Austin Commuter Survey: Findings and Recommendations

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Austin Commuter Survey Findings and
Recommendations
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• Dr. Chandra Bhat
• The University of Texas at Austin

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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

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• 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

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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

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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

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SURVEY CONTENT
Screening
Introduction and Travel opinions
Work-related characteristics
Commute travel experience by
Drive
Share-ride
Bus
Walk
Bicycle
Commute and midday stop-making
Stated preference games
Demographic data
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DATA PREPARATION

• Geo-coded home and work locations
• Overlaid geo-coded locations with CAMPOs zonal
  configuration to assign appropriate zones
• Appended LOS attributes to each individuals
  record extracted from CAMPOs 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

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DEMOGRAPHIC AND SOCIO-ECONOMIC CHARACTERISTICS

• Household characteristics
• Individual characteristics
• Demographic characteristics
• Socio-economic characteristics
• Work characteristics

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COMMUTE TRAVEL CHARACTERISTICS

• Travel Perceptions
• Commute Distance
• Nonwork stops
• Commute Mode
• Commute Duration
• Commute Time-of-Day

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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 todays congestion
  levels into the future by focusing on only one
  strategy

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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

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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

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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

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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

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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

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THANK YOU!
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Household size and structure
2-person hhs
3 and 4 person hhs
Distribution of household size
Distribution of household types
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Household income
Low income lt 35,000 32 Medium income
35,000-95,000 48 High income gt 95,000 20
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Housing characteristics
Distribution of housing tenure type
Distribution of residence type
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Residential location
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Internet access from residence
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Motorized vehicle ownership
Auto-ownership of commuters
Average vehicle ownership by residence zone
population density
Average vehicle ownership by income level
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Motorized vehicle type and age
Average age of vehicles by vehicle type
Vehicle types used for commute
Vehicle types owned by commuter households
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Demographic characteristics
Racial composition of the commute population
Gender of the commute population
Marital status of commuters
Age distribution of commuters
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Socio-economic characteristics
Distribution of highest level of education
Distribution of personal income
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Work characteristics
Employment status
Length of time working in Austin
Employer type
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Work start time distribution
Work start time distribution
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Work end time distribution
Work end time distribution
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Work schedule flexibility
Work start time flexibility
Work end time flexibility
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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
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Travel perceptions
Perception of level of congestion during commute
Characterization of the commute trip
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Perception of level of congestion by commute
distance
Highway not used
Short Commute (7 miles)
Long Commute (gt15 miles)
Medium Commute (7.01 15 miles)
Highway used
Long Commute (gt15 miles)
Medium Commute (7.01 15 miles)
Short Commute (7 miles)
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Characterization of commute trip by commute
duration
Highway not used
Short Commute (7 miles)
Long Commute (gt15 miles)
Medium Commute (7.01 15 miles)
Highway used
Long Commute (gt15 miles)
Medium Commute (7.01 15 miles)
Short Commute (7 miles)
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Travel perceptions
Ease of travel to non-work activities around home
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Commute distance
Distribution of commute distance
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Nonwork stops weekly
Distribution of weekly commute stop-making
Distribution during evening commute
Distribution during morning commute
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Distribution of weekly midday stop-making
Non-home trips
Return home trips
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Degree of stop-making during the week
Commute stop-making
Midday stop-making
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Nonwork stops - daily
Distribution of number of activity stops
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Distribution of stop-making by purpose and time
period
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Commute mode
Distribution of mode use over the week
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Commute mode choice on most recent work day
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Mode split by weekly commute stop-making propensit
y
Mode split by weekly midday stop-making propensity
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• 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

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• 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

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Commute duration
Commute durations by mode
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Commute Time-of-Day
Distribution of the time of the morning commute
Distribution of the time of the evening commute