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A Combinatorial user optimal dynamic traffic assignment algorithm

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  • S. Waller
  • Athanasios Ziliaskopoulos

Abstract

This paper introduces a polynomial combinatorial optimization algorithm for the dynamic user optimal problem. The approach can efficiently solve single destination networks and can be potentially extended to heuristically solve multidestinational networks. In the model, traffic is propagated according to sound traffic flow theoretical models rather than link exit functions; thereby allowing link queue evolution to be modeled more precisely. The algorithm is designed, proven, implemented and computationally tested. Copyright Springer Science+Business Media, LLC 2006

Suggested Citation

  • S. Waller & Athanasios Ziliaskopoulos, 2006. "A Combinatorial user optimal dynamic traffic assignment algorithm," Annals of Operations Research, Springer, vol. 144(1), pages 249-261, April.
    • Handle: RePEc:spr:annopr:v:144:y:2006:i:1:p:249-261:10.1007/s10479-006-0013-z
    DOI: 10.1007/s10479-006-0013-z
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    References listed on IDEAS

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    Cited by:

    1. Satish Ukkusuri & S. Waller, 2008. "Linear Programming Models for the User and System Optimal Dynamic Network Design Problem: Formulations, Comparisons and Extensions," Networks and Spatial Economics, Springer, vol. 8(4), pages 383-406, December.
    2. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    3. Satsukawa, Koki & Wada, Kentaro & Iryo, Takamasa, 2020. "Reprint of “Stochastic stability of dynamic user equilibrium in unidirectional networks: Weakly acyclic game approach”," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 117-135.
    4. Michael W. Levin, 2019. "A Combinatorial Dynamic Network Trajectory Reservation Algorithm for Connected Autonomous Vehicles," Networks and Spatial Economics, Springer, vol. 19(1), pages 27-55, March.
    5. Dung-Ying Lin & Ampol Karoonsoontawong & S. Waller, 2011. "A Dantzig-Wolfe Decomposition Based Heuristic Scheme for Bi-level Dynamic Network Design Problem," Networks and Spatial Economics, Springer, vol. 11(1), pages 101-126, March.
    6. 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.
    7. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    8. Ampol Karoonsoontawong & Steven Waller, 2010. "Integrated Network Capacity Expansion and Traffic Signal Optimization Problem: Robust Bi-level Dynamic Formulation," Networks and Spatial Economics, Springer, vol. 10(4), pages 525-550, December.
    9. Satsukawa, Koki & Wada, Kentaro & Iryo, Takamasa, 2019. "Stochastic stability of dynamic user equilibrium in unidirectional networks: Weakly acyclic game approach," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 229-247.
    10. Arpad Torok & Gabor Pauer, 2022. "Safety aspects of critical scenario identification for autonomous transport," Cognitive Sustainability, Cognitive Sustainability Ltd., vol. 1(3), pages 32-38, September.
    11. Iryo, Takamasa & Smith, Michael J., 2018. "On the uniqueness of equilibrated dynamic traffic flow patterns in unidirectional networks," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 757-773.
    12. Chi Xie & Jennifer Duthie, 2015. "An Excess-Demand Dynamic Traffic Assignment Approach for Inferring Origin-Destination Trip Matrices," Networks and Spatial Economics, Springer, vol. 15(4), pages 947-979, December.
    13. Long, Jiancheng & Szeto, W.Y. & Huang, Hai-Jun & Gao, Ziyou, 2015. "An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 182-217.

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