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Dynamic and Static congestion models: A review

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  • André De Palma

    (ENS Cachan - Ecole Normale Supérieure de Cachan - École normale supérieure de Cachan - ENS Cachan, Department of Economics, Ecole Polytechnique - CNRS : UMR7176 - Polytechnique - X)

  • Mogens Fosgerau

    (DTU Transport - University of Denmark - Department of Transport)

Abstract

We begin by providing an overview of the conventional static equilibrium approach. In such model both the flow of trips and congestion delay are assumed to be constant. A drawback of the static model is that the time interval during which travel occurs is not specified so that the model cannot describe changes in the duration of congestion that result from changes in demand or capacity. This limitation is overcome in the Vickrey/Arnott, de Palma Lindsey bottleneck model, which combines congestion in the form of queuing behind a bottleneck with users' trip-timing preferences and departure time decisions. We derive the user equilibrium and social optimum for the basic bottleneck model, and explain how the optimum can be decentralized using a time-varying toll. They then review some extensions of the basic model that encompass elastic demand, user heterogeneity, stochastic demand and capacity and small networks. We conclude by identifying some unresolved modelling issues that apply not only to the bottleneck model but to trip-timing preferences and congestion dynamics in general

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Bibliographic Info

Paper provided by HAL in its series Working Papers with number hal-00539166.

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Date of creation: 24 Nov 2010
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Handle: RePEc:hal:wpaper:hal-00539166

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  15. Fosgerau, Mogens & Engelson, Leonid, 2011. "The value of travel time variance," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 1-8, January.
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  20. Fosgerau, Mogens, 2008. "On the relation between the mean and variance of delay in dynamic queues with random capacity and demand," MPRA Paper 11994, University Library of Munich, Germany.
  21. Richard Arnott & Andre de Palma & Robin Lindsey, 1996. "Information and Time-of-Usage Decisions in the Bottleneck Model with Stochastic Capacity and Demand," Boston College Working Papers in Economics 355., Boston College Department of Economics.
  22. Lindsey, Robin, 2009. "Cost recovery from congestion tolls with random capacity and demand," Journal of Urban Economics, Elsevier, vol. 66(1), pages 16-24, July.
  23. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1993. "A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand," American Economic Review, American Economic Association, vol. 83(1), pages 161-79, March.
  24. Robert E. Hall, 1989. "Temporal Agglomeration," NBER Working Papers 3143, National Bureau of Economic Research, Inc.
  25. Laih, Chen-Hsiu, 1994. "Queueing at a bottleneck with single- and multi-step tolls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(3), pages 197-208, May.
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Citations

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Cited by:
  1. Mogens Fosgerau & Kenneth Small, 2013. "Endogenous Scheduling Preferences and Congestion," Working Papers 131403, University of California-Irvine, Department of Economics, revised May 2014.
  2. Leonid Engelson & Ida Kristoffersson & Mohammad Saifuzzaman & André De Palma & Kiarash Motamedi, 2013. "Comparison of two dynamic transportation models: The case of Stockholm congestion charging," Working Papers hal-00779285, HAL.

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