Abstract
This study develops a new method for estimating the departure time of OD flows. Although departure time choice is very sensitive to changes in the travel environment, it has not been included in transportation planning. There exist some theoretical methods, but most have not been applied to practical studies. In addition, the behavior of travelers regarding departure time choice has not been adequately addressed. To overcome these problems, the proposed model takes two behavioral aspects into account. The first is the maximization of in-home activity time before a departure, and the second is the dynamic user equilibrium in departure time choice. This study investigates the effect of incorporating these two aspects through numerical tests. The results indicate that the developed method has a reasonable capability to forecast the resulting departure pattern change after the modification of network attributes. In addition, the method is simpler than existing approaches such as the schedule delay function; thus, it can be helpful for studying practical problems.
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References
Bellei, G., Gentile, G., Meschini, L., and Papola, N. (2006). “A demand model with departure time choice for within-day dynamic traffic assignment.” European Journal of Operational Research, Vol. 175, No. 3, pp. 1557–1576
Bhat, C. R. and Steed, J. L. (2002). “A continuous-time model of departure time choice for urban shopping trips.” Transportation Research Part B, Vol. 36, No. 3, pp. 207–234.
Chang, G.-L. and Mahmassani, H. S. (1988). “Travel time prediction and departure time adjustment behavior dynamics in a congested traffic system.” Transportation Research Part B, Vol. 22, No. 3, pp. 217–232.
Chen, H. K. (1999). Dynamic travel choice models, Springer.
Chow, A. H. F. (2009). “Properties of system optimal traffic assignment with departure time choice and its solution method.” Transportation Research Part B, Vol. 43, No. 3, pp. 325–344.
Ettema, D., Tammingga, G., Timmermans, H., and Arentze, T. (2005). “A micro-simulation model system of departure time using a perception updating model under travel time uncertainty.” Transportation Research Part A, Vol. 39, No. 4, pp. 325–344.
Fujii, S. and Kitamura, R. (2004). “Drivers’ mental representation of travel time and departure time choice in uncertain traffic network conditions.” Networks and Spatial Economics, Vol. 4, No. 3, pp. 243–256.
Heydecker, B. G. and Addison, J. D. (2005). “Analysis of dynamic traffic equilibrium with departure time choice.” Transportation Science, Vol. 39, No. 1, pp. 39–57.
Huang, H.-J. and Lam, W. H. K. (2002). “Modeling and solving the dynamic user equilibrium route and departure time choice problem in network with queues.” Transportation Research Part B, Vol. 36, No. 3, pp. 253–273.
Jou, R.-C. (2001). “Modeling the impact of pre-trip information on commuter departure time and route choice.” Transportation Research Part B, Vol. 35, No. 10, pp. 887–902.
Kim, H. (2008). New dynamic travel demand modeling methods in advanced data collecting environments, PhD Dissertation, University of California, Irvine.
Kim, H. (2009). “Dynamic traffic assignment based on arrival time-based OD flows.” Journal of Korean Society of Transportation, Vol. 27, No. 1, pp. 143–155
Kim, H. and Jayakrishnan, R. (2006). “Dynamic traffic assignment based on arrival time-based OD demand.” The 85th Annual Meeting of the Transportation Research Board, January 22–26, Washington, D.C
Kitamura, R., Pas, E. I., Lula, C. V., Lawton, T. K., and Benson, P. E. (1996). “The Sequenced Activity Mobility Simulator (SAMS): An integrated approach to modeling transportation, land use and air quality.” Transportation, Vol. 23, No. 3, pp. 267–297.
Lam, W. H. K. and Huang, H.-J. (2002). “A combined activity/travel choice model for congested road network with queues.” Transportation, Vol. 29, No. 1, pp. 5–29.
Lim, Y. and Heydecker, B. (2005). “Dynamic departure time and stochastic user equilibrium assignment.” Transportation Research Part B, Vol. 39, No. 2, pp. 97–118.
Mahmassani, H. S., Sbayti, H., and Zhou, X. (2004). DYNASMART-P: Intelligent transportation network planning tool, version 1.9 user’s guide, Maryland Transportation Initiative, University of Maryland.
Ortuzar, J. D. and Willumsen, L. G.. (1990). Modelling transport, John Wiley & Sons Ltd.
Ran, B., Hall, R. W., and Boyce, D. E. (1996). “A link-based variational inequality model for dynamic departure time/route choice.” Transportation Research Part B, Vol. 30, No. 1, pp. 31–46.
Sheffi, Y. (1985). Urban transportation networks, MIT press, NY.
Spiess, H. (1990). A gradient approach for the O-D matrix adjustment problem, Transportation Research Paper #692, University of Montreal.
Yang, H. and Meng, Q. (1998). “Departure time, route choice and congestion toll in a queuing network with elastic demand.” Transportation Research Part B, Vol. 32, No. 4, pp. 247–260.
Zhang, X., Huang, H.-J., and Zhang, M. (2008). “Integrate daily commuting patterns and optimal road tolls and parking fees in a linear city.” Transportation Research Part B, Vol. 42, No. 1, pp. 38–56.
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Kim, H., Lim, Y. & Rhee, S. Dynamic traffic assignment with departure flow estimation based on preferred arrival time. KSCE J Civ Eng 16, 633–643 (2012). https://doi.org/10.1007/s12205-012-1210-8
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DOI: https://doi.org/10.1007/s12205-012-1210-8