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Analysis of Dynamic Traffic Equilibrium with Departure Time Choice

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  • B. G. Heydecker

    (Centre for Transport Studies, University College London, Gower Street, London WC1E 6BT, United Kingdom)

  • J. D. Addison

    (Centre for Transport Studies, University College London, Gower Street, London WC1E 6BT, United Kingdom)

Abstract

We present and analyse a model of the combined choice of departure time and route in a congested road network. Using the property of equilibrium solutions that for each origin-destination pair the total cost associated with travel is identical for all travellers, we establish a general result that relates assignments to various components of cost. The analysis is developed to include time-varying tolls and to establish a formula that will induce any specified inflow profile as an equilibrium. We introduce an iteration operator to calculate equilibrium inflow profiles, and present the results of example calculations for a range of test problems.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ortrsc:v:39:y:2005:i:1:p:39-57
    DOI: 10.1287/trsc.1030.0075
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    References listed on IDEAS

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    Cited by:

    1. Berliant, Marcus, 2017. "Commuting and internet traffic congestion," MPRA Paper 77378, University Library of Munich, Germany.
    2. Li-Jun Tian & Hai-Jun Huang & Zi-You Gao, 2012. "A Cumulative Perceived Value-Based Dynamic User Equilibrium Model Considering the Travelers’ Risk Evaluation on Arrival Time," Networks and Spatial Economics, Springer, vol. 12(4), pages 589-608, December.
    3. Frédéric Meunier & Nicolas Wagner, 2010. "Equilibrium Results for Dynamic Congestion Games," Transportation Science, INFORMS, vol. 44(4), pages 524-536, November.
    4. Correia, Gonçalo Homem de Almeida & van Arem, Bart, 2016. "Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 64-88.
    5. Chow, Andy H.F., 2009. "Properties of system optimal traffic assignment with departure time choice and its solution method," Transportation Research Part B: Methodological, Elsevier, vol. 43(3), pages 325-344, March.
    6. Xiaoning Zhang & H. Zhang, 2010. "Simultaneous Departure Time/Route Choices in Queuing Networks and a Novel Paradox," Networks and Spatial Economics, Springer, vol. 10(1), pages 93-112, March.
    7. André de Palma & Mogens Fosgerau, 2010. "Dynamic and Static congestion models: A review," Working Papers hal-00539166, HAL.
    8. André de Palma & Mogens Fosgerau, 2011. "Dynamic Traffic Modeling," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 9, Edward Elgar Publishing.
    9. Verhoef, Erik T. & Silva, Hugo E., 2017. "Dynamic equilibrium at a congestible facility under market power," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 174-192.
    10. Ying, Cheng-shuo & Chow, Andy H.F. & Nguyen, Hoa T.M. & Chin, Kwai-Sang, 2022. "Multi-agent deep reinforcement learning for adaptive coordinated metro service operations with flexible train composition," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 36-59.

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