Through analysis of historical data of subway transportation, use the model extracted from the law of normal and large-scale activities’ passenger traffic flow and combine the pattern library established by large-scale events’ attribute information, this paper describes a method that provides a way to forecast the subway traffic passenger flow when a large-scale activity will happen. Before the occurrence of large-scale activities, We analysis and forecast the in and out passenger flow for the stations, which around the place where the large-scale activity will happen, and the entire road network which could describe the effect of this activity to the whole network. This system able to provide passengers with a travel reference to ensure the travel speed, security and comfort, and provide an important basis for the traffic management department to realize the effective real-time scheduling.


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    Titel :

    Study of the Intelligent Analysis and Prediction about Subway Passenger Flow during Large-Scale Events


    Beteiligte:
    Kang, Jian-Chu (Autor:in) / Pang, Song-Song (Autor:in) / Zhang, Yan (Autor:in)


    Erscheinungsdatum :

    2013


    Format / Umfang :

    5 Seiten




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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