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Solving an Instantaneous Dynamic User-Optimal Route Choice Model

Author

Listed:
  • David E. Boyce

    (Urban Transportation Center, University of Illinois at Chicago, Chicago, Illinois 60607)

  • Bin Ran

    (Institute of Transportation Studies, University of California at Berkeley, Richmond, California 94804)

  • Larry J. Leblanc

    (Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203)

Abstract

Dynamic models of the behavior of automobile drivers in choosing routes through urban transportation networks are required for the design and operation of intelligent transportation systems generally, and traveler information systems in particular. In this paper, drivers' route choice behavior based on current, or instantaneous, information on network conditions is described using an optimal control theory formulation. The time-dependent origin-destination vehicle trip pattern is assumed to be known. The instantaneous dynamic user-optimal route choice problem is to allocate vehicle flows to the current minimal-cost routes, defined as the routes that minimize the route travel cost between each decision node (any node on the route including the origin) and the destination node based on the currently prevailing travel times. The continuous time formulation of the problem is transformed into a discrete time nonlinear programming (NLP) formulation. Each of a sequence of NLPs is then solved by an algorithm based on the Frank-Wolfe technique. In this sequence, approximate link travel times are updated iteratively in order to represent flow propagation over routes. Computational results from applying the algorithm to two test networks conclude the paper.

Suggested Citation

  • David E. Boyce & Bin Ran & Larry J. Leblanc, 1995. "Solving an Instantaneous Dynamic User-Optimal Route Choice Model," Transportation Science, INFORMS, vol. 29(2), pages 128-142, May.
    • Handle: RePEc:inm:ortrsc:v:29:y:1995:i:2:p:128-142
    DOI: 10.1287/trsc.29.2.128
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    Cited by:

    1. B. G. Heydecker & J. D. Addison, 2005. "Analysis of Dynamic Traffic Equilibrium with Departure Time Choice," Transportation Science, INFORMS, vol. 39(1), pages 39-57, February.
    2. Soulaymane Kachani & Georgia Perakis, 2009. "A Dynamic Travel Time Model for Spillback," Networks and Spatial Economics, Springer, vol. 9(4), pages 595-618, December.
    3. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
    4. Anthony G O Yeh & P C Lai & S C Wong & Nelson H C Yung, 2004. "The Architecture for a Real-Time Traffic Multimedia Internet Geographic Information System," Environment and Planning B, , vol. 31(3), pages 349-366, June.
    5. Nie, Xiaojian & Zhang, H.M., 2005. "Delay-function-based link models: their properties and computational issues," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 729-751, September.
    6. Yan-Qun Jiang & S.C. Wong & Peng Zhang & Keechoo Choi, 2017. "Dynamic Continuum Model with Elastic Demand for a Polycentric Urban City," Transportation Science, INFORMS, vol. 51(3), pages 931-945, August.
    7. Aghamohammadi, Rafegh & Laval, Jorge A., 2020. "Dynamic traffic assignment using the macroscopic fundamental diagram: A Review of vehicular and pedestrian flow models," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 99-118.
    8. Carey, Malachy & McCartney, Mark, 2002. "Behaviour of a whole-link travel time model used in dynamic traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 83-95, January.
    9. Wu, Chengyuan & Yang, Liangze & Du, Jie & Pei, Xin & Wong, S.C., 2024. "Continuum dynamic traffic models with novel local route-choice strategies for urban cities," Transportation Research Part B: Methodological, Elsevier, vol. 181(C).

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