mode choice decisions – particularly for commuters with an inflexible particularly for commuters with an inflexible work schedulework schedule

Overall, several Austin area employees do Overall, several Austin area employees do enjoy the routine of traveling to their work enjoy the routine of traveling to their work placeplace

CONCLUSIONSCONCLUSIONS

Commuters have a more positive image of a potential Commuters have a more positive image of a potential CRT mode than the current bus modeCRT mode than the current bus mode

Percentage of commuters using a potential CRT system Percentage of commuters using a potential CRT system will be dependent upon the service characteristics; will be dependent upon the service characteristics; under assumptions that are not unreasonable, a new under assumptions that are not unreasonable, a new CRT mode is predicted to capture 1.5% of overall mode CRT mode is predicted to capture 1.5% of overall mode share if 10% of the commuter population have access to share if 10% of the commuter population have access to CRT and 4.1% of overall mode share if 25% of the CRT and 4.1% of overall mode share if 25% of the commuter population have access to CRTcommuter population have access to CRT

Within the group of individuals for whom CRT is an Within the group of individuals for whom CRT is an available alternative, CRT is predicted to capture about available alternative, CRT is predicted to capture about 15% of the mode share15% of the mode share

Specific Findings on Commuter Rail and TollsSpecific Findings on Commuter Rail and Tolls

CONCLUSIONSCONCLUSIONS

Tolls on highways can be expected to lead to a drop of about 2.5% in the DA mode share on highways for each $1 toll

A $1 toll for the use of all the major highways in the Austin area would lead to a 1.5% reduction in DA mode share across the entire Austin metropolitan area

The average commuter is willing to pay $12 for an hour of commute time savings

CONCLUSIONSCONCLUSIONS

The household structures of Austin area The household structures of Austin area commuters are rather diverse - only 13% of commuters are rather diverse - only 13% of commuter households are “traditional” family commuter households are “traditional” family householdshouseholds

The average household income ($65,700) is The average household income ($65,700) is higher than the national average ($58,000)higher than the national average ($58,000)

A large number of commuters have internet A large number of commuters have internet access at home (84%)access at home (84%)

Average motorized vehicle ownership level of 2 Average motorized vehicle ownership level of 2 per household per household

Other Findings about Austin Area CommutersOther Findings about Austin Area Commuters

CONCLUSIONSCONCLUSIONS

Key facts about Austin area commuters :

67% white, non-Hispanic; 16% Hispanic 57% male avg. personal income $44,650 primarily full-time employed start work 7-9 AM, end work 4-6 PM 10% telework at least occasionally 42% have inflexible work schedules in both arrival & departure;

30% have a flexible work schedule in both arrival & departure majority of the commuters (72%) live within 15 miles from work

Net result of high incomes and car ownership, diverse household structures and increased commute/midday stop-making is high DA mode shares

THANK YOU!

Household size and structureHousehold size and structure

Couple Families, 72%

Single Parent Families, 10%

Other, 8%Unrelated/Same-Sex Couple

Families, 10%

23%

30%

19% 17%

7%4%

0%

10%

20%

30%

40%

1 2 3 4 5 Greaterthan 6

23%21%

25%

4%

13%

4%

10%

0%

10%

20%

30%

Singleperson

Couple Nuclearfamily

Singleparent

Returningyoungadult

Roommatesame-sexcouples

Other

Distribution of household size

Distribution of household types

2-person hhs

3 and 4 person hhs

Returning Young Adult

Families, 25%

Nuclear Families, 60%

Single Parent Families, 3%

Household incomeHousehold income

$35,000 - $54,999

17%

$55,000 - $74,999

21%

Less than $35,000

32%

$95,000 - $140,000

12%

Greater than

$140,0008%

$75,000 - $94,999

10%

Low incomeLow income

< $35,000< $35,000 32%32%

Medium incomeMedium income

$35,000-$95,000$35,000-$95,000 48%48%

High incomeHigh income

> $95,000> $95,000 20%20%

Housing characteristics

Rent34%

Own66%

2-4 unit duplex,

townhouse5%

5 or more unit

apartment complex

19%

Other2%

Single family

residence74%

Distribution of housing tenure

type

Distribution of residence type

Residential location

CBD area2%

CBD fringe area26%

urban area20%

suburbia39%

rural area13%

Internet access from residence

Yes87%

No13%

Motorized vehicle ownership

0.1%

34.8%40.0%

18.3%

5.7% 1.1%0%10%20%30%40%50%

0 1 2 3 4 5 ormore

Number of vehicles owned

1.99Rural

2.15Suburban

2.03Urban

1.76CBD Fringe

1.15CBD Core

Avg. Vehicle OwnershipResidence zone type

1.99Rural

2.15Suburban

2.03Urban

1.76CBD Fringe

1.15CBD Core

Avg. Vehicle OwnershipResidence zone type

2.53High Income($95,000 or greater)

2.13Medium Income ($35,000-$94,999)

1.44Low Income (less than $35,000)

Avg. Vehicle OwnershipIncome level

2.53High Income($95,000 or greater)

2.13Medium Income ($35,000-$94,999)

1.44Low Income (less than $35,000)

Avg. Vehicle OwnershipIncome level

Average vehicle ownership by residence zone population density

Average vehicle ownership by income level

Auto-ownership of commuters

Motorized vehicle type and age

SUV20%

Coupe12%

Pickup Truck11%

Other8%

Minivan3%

Sedan47%

Sedan34%

Minivan5%

Other16%

Pickup Truck14% Coupe

11%SUV19%

8.74All

10.03Other

8.75Minivan

8.07Pickup Truck

6.78SUV

11.42Coupe

8.72Sedan

Avg. Age of VehiclesVehicle type

8.74All

10.03Other

8.75Minivan

8.07Pickup Truck

6.78SUV

11.42Coupe

8.72Sedan

Avg. Age of VehiclesVehicle type

Average age of vehicles by vehicle

type

Vehicle types owned by commuter

households

Vehicle types used for commute

Demographic characteristics

Female43%

Male57%

Other17%

Hispanic16%

White non-

Hispanic67%

30 - 39 yrs

24%

22 - 29 yrs

29%

40 - 49 yrs

27%

Greater than 60

yrs3%

50 - 59 yrs

15%

Less than 21

yrs2%

Un-married

43%

Married57%

Gender of the commute population Racial composition of the commute population

Age distribution of commuters Marital status of commuters

Socio-economic characteristics

3%

23%

57%

3%

14%

0%

10%

20%

30%

40%

50%

60%

High school orlesser

Completedtechnical

school

Completedundergraduate

degree

CompletedMaster's (orequivalent)

degree

CompletedPhD (or

equivalentdegree)

$35,000 - $44,999

17%

$25,000 - $34,999

22%

$75,000 - $94,999

5%

Greater than $120K

4%

$95,000 - $120,000

3%

$45,000 - $54,999

12%

$65,000 - $74,999

5%$55,000 - $64,999

10%

Less than $25K22%

Distribution of highest level of education

Distribution of personal income

Local government15%

A private, non-profit, tax exempt

or charitable group21%

Educational institution

16%

Other employer6%

State or Federal government

9%A private, for-

profit company or business

33%

Work characteristics

Full-time85%

Part-time15%

36% 34%

22%

8%

0%

10%

20%

30%

40%

Lessthan 5years

5-15years

15-25years

Morethan 25years

Duration working in Austin

Length of time working in Austin

Employer type

Employment status

Work start time distribution

0.5% 2.3%

21.1%

66.6%

3.7% 2.8% 3.0%

0%

10%

20%

30%

40%

50%

60%

70%

Before 6AM

Between6-6:59

AM

Between7-7:59

AM

Between8-8:59

AM

Between9-9:59

AM

Between10-10:59

AM

Beyond11 AM

Work start time distribution

Work end time distribution

2.3% 5.0%

18.9%

63.1%

4.0% 3.9% 2.8%0%

10%20%30%40%50%60%70%

Before 3PM

Between3-3:59

PM

Between4-4:59

PM

Between5-5:59

PM

Between6-6:59

PM

Between7-7:59

PM

Beyond 8PM

Work end time distribution

Work schedule flexibility

Inflexible53%

Flexible47%

Flexible41%

Inflexible59%

Work start time flexibility Work end time flexibility

Yes14%

No86%

Teleworking percentages

No93%

Yes7%

No73%

Yes27%

No92%

Yes8%

No76%

Yes24%

Part-time employed

Full-time employed

Educational Instit.

Non-educational Instit.

Flexible arrival and/or departure

times

Inflexible arrival and/or departure

times

No92%

Yes8%

Travel perceptions

Somewhat Stressful

52%

Somewhat Enjoyable

31%

Very Stressful

11%

Very Enjoyable

6%

Very Congested

44%

Slightly Congested

37%

Extremely Congested

11%

Not Congested

at all8%

Perception of level of congestionduring commute

Characterization of the commutetrip

Perception of level of congestion by commute distance

28%

72%

40%

60%

30%

70%

51%49%

34%

66%

78%

22%

Short Commute (≤7 miles)

Highway not used

Highway used

Long Commute (>15 miles)Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)Medium Commute (7.01 – 15 miles)Short Commute (≤7 miles)

Not or Slightly Congested Very or Extremely Congested

Characterization of commute trip by commute duration

79%

21%27%

73%35%

65%

`

30%

70%61%

39%

71%

29%

Short Commute (≤7 miles)

Highway not used

Highway used

Long Commute (>15 miles)Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)Medium Commute (7.01 – 15 miles)Short Commute (≤7 miles)

Somewhat or Very Enjoyable Somewhat or Very Stressful

Travel perceptions

Very Easy10%

Very Difficult

3%

Easy57%

Difficult30%

Ease of travel to non-work activities around home

Commute distance

7%4%

15% 14%

17%

22% 21%

0%

10%

20%

30%

2 miles orless

2.01 to 5miles

5.01 to 7miles

7.01 - 10miles

10.01 - 15miles

15.01 - 25miles

Greaterthan 25miles

Distribution of commute distance

Nonwork stops – weeklyNonwork stops – weekly

Distribution during Distribution during

morning commutemorning commute

Distribution during Distribution during

evening commuteevening commute

Distribution of weekly commute stop-makingDistribution of weekly commute stop-making

2 days12%

1 day23%

3 days4%

5 or more days8%

4 days2%

0 days51%

2 days24%

1 day23%

3 days23%

5 or more days8%4 days

5%

0 days17%

Non-home tripsNon-home trips Return home tripsReturn home trips

Distribution of weekly midday stop-Distribution of weekly midday stop-makingmaking

0 days43%

4 days5%

5 or more days3%

3 days14%

1 day19%

2 days16%

2 days4%

1 day10%

3 days3%

5 or more days1%

4 days2%

0 days80%

Commute stop-makingCommute stop-making Midday stop-makingMidday stop-making

Degree of stop-making during the weekDegree of stop-making during the week

Never make a commute stop on any day of the

week15%

Make commute stops on

some (but not all)

days of the week75%

Make one or more

commute stops every day of the

week10%

Never make a midday stop on

any day of the week

39%

Make midday

stops on some (but

not all) days of

the week57%

Make one or more midday stops

every day of the week4%

Nonwork stops - dailyNonwork stops - daily

Distribution of number of activity stopsDistribution of number of activity stops

No. of Percentage of each number of stops during: Activity Stops Before Morning Mid-day Evening After

Morning Commute Commute Evening Commute Commute

0 93.6% 88.4% 72.9% 70.0% 81.2% 1 5.4% 10.6% 11.3% 15.8% 6.0% 2 0.4% 1.0% 10.2% 9.6% 3.2% 3 0.0% 0.0% 3.7% 2.5% 3.2% 4 0.6% 0.0% 1.5% 0.6% 2.4%

>=5 0.0% 0.0% 0.4% 1.5% 4.0%

Activity type

Before During Mid-day During AfterMorning Morning Evening Evening

Go out to eat 0.0 0.0 17.5 3.0 7.2Conduct personal business 1.7 2.9 14.3 9.3 5.7Go shopping (groceries) 0.0 0.3 2.3 14.9 10.6Go shopping (other items) 0.0 0.0 3.7 8.4 10.3Conduct work related to business 1.1 3.6 11.0 0.0 0.1Drop-off/pick-up my children 4.4 6.4 0.9 7.4 0.0Drop-off/pick-up adults in my household 0.0 0.0 0.0 1.0 1.9Other drop-off/pick-up 1.1 0.0 0.0 1.4 0.0Visit friends/family 0.0 0.0 1.3 2.3 7.4Undertake recreational activities 0.0 0.0 0.0 5.0 10.6Just wanted to travel 0.0 0.0 0.0 0.6 0.0

stops of each type in each periodPercentage of individuals making one or more

Distribution of stop-making by purpose and time Distribution of stop-making by purpose and time periodperiod

Commute mode

Distribution of mode use over the week

1.7%0.5%0.5%0.9%2.2%6.9%

2.0%1.2%0.4%1.3%6.3%

76.1%

0.0%

20.0%

40.0%

60.0%

80.0%

Only DriveAlone

Only SharedRide

Only Transit Only Bicycle Only Walk Drive +Shared Ride

Drive +Transit

Drive +Bicycle

Shared Ride+ Walk

Transit +Bicycle

Transit +Walk

All othercombinations

Mode used during week

Bus3.4%

Shared Ride7.4%

Bicycle1.0%

Motorized two-

wheeler0.4%

Walk1.6%

Drive Alone84.6%

Other1.4%

Commute mode choice on most recent work day

Mode split by weeklycommute stop-makingpropensity

Mode split by weeklymidday stop-makingpropensity

Never make a Make one or Totalcommute stop more commute on any day of stops on one

the week or more daysof the week

Drive Alone 69.6% 87.0% 84.4%Shared Ride (with workers) 6.9% 7.5% 7.4%Bus 9.8% 2.5% 3.6%Walk 8.8% 0.5% 1.7%Bicycle 2.0% 0.8% 1.0%Motorized two-wheeler 2.0% 0.2% 0.4%Other 1.0% 1.5% 1.4%

Never make a Make one or Totalmid-day stop more mid-day on any day of stops on one

the week or more daysof the week

Drive Alone 80.7% 87.2% 84.7%Shared Ride (with workers) 11.9% 4.7% 7.4%Bus 1.5% 4.7% 3.4%Walk 3.3% 0.7% 1.7%Bicycle 1.1% 0.7% 0.9%Motorized two-wheeler 0.7% 0.2% 0.4%Other 0.7% 1.9% 1.4%

Important results from Bhat and Sardesai (2004) The ability of auto-use disincentives and hov

incentives to shift commuters away from driving to car/van-pooling and transit modes will be overestimated if the impact of commute and midday stop-making is ignored

Commuters are not only concerned about average travel time but also about the reliability of travel time

The average commuter is willing to pay $12 for an hour of commute savings

Commuters have a more positive image of a potential CRT mode than the current bus mode

Important results from Bhat and Sardesai (2004) contd…

The presence of a grocery store around potential CRT stations acts as an impetus for CRT mode use; however, the presence of a child care center does not provide any stimulation

A new CRT mode is predicted to capture 4.1% of the overall mode share (2.6% from DA)

Within the group of individuals for whom CRT is an available alternative, a shift of 15% from driving to CRT is projected

Tolls on highways can be expected to lead to a drop of about 2.5% in the DA mode share on the highways for each $1 toll

Commute duration

Commute durations by modeMode

Avg. commute duration

Drive-Alone 28.18 Shared-Ride 29.09 Transit 44.04 Bike 28.50 Walk 14.53

Commute Time-of-Day

Start and end

commute between 6-9 AM

76%

Start commute before 6 AM and

end between 6-9 AM

2%

Start and end

commute before 6 AM1%

Start commute

between 6-9 AM and end after

9 AM10%

Start and end

commute after 9 AM

12%

Distribution of the time of the morning commute

Distribution of the time of the evening commute

Start and end

commute between 4-7 PM

74%

Start and end

commute before 4 PM

10%

Start commute

before 4 PM and end between 4-7 PM

3%Start and end

commute after 7 PM

8%

Start commute

between 4-7 PM and end after 7 PM

5%