The integrated travel demand has promoted the interconnection of multimode rail transit. As different rail transit systems are separately modeled, current network and resilience evaluation methods are limited in addressing interconnected characteristics and various travel demands. In this study, a multilayer network was constructed to validly understand the interconnected characteristics of the multimode regional rail transit system (MRRTS). A weighted multilayer regional rail transit network (W‐MRRTN) was presented to describe the travel demands and choices from an overall system perspective. Based on the W‐MRRTN combined with topological and operational features, a novel performance indicator was proposed, explicitly considered travel delays and rerouting. Furthermore, a specific definition, performance‐based metric, and simulation approach for resilience evaluation that characterized the absorptive, adaptive, and restorative capacities, was proposed. The consequences of accumulative and rerouted passengers were expressly considered to quantify the time‐dependent resilience under different disruptions. The proposed framework was applied to MRRTS in Chongqing metropolitan area, China. The results identify the stations with the highest impact on network connectivity and passenger flow, thereby proving the assortative and heterogeneous ability of the network. The comprehensive performance indicator evaluates the system more accurately than that using a single indicator. Moreover, the system under the disruption of 10, 20, and 35 min have no adaptive capacity, indicating that MRRTN is non‐resilient. The development of adaptive capacity can improve system resilience. In addition, attention should be paid to the transfer stations located near the disrupted stations. The methods and results presented in this study can be adopted as a support multimode system by transport planners, managers, and policymakers.


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    Title :

    Multilayer structures and resilience evaluation for multimode regional rail transit system


    Contributors:
    Ju, Yanni (author) / Yuan, Haihua (author) / Li, Zongping (author) / Gan, Mi (author) / Chen, Yufan (author)

    Published in:

    Publication date :

    2022-07-01


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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