This study examines the value of travel time savings for carshare users in Sydney through a revealed preference study of GPS data from a carshare program. The study compares travel times on toll roads versus untolled alternatives to isolate the value of time. The analysis finds a value of expected travel time savings of $9.63/hour for carshare users, which is over 50% lower than values found in other cities. This lower value may be because carshare users have a lower value of time than the average motorist. The study is exploring incorporating risk parameters into the model since travel times are stochastic.

1. Value of Time of Carshare Users in Sydney
Revealed Preference Study of GPS Data
Dr. V.V. Dixit | John Trieu | Sisi Jian | Xun Li

2. Introduction – Why Study Value of Time?
• Economic cost of congestion
– $3.9 billion to Sydney in 2005
(BITRE, 2007)
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3. This Study – Value of Time in Sydney
• Goal
– Value of time for motorists in Sydney
• Why?
– Important consideration in Congestion Charging
schemes
– Important input to Cost-Benefit Analysis of
transport projects
• Economic “benefit” of travel time savings
• How?
– Revealed preference study of GPS data
– Data provided by carshare program in Sydney
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4. Value of Travel Time Savings (1)
• Value of Time
– Not directly measurable
– Minimum travel time, regardless of mode and
route
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5. Value of Travel Time Savings (2)
• Need to consider the “Value of Travel Time
Savings”
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6. What is a Revealed Preference study?
• Collection of raw data (e.g. GPS logs)
• Convert data to trips
• Determine relationships between trip
decisions and factors influencing choices
• The preferences of drivers are “Revealed”
– Preferences are not explicitly “Stated” by drivers
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7. Past Studies
• Different locations = Different characteristics
– Los Angeles
– Brisbane
• Stated Preference = Controlled Experiment
(Hensher, Greene and Li, 2011)
– Artificial environment
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8. Delineating Trips – Overview
• GPS Logs = Data Points
– Need trips
• Trip Identification – Trip Ends
– (1) Time between GPS data points
– (2) Time with zero movement
– (3) Significant changes in direction
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9. Delineating Trips – (1) Time between GPS data points
• Large amount of time (e.g. 2 Days)
– Trip has ended
• Cut-off = 20 minutes
– Timeout of in-car GPS units
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10. Delineating Trips – (2) Time with zero movement
• Based upon maximum signal cycle time in
Sydney
– 150 seconds during peak periods
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11. Delineating Trips – (3) Significant changes in direction
• U-turns
• Turns greater than 90 degrees
– Sensitivity testing undertaken on the
change in heading
– No change in number of trips identified
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12. This Study
• Focal Point
– Toll Road versus Untolled Alternative
– Can isolate value of time
• Explicit cost for toll road
• Stochastic travel time saving
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13. Study Area (1) – M2 vs Epping Road
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14. Study Area (2) – M4 vs Parramatta Road
• Used as a “control” for the study
– Equivalent to “no treatment” scenario in
experiments
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15. This Study
• Other variables / covariates
– Age / Experience
– Preferred Travel Mode
– Car Ownership
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16. Modelling – Value of Expected Travel Time Savings
• Regression Modelling
– Binary Logit Model
Choice of Motorway or Arterial
• Value of Expected Travel Time Savings (VETTS)
– $9.63 / hour
• Comparison VETTS
– Los Angeles, USA: $21.46 / hour
– Brisbane, Australia: $17.60 / hour
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17. Modelling – Value of Expected Travel Time Savings
• Value of Expected Travel Time Savings (VETTS)
– $9.63 / hour
• VETTS result is more than 50% less than in
other cities
• Reason for difference
– VETTS identified is specific to Carshare Users
– Carshare Users are suspected of having lower
VETTS compared to average motorist
• Cannot be used as a representative sample group
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18. Further Studies
• Risk aversion
– Travel times are stochastic
– Need to include risk parameter
• Model including risk parameter is ongoing
– Risk models considered:
• Constant Absolute Risk Aversion (CARA)
• Constant Relative Risk Aversion (CRRA)
• Ongoing / Not yet finalised
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19. Questions?
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