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Dr. Chandra Bhat The University of Texas at Austin. Austin Commuter Survey: Findings and Recommendations. Note: This presentation is in slideshow mode. Please follow the and buttons. THE CONTEXT.

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dr chandra bhat the university of texas at austin
Dr. Chandra Bhat

The University of Texas at Austin

Austin Commuter Survey: Findings and Recommendations

Note: This presentation is in slideshow mode. Please follow the and buttons.

the context
THE CONTEXT
  • An average Austin area rush hour commuter spends 50 hours annually just sitting in traffic and takes 30% longer to get from point A to point B.
  • Traffic delay per rush hour traveler has risen by 250% in the past decade in Austin
  • Need to design and implement bold, creative, coordinated and proactive strategies
slide3
Congestion alleviation strategies may be broadly grouped into the following categories:
    • Increase supply/vehicular carrying capacity of roadways
    • Influence vehicular traffic patterns
    • Change commuter travel patterns
  • Accurate analysis of the potential effectiveness of these strategies is critical
  • This requires examination of commuter travel behavior – commute periods being the most congested times of the weekday
report objectives
REPORT OBJECTIVES
  • Examine demographic, employment and overall travel characteristics of Austin area commuters and analyze how these characteristics impact commute travel choices and perceptions
  • Develop a framework for evaluating the effect of alternative strategies on commute mode choice to enable policy analysis
  • Highlight the need to identify and implement a coordinated, balanced, multi-modal, and integrated land use-transportation plan to control traffic
austin commuter survey acs
AUSTIN COMMUTER SURVEY (ACS)
  • Endorsed by Clean Air Force (CAF) of Central Texas and supported by NuStats Inc.
  • Web-based survey hosted by UT Austin
  • Publicity and recruitment
    • CAF email messages to Austin area employers
    • Radio and TV media
    • Austin Chamber of Commerce article in newsletter
    • Color posters at strategic public places
    • Posters handed out to individuals at public locations
survey content
SURVEY CONTENT

Screening

Introduction and Travel opinions

Work-related characteristics

Commute travel experience by:

Bus

Walk

Bicycle

Drive

Share-ride

Commute and midday stop-making

Stated preference games

Demographic data

data preparation
DATA PREPARATION
  • Geo-coded home and work locations
  • Overlaid geo-coded locations with CAMPO’s zonal configuration to assign appropriate zones
  • Appended LOS attributes to each individual’s record – extracted from CAMPO’s network skims
  • Ensured consistency through several cleaning and screening steps
  • Final sample
  • 699 commuters who reside and work within 3-county area of Hays, Williamson and Travis
  • Weighted by race, income, gender, household size, household type and commute travel mode choice
demographic and socio economic characteristics
DEMOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICS
  • Household characteristics
  • Individual characteristics
    • Demographic characteristics
    • Socio-economic characteristics
    • Work characteristics
commute travel characteristics
COMMUTE TRAVEL CHARACTERISTICS
  • Travel Perceptions
  • Commute Distance
  • Nonwork stops
  • Commute Mode
  • Commute Duration
  • Commute Time-of-Day
conclusions
CONCLUSIONS

The “Big Picture” Findings

  • 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
conclusions11
CONCLUSIONS
  • Need to also focus attention on modifying work arrangements as a means to alleviating congestion – currently only 2.5% of the commuters telework on any given day
  • Reliability of travel time plays an important role in commute mode choice decisions – particularly for commuters with an inflexible work schedule
  • Overall, several Austin area employees do enjoy the routine of traveling to their work place
conclusions12
CONCLUSIONS

Specific Findings on Commuter Rail and Tolls

  • Commuters have a more positive image of a potential CRT mode than the current bus mode
  • Percentage of commuters using a potential CRT system will be dependent upon the service characteristics; under assumptions that are not unreasonable, a new CRT mode is predicted to capture 1.5% of overall mode share if 10% of the commuter population have access to CRT and 4.1% of overall mode share if 25% of the commuter population have access to CRT
  • Within the group of individuals for whom CRT is an available alternative, CRT is predicted to capture about 15% of the mode share
conclusions13
CONCLUSIONS
  • 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
conclusions14
CONCLUSIONS

Other Findings about Austin Area Commuters

  • The household structures of Austin area commuters are rather diverse - only 13% of commuter households are “traditional” family households
  • The average household income ($65,700) is higher than the national average ($58,000)
  • A large number of commuters have internet access at home (84%)
  • Average motorized vehicle ownership level of 2 per household
conclusions15
CONCLUSIONS
  • 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
household size and structure
Household size and structure

2-person hhs

3 and 4 person hhs

Distribution of household size

Distribution of household types

household income
Household income

Low income

< $35,000 32%

Medium income

$35,000-$95,000 48%

High income

> $95,000 20%

housing characteristics
Housing characteristics

Distribution of housing tenure type

Distribution of residence type

motorized vehicle ownership
Motorized vehicle ownership

Auto-ownership of commuters

Average vehicle ownership by residence zone population density

Average vehicle ownership by income level

motorized vehicle type and age
Motorized vehicle type and age

Average age of vehicles by vehicle type

Vehicle types used for commute

Vehicle types owned by commuter households

demographic characteristics
Demographic characteristics

Racial composition of the commute population

Gender of the commute population

Marital status of commuters

Age distribution of commuters

socio economic characteristics
Socio-economic characteristics

Distribution of highest level of education

Distribution of personal income

work characteristics
Work characteristics

Employment status

Length of time working in Austin

Employer type

work start time distribution
Work start time distribution

Work start time distribution

work end time distribution
Work end time distribution

Work end time distribution

work schedule flexibility
Work schedule flexibility

Work start time flexibility

Work end time flexibility

teleworking percentages
Teleworking percentages

Flexible arrival and/or departure times

Educational Instit.

Part-time employed

Inflexible arrival and/or departure times

Non-educational Instit.

Full-time employed

travel perceptions
Travel perceptions

Perception of level of congestion

during commute

Characterization of the commute

trip

perception of level of congestion by commute distance
Perception of level of congestion by commute distance

Highway

not used

Short Commute (≤7 miles)

Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)

Highway

used

Short Commute (≤7 miles)

Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)

characterization of commute trip by commute duration
Characterization of commute trip by commute duration

Highway

not used

Short Commute (≤7 miles)

Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)

Highway

used

Short Commute (≤7 miles)

Medium Commute (7.01 – 15 miles)

Long Commute (>15 miles)

travel perceptions34
Travel perceptions

Ease of travel to non-work activities around home

commute distance
Commute distance

Distribution of commute distance

nonwork stops weekly
Nonwork stops – weekly

Distribution of weekly commute stop-making

Distribution during

evening commute

Distribution during

morning commute

slide37

Distribution of weekly midday stop-making

Non-home trips

Return home trips

slide38

Degree of stop-making during the week

Commute stop-making

Midday stop-making

nonwork stops daily
Nonwork stops - daily

Distribution of number of activity stops

commute mode
Commute mode

Distribution of mode use over the week

slide43

Mode split by weekly

commute stop-making

propensity

Mode split by weekly

midday stop-making

propensity

slide44
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
slide45
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 duration

Commute durations by mode

commute time of day
Commute Time-of-Day

Distribution of the time

of the morning commute

Distribution of the time

of the evening commute