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First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction

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  • Xuan Li

    (School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University Sub-center, Ningbo 315211, China
    Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Ningbo University Sub-center, Nanjing 210096, China)

  • Toshiyuki Yamamoto

    (Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8603, Japan)

  • Tao Yan

    (School of Maritime and Transportation, Ningbo University, Ningbo 315211, China)

  • Lili Lu

    (School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University Sub-center, Ningbo 315211, China
    Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Ningbo University Sub-center, Nanjing 210096, China)

  • Xiaofei Ye

    (School of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    National Traffic Management Engineering & Technology Research Centre, Ningbo University Sub-center, Ningbo 315211, China
    Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Ningbo University Sub-center, Nanjing 210096, China)

Abstract

This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.

Suggested Citation

  • Xuan Li & Toshiyuki Yamamoto & Tao Yan & Lili Lu & Xiaofei Ye, 2020. "First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4166-:d:360446
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    References listed on IDEAS

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    1. Caiyun Cui & Meng Liu & Yong Liu & Bo Xia & Martin Skitmore & Guobo Han, 2021. "The Influence of Passengers’ Perceived Social Responsibility Efforts on Their Satisfaction in Public-Private-Partnership Urban Rail Transit Projects," Sustainability, MDPI, vol. 13(23), pages 1-16, November.
    2. Wang, Chao & Meng, Xin & Guo, Mingxue & Li, Hao & Hou, Zhiqiang, 2022. "An integrated energy-efficient and transfer-accessible model for the last train timetabling problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    3. Anna Dolinayova & Vladislav Zitricky & Lenka Cerna, 2020. "Decision-Making Process in the Case of Insufficient Rail Capacity," Sustainability, MDPI, vol. 12(12), pages 1-21, June.

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