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Road pricing modeling for hyper-congestion

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  • Lo, Hong K.
  • Szeto, W.Y.

Abstract

Recently there has been a resurgence in the interest of road pricing. Most studies adopt the static modeling paradigm, typically using either separable monotone or backward-bending link travel time functions for the analysis. In this study, through the shockwave analysis, we show that separable backward-bending functions are not appropriate for modeling hyper-congestion and hence road pricing. In the absence of queue spillback, link travel time is a monotone increasing function of inflow. However, in the presence of queue spillback, we show that the static paradigm even with a monotone travel time function cannot adequately portray the congestion phenomenon. In some cases, the tolls determined by the static paradigm can be even detrimental, worsening rather than alleviating the congestion problem. In the end, to model congested networks properly, perhaps one has no other choices but to adopt a modeling paradigm that faithfully captures both the temporal as well as the spatial dimensions of traffic queuing.

Suggested Citation

  • Lo, Hong K. & Szeto, W.Y., 2005. "Road pricing modeling for hyper-congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 705-722.
    • Handle: RePEc:eee:transa:v:39:y:2005:i:7-9:p:705-722
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    References listed on IDEAS

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    Cited by:

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    3. Vosough, Shaghayegh & de Palma, André & Lindsey, Robin, 2022. "Pricing vehicle emissions and congestion externalities using a dynamic traffic network simulator," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 1-24.
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    6. Holgui­n-Veras, Jose & Cetin, Mecit & Xia, Shuwen, 2006. "A comparative analysis of US toll policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 852-871, December.
    7. Tsekeris, Theodore & Geroliminis, Nikolas, 2013. "City size, network structure and traffic congestion," Journal of Urban Economics, Elsevier, vol. 76(C), pages 1-14.
    8. Du, Jie & Wong, S.C. & Shu, Chi-Wang & Xiong, Tao & Zhang, Mengping & Choi, Keechoo, 2013. "Revisiting Jiang’s dynamic continuum model for urban cities," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 96-119.
    9. André de Palma & Shaghayegh Vosough & Robin Lindsey, 2020. "Pricing vehicle emissions and congestion using a dynamic traffic network simulator," THEMA Working Papers 2020-09, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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