Following operational interruptions in the urban rail transit system, affected trains are typically organized to perform turn back operations at stations with turn-back capabilities, aiming to minimize the impact of the interruption on the network. Considering potential interruptions in the urban rail transit network, this paper presents a method for selecting turn-back stations during the network planning and construction phase to optimize the network structure and enhance resilience. With the uncertainty of interruptions in the urban rail transit network in mind, a stochastic optimization model is formulated in this paper, with the objective of maximizing the expected network performance under various interruption scenarios. The aim is to select the positions of a limited number of turn-back stations in the network so that the network can maintain a high level of resilience in possible interruption scenarios. The number of passengers transported on the shortest path is utilized as the performance metric for the urban rail transit network. Finally, a case study is conducted using part of the Beijing subway network as an example. The result indicates that the resilience of the urban rail transit network is increased by 7.12% compared to traditional methods by the proposed approach in this paper.


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    Titel :

    Turn-back station selection model of urban rail transit network considering resilience improvement


    Beteiligte:
    Falcone, Francisco (Herausgeber:in) / Yao, Xinwei (Herausgeber:in) / Sun, Yuping (Autor:in)

    Kongress:

    4th International Conference on Internet of Things and Smart City (IoTSC 2024) ; 2024 ; Hangzhou, China


    Erschienen in:

    Proc. SPIE ; 13224


    Erscheinungsdatum :

    07.08.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch