To estimate evacuation capacity of subway stations under emergency conditions, a bilevel programming model of evacuee equilibrium is built by considering travel time on walking facilities with various congestion degrees. The upper-level model ensures the maximum utilization of facilities, whereas the lower level model is to minimize the evacuation time by determining how to guide evacuees to arrive at safety zones. An improved particle swarm optimization algorithm is designed to solve the model. To validate the model and algorithm, by taking capacity estimation of Fuxingmen Station of Beijing Subway as an example, evacuation process is simulated to get the optimal routes and proper estimation. Evacuation passenger flow per unit time and network crowdedness are selected as indexes to estimate the capacity of station under emergency condition. The results show that the capacity of Fuxingmen Station is 1,071 persons per minute in the adverse situation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Estimation of emergency evacuation capacity for subway stations


    Beteiligte:
    Wu, You (Autor:in) / Xu, Jie (Autor:in) / Jia, Limin (Autor:in) / Qin, Yong (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    02.11.2018


    Format / Umfang :

    16 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Emergency evacuation platform for subway tunnel

    WU TIANZE | Europäisches Patentamt | 2021

    Freier Zugriff


    Evacuation Capacity Estimation for Subway Station Based on Queueing Model

    Zhang, Hui / Xu, Jie / Li, Siyao et al. | TIBKAT | 2020


    Evacuation Capacity Estimation for Subway Station Based on Queueing Model

    Zhang, Hui / Xu, Jie / Li, Siyao et al. | Springer Verlag | 2020


    Evacuation Capacity Estimation for Subway Station Based on Queueing Model

    Zhang, Hui / Xu, Jie / Li, Siyao et al. | British Library Conference Proceedings | 2020