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Congestion pricing in the absence of demand functions

Author

Listed:
  • Han, Deren
  • Yang, Hai

Abstract

This paper enhances a trial-and-error implementation scheme of marginal-cost pricing on a transportation network, in the absence of explicit expression of the demand function. Link tolls and link flows are updated for the next trial with the revealed link flows for given current trial toll pattern. The method is quite simple, requiring only some function evaluations. Also, the step size is not required to be square summable, thereby leading to the improvement of the efficiency of the algorithm. The global convergence of the method is proved and some numerical results are reported to illustrate its performance.

Suggested Citation

  • Han, Deren & Yang, Hai, 2009. "Congestion pricing in the absence of demand functions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 159-171, January.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:1:p:159-171
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    Citations

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    Cited by:

    1. Zhou, Bojian & Bliemer, Michiel & Yang, Hai & He, Jie, 2015. "A trial-and-error congestion pricing scheme for networks with elastic demand and link capacity constraints," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 77-92.
    2. Guo, Ren-Yong & Szeto, W.Y. & Long, Jiancheng, 2020. "Trial-and-error operation schemes for bimodal transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 106-123.
    3. Xinyuan Chen & Yiran Wang & Yuan Zhang, 2021. "A Trial-and-Error Toll Design Method for Traffic Congestion Mitigation on Large River-Crossing Channels in a Megacity," Sustainability, MDPI, vol. 13(5), pages 1-13, March.
    4. Ren-Yong Guo & Hai-Jun Huang & Hai Yang, 2019. "Tradable Credit Scheme for Control of Evolutionary Traffic Flows to System Optimum: Model and its Convergence," Networks and Spatial Economics, Springer, vol. 19(3), pages 833-868, September.
    5. Ren-Yong Guo & Hai Yang & Hai-Jun Huang & Zhijia Tan, 2016. "Day-to-Day Flow Dynamics and Congestion Control," Transportation Science, INFORMS, vol. 50(3), pages 982-997, August.
    6. Wang, Xiaolei & Yang, Hai, 2012. "Bisection-based trial-and-error implementation of marginal cost pricing and tradable credit scheme," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1085-1096.
    7. Wada, Kentaro & Akamatsu, Takashi, 2013. "A hybrid implementation mechanism of tradable network permits system which obviates path enumeration: An auction mechanism with day-to-day capacity control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 94-112.
    8. Farokhi, Farhad & Johansson, Karl H., 2015. "A piecewise-constant congestion taxing policy for repeated routing games," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 123-143.
    9. Lie Han, 2022. "Proportional-Switch Adjustment Process with Elastic Demand and Congestion Toll in the Absence of Demand Functions," Networks and Spatial Economics, Springer, vol. 22(4), pages 709-735, December.
    10. Chen, Xinyuan & Zhang, Wei & Guo, Xiaomeng & Liu, Zhiyuan & Wang, Shuaian, 2021. "An improved learning-and-optimization train fare design method for addressing commuting congestion at CBD stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    11. Ye, Hongbo & Yang, Hai & Tan, Zhijia, 2015. "Learning marginal-cost pricing via a trial-and-error procedure with day-to-day flow dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 794-807.
    12. Wang, Shuaian & Zhang, Wei & Qu, Xiaobo, 2018. "Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 318-335.

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