Estimation of the time-dependency of values of travel time and its reliability from loop detector data
Although the effects of travel time and its reliability have been addressed in a variety of papers concerning pricing policies, most of the existing research is based on the assumption that travelers' preferences are static over a given time interval, such as the morning commuting period. Here, we relax this assumption, assuming rather that travelers' tastes toward the travel time and its reliability vary with time, and examine their time-dependent effects on traveler's route choice decisions. We adopt a mixed logit formulation of route choice behavior as a function of travel time, reliability, and cost. To uncover the values of travel time and its reliability, we introduce an alternative approach to the use of traveler surveys to estimate the model coefficients by determining the parameter set that produces the best match between the aggregated results from the travelers' route choice model and the observed time-dependent traffic volume data from loop detectors. We apply the methodology to loop detector data obtained from the California State Route 91 value-pricing project, and use a genetic algorithm to identify the parameters. The time-dependent values of travel time and values of reliability for the morning commuting period are estimated and their implications on the toll pricing policy are discussed. The results indicate that, under the time-dependent formulation, travel-time savings may be more important than uncertain travel time when departure time is close to such time constraints as work-start time.
Volume (Year): 41 (2007)
Issue (Month): 4 (May)
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- Jiang, Meilan & Morikawa, Takayuki, 2004. "Theoretical analysis on the variation of value of travel time savings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(8), pages 551-571, October.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge University Press, number 9780521747387, June.
- Liu, Henry X. & Recker, Will & Chen, Anthony, 2004. "Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(6), pages 435-453, July.
- Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability," Econometrica, Econometric Society, vol. 73(4), pages 1367-1382, 07.
- Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
- Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
- Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
- Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
- Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
- Sándor, Z. & Train, K., 2004.
"Quasi-random simulation of discrete choice models,"
Econometric Institute Research Papers
EI 2004-51, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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