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The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network

Author

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  • Kai Lu

    (School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100404, China
    National Engineering Laboratory for Urban Rail Transit Communication and Operation Control, Beijing 100044, China
    Traffic Control Technology Co., Ltd., Beijing 100070, China)

  • Tao Tang

    (School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100404, China
    National Engineering Laboratory for Urban Rail Transit Communication and Operation Control, Beijing 100044, China)

  • Chunhai Gao

    (Traffic Control Technology Co., Ltd., Beijing 100070, China)

Abstract

Passenger behavior analysis is a key issue in passenger assignment research, in which the path choice is a fundamental component. A highly complex transit network offers multiple paths for each origin–destination (OD) pair and thus resulting in more flexible choices for each passenger. To reflect a passenger’s flexible choice for the transit network, the optimal strategy was proposed by other researchers to determine passenger choice behavior. However, only strategy links have been searched in the optimal strategy algorithm and these links cannot complete the whole path. To determine the paths for each OD pair, this study proposes the depth-first path generation algorithm, in which a strategy node concept is newly defined. The proposed algorithm was applied to the Beijing metro network. The results show that, in comparison to the shortest path and the K-shortest path analysis, the proposed depth-first optimal strategy path generation algorithm better represents the passenger behavior more reliably and flexibly.

Suggested Citation

  • Kai Lu & Tao Tang & Chunhai Gao, 2020. "The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network," Sustainability, MDPI, vol. 12(13), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:13:p:5365-:d:379577
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    References listed on IDEAS

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    3. Alireza Khani & Mark Hickman & Hyunsoo Noh, 2015. "Trip-Based Path Algorithms Using the Transit Network Hierarchy," Networks and Spatial Economics, Springer, vol. 15(3), pages 635-653, September.
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