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Are the objective and solutions of dynamic user-equilibrium models always consistent?*

* This paper has been replicated

Author

Listed:
  • Lin, Wei-Hua
  • Lo, Hong K.

Abstract

Existing dynamic user-equilibrium traffic assignment (DUETA) models are mostly expanded from the static user-equilibrium traffic assignment model by introducing the time dimension along with a group of additional constraints. Whereas the equivalency between the solution to the traffic assignment model and the user-equilibrium condition as defined by Wardrop is well established in the static case, the same may not be true for the dynamic case. This paper examines the general form of DUETA models as proposed in previous research and shows that, if queuing behavior is represented in the model at a minimal level, the solution to conventional DUETA models with an objective function of the form adopted by most existing formulations may not necessarily converge to or approximate the Wardropian user-equilibrium condition in the dynamic sense as defined by many researchers.

Suggested Citation

  • Lin, Wei-Hua & Lo, Hong K., 2000. "Are the objective and solutions of dynamic user-equilibrium models always consistent?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 137-144, February.
    • Handle: RePEc:eee:transa:v:34:y:2000:i:2:p:137-144
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    Citations

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    Cited by:

    1. Hoang, Nam H. & Vu, Hai L. & Lo, Hong K., 2018. "An informed user equilibrium dynamic traffic assignment problem in a multiple origin-destination stochastic network," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 207-230.
    2. Han, Sangjin, 2007. "A route-based solution algorithm for dynamic user equilibrium assignments," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1094-1113, December.
    3. Mansoureh Jeihani & Hanif Sherali & Antoine Hobeika, 2006. "Computing dynamic user equilibria for large-scale transportation networks," Transportation, Springer, vol. 33(6), pages 589-604, November.
    4. Han, S. & Heydecker, B.G., 2006. "Consistent objectives and solution of dynamic user equilibrium models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 16-34, January.
    5. Poon, M. H. & Wong, S. C. & Tong, C. O., 2004. "A dynamic schedule-based model for congested transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 343-368, May.
    6. Lo, Hong K. & Szeto, W. Y., 2002. "A cell-based variational inequality formulation of the dynamic user optimal assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 421-443, June.
    7. Georgia Perakis & Guillaume Roels, 2006. "An Analytical Model for Traffic Delays and the Dynamic User Equilibrium Problem," Operations Research, INFORMS, vol. 54(6), pages 1151-1171, December.
    8. Hoang, Nam H. & Vu, Hai L. & Panda, Manoj & Lo, Hong K., 2019. "A linear framework for dynamic user equilibrium traffic assignment in a single origin-destination capacitated network," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 329-352.
    9. Hong Zheng & Yi-Chang Chiu & Pitu B. Mirchandani, 2015. "On the System Optimum Dynamic Traffic Assignment and Earliest Arrival Flow Problems," Transportation Science, INFORMS, vol. 49(1), pages 13-27, February.
    10. Kachani, Soulaymane & Perakis, Georgia, 2006. "Fluid dynamics models and their applications in transportation and pricing," European Journal of Operational Research, Elsevier, vol. 170(2), pages 496-517, April.

    Replication

    This item has been replicated by:
  • Han, S. & Heydecker, B.G., 2006. "Consistent objectives and solution of dynamic user equilibrium models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 16-34, January.

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