The resilience of an urban rail transit (URT) network when faced with disruptions is affected by the locations of stations equipped with turn-back (TB) tracks. However, limited studies have enhanced the resilience of a URT network by setting new TB tracks. The present work addresses this gap by proposing and solving a scenario model for improving the operation of a URT network under normal conditions and disruptions by considering uncertain disruptions. A solution algorithm combined with the non-dominated sorting genetic algorithm-II is proposed to solve the model. Numerical experiments conducted on the Chengdu subway system indicate that the resilience of a URT network is significantly affected by TB operations provided at stations equipped with TB tracks. Compared with a network without new TB tracks, the matching degree between passenger flow spatial distribution and TB convenience, and the network’s overall resilience metric (NORM) are improved by 12.05% and 0.58%, respectively, when five new TB tracks are installed. The solution effectiveness of the model is related to the number of new TB tracks, and the NORM decreases by an average of [Formula: see text] after adding new TB tracks to a station.


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    Title :

    Resilience Enhancement of an Urban Rail Transit Network by Setting Turn-Back Tracks: A Scenario Model Approach


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Chen, Jinqu (author) / Jiang, Chengzhen (author) / Liu, Xiaowei (author) / Du, Bo (author) / Peng, Qiyuan (author) / Yin, Yong (author) / Li, Baowen (author)


    Publication date :

    2023-09-09




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English