Examining the Relationship between Drivers’ Anticipated Travel Time and Previous Experienced Travel Times
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 3
Abstract
Travel time reliability refers to the day-to-day variability of trip travel times. There is a belief that there is a cost associated with unreliability and this cost can be quantified as a function of the difference between the travel time that was experienced and the travel time that was anticipated. In the realm of public transport systems, the anticipated travel time is essentially the scheduled travel time and is therefore easy to compute. However, for personal auto modes, it is not clear how the anticipated travel time should be computed. This paper focuses on addressing the following two questions: What is the relationship between the distribution of the travel times that travelers experience and the travel times that travelers anticipate for a future trip? What effect do unusually long travel times have on this anticipated travel time? The authors explored both questions through a stated preference survey that was distributed to over 3,000 individuals. Just over 300 valid responses were received, and on the basis of the survey results, a two-stage model for estimating the anticipated travel time as a function of the experienced travel time distribution was formulated and calibrated. The proposed model can be applied to travel times obtained from simulation models or from field observations.
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Acknowledgments
The authors would like to thank Professor Derek Koehler for contributing the ideas related to the social psychology; Mr. Ahmad Tanehkar for his assistance in designing the survey; and the executive committee of the Canadian Institute of Transportation Engineers (CITE) for their help in distributing the survey.
References
Avineri, E., and Prashker, J. N. (2006). “The impact of travel time information on travelers’ learning under uncertainty.” Transportation, 33(4), 393–408.
Bogers, E. A. (2009). Traffic information and learning in day-to-day route choice, Netherlands TRAIL Research School, Delft, Netherlands.
Boyles, S. D., Voruganti, A., and Waller, S. T. (2010). Quantifying travel time variability in transportation networks, Southwest Region Univ. Transportation Center, Austin, TX.
Cambridge Systematics. (2013). “Analytical procedures for determining the impacts of reliability mitigation strategies.”, Transportation Research Board, Washington, DC.
Chang, G., and Mahmassani, H. S. (1988). “Travel time prediction and departure time adjustment behavior dynamics in a congested traffic system.” Transp. Res. Part B, 22(3), 217–232.
Do, M., and Kobayashi, K. (2000). “Hypothesis testing on divers’ rational expectations: An experimental approach.” KSCE J. Civ. Eng., 4(1), 1–10.
Fujii, S., and Kitamura, R. (2000). “Anticipated travel time, information acquisition, and actual experience: Hanshin Expressway route closure, Osaka-Sakai, Japan.” Transp. Res. Rec., 1725(1), 79–85.
Hahn, U. (2014). “Experiential limitation in judgment and decision.” Top. Cognit. Sci., 6(2), 229–244.
Jin, L., and McLeod, D. S. (2013). “Comparison of travel time indexes and other travel time reliability measures using Florida freeway spot speed data.” TRB 92nd Annual Meeting Compendium of Papers, Transportation Research Board, Washington, DC, 17.
Lam, T. C., and Small, K. A. (2001). “The value of time and reliability: Measurement from a value pricing experiment.” Transp. Res. Part E, 37(2), 231–251.
Mahmassani, H. S., and Chang, G. (1985). “Dynamic aspects of departure-time choice behavior in a commuting system: Theoretical framework and experimental analysis.” Transp. Res. Rec., 1037, 88–101.
Muth, J. F. (1961). “Rational expectations and the theory of price movements.” Econometrica, 29(3), 315–335.
National Academies of Sciences, Engineering, and Medicine. (2007). “Guide to effective freeway performance measurement.” National Academies Press, Washington, DC.
National Academies of Sciences, Engineering, and Medicine. (2013). Transit capacity and quality of service manual, 3rd Ed., National Academies Press, Washington, DC.
National Academies of Sciences, Engineering, and Medicine. (2014). “Incorporating travel time reliability into the highway capacity manual.” National Academies Press, Washington, DC.
Trope, Y., and Liberman, N. (2010). “Construal-level theory of psychological distance.” Psychol. Rev., 117(2), 440–463.
Van Lint, J., van Zuylen, H. J., and Tu, H. (2008). “Travel time unreliability on freeways: Why measures based on variance tell only half the story.” Transp. Res. Part A, 42(1), 258–277.
VISSIM [Computer software]. PTV AG, Karlsruhe, Germany.
Warffemius, P. (2013). “The social value of shorter and more reliable travel times.”, KiM Netherlands Institute for Transport Policy Analysis, The Hague, Netherlands.
Information & Authors
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 3 • March 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Feb 6, 2017
Accepted: Sep 12, 2017
Published online: Jan 11, 2018
Published in print: Mar 1, 2018
Discussion open until: Jun 11, 2018
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