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Critical Percolation on Temporal High-Speed Railway Networks

Author

Listed:
  • Yi Liu

    (Institute of Transportation System Science and Engineering, Beijing Jiaotong University, Beijing 100044, China
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China)

  • Senbin Yu

    (Institute of Transportation System Science and Engineering, Beijing Jiaotong University, Beijing 100044, China
    College of Engineering, Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China)

  • Chaoyang Zhang

    (Institute of Transportation System Science and Engineering, Beijing Jiaotong University, Beijing 100044, China
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China)

  • Peiran Zhang

    (Institute of Transportation System Science and Engineering, Beijing Jiaotong University, Beijing 100044, China
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China)

  • Yang Wang

    (School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China)

  • Liang Gao

    (Institute of Transportation System Science and Engineering, Beijing Jiaotong University, Beijing 100044, China
    Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Deeply understanding the dynamic operating characteristics of high-speed railway (HSR) systems is of essential significance in theory and practice for the planning, construction, and operational management of HSR systems. In this paper, the HSR system is described as a temporal network, and the evolution of connected clusters in the system is considered as a percolation process. The critical integration time T c of the percolation process can determine the formation of a globally connected cluster and measure the transport performance of the HSR system. The appearance time of critical edges identified at T c can significantly affect the reliability of the transport performance of an HSR system. Compared to random percolation in the static HSR network, it can be found that the critical fraction p c of the percolation process in a temporal HSR network is almost always larger. This indicates that the global connectivity and the transport performance of HSR systems is overestimated by the static network abstraction. This paper provides a promising way of understanding the dynamic characteristics of HSR systems, evaluating their transport performance, and improving their reliability.

Suggested Citation

  • Yi Liu & Senbin Yu & Chaoyang Zhang & Peiran Zhang & Yang Wang & Liang Gao, 2022. "Critical Percolation on Temporal High-Speed Railway Networks," Mathematics, MDPI, vol. 10(24), pages 1-8, December.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4695-:d:1000055
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