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Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations

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  • Wang, Shuaian
  • Zhang, Wei
  • Qu, Xiaobo

Abstract

This study deals with boarding/alighting congestion of congested commuter train stations at central business district (CBD), in which the additional fares are determined to shift an appropriate number of passengers to board/alight at the neighboring uncongested stations on the railway line. A bi-objective model is investigated to minimize both fare increases of the congested stations, while alleviating their boarding/alighting congestion to a certain level simultaneously. The existence of the unique Pareto-optimal solution is proven mathematically in the absence of explicit demand functions. A trial-and-error fare design scheme is proposed to identify the Pareto-optimal solution. An illustrative study demonstrates the effectiveness of the trial-and-error scheme.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transb:v:118:y:2018:i:c:p:318-335
    DOI: 10.1016/j.trb.2018.11.003
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    5. 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.
    6. 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.
    7. Offiaeli, K. & Yaman, F., 2020. "Social Norms as a Cost-Effective Measure of Managing Transport Demand: Evidence from an Experiment on the London Underground," Working Papers 20/07, Department of Economics, City University London.
    8. Offiaeli, Kingsley & Yaman, Firat, 2021. "Social norms as a cost-effective measure of managing transport demand: Evidence from an experiment on the London underground," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 63-80.
    9. Huo, Jinbiao & Liu, Zhiyuan & Chen, Jingxu & Cheng, Qixiu & Meng, Qiang, 2023. "Bayesian optimization for congestion pricing problems: A general framework and its instability," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 1-28.
    10. Zhen, Lu & Tan, Zheyi & Wang, Shuaian & Yi, Wen & Lyu, Junyan, 2021. "Shared mobility oriented open vehicle routing with order radius decision," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 19-33.

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