According to the more qualitative methods for urban rail analysis, long cycle of diagramming train schedule chart and large passenger flow, getting the real-time statistics of the passengers’ IC card information in AFC system, according to the retention time in each station, a scatterplot of the passengers’ density can be drawn, intuitively reflecting the distribution of the passengers’ density in every station. To gain the data of the passenger flow in each station and on each route, a more accurate full-time traffic planning can be made by using the reliable traffic data. Due to the multi-routes for passengers, Based on the optimization of Dijkstra, the route in a net can be chosen, then mapping the train schedule chart. At the same time, use the data mining technology in large data era to process the history data and the dynamic information of passenger flow to provide accurate and intuitive reference for the update of the train schedule chart.


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    Titel :

    Analysis of Dynamic Passenger Flow in Urban Rail Transit Based on Data Mining


    Beteiligte:
    Chen, Xinyu (Autor:in) / Guo, Yihan (Autor:in) / Li, Boyang (Autor:in) / Ge, Miao (Autor:in) / Xu, Chunxian (Autor:in)

    Kongress:

    Fifth International Conference on Transportation Engineering ; 2015 ; Dailan, China


    Erschienen in:

    ICTE 2015 ; 2035-2042


    Erscheinungsdatum :

    25.09.2015




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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