The invention relates to a multi-source data-based rail transit transfer shared bicycle influence area defining method. The method comprises the steps of obtaining an urban road network, an urban railline network, urban POI facility point data and shared bicycle riding order data of a target city; obtaining the space-time influence range characteristic of each rail station and the space-time ringlayer of each rail station; drawing a transfer riding space-time circle layer graph according to the space-time circle layer of each rail station, adding the transfer riding space-time circle layer graph to a graph layer, assigning a space-time circle layer index to an attribute table of the graph layer, and performing analysis through an analytic hierarchy process to obtain a basic riding indexin each calculation grid; analyzing according to the space-time circle layer index and the basic riding index to obtain a transfer comprehensive index; combining a Thiessen polygon theory to obtain arail transit transfer shared bicycle influence area division graph; and performing boundary correction on the rail transit transfer shared bicycle influence area division graph to obtain a final railtransit transfer shared bicycle influence area range, and accurately defining a rail station transfer riding influence area.

    本申请涉及一种多源数据的轨道交通换乘共享单车影响区界定方法。该方法包括:获取目标城市的城市道路网、城市轨道线网、城市POI设施点数据、共享单车骑行订单数据;得到各轨道站点的时空影响范围特性、各轨道站点的时空圈层;根据各轨道站点的时空圈层,绘制换乘骑行时空圈层图添加至图层,并在图层的属性表中赋值时空圈层指数,通过层次分析法进行分析,获得各计算网格内的基础骑行指数;根据时空圈层指数和基础骑行指数进行分析,获得换乘综合指数;结合泰森多边形理论获得轨道交通换乘共享单车影响区划分图;对轨道交通换乘共享单车影响区划分图进行边界修正,获得最终轨道交通换乘共享单车影响区域范围,准确界定出轨道站点换乘骑行的影响区。


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    Title :

    multi-source data-based rail transit transfer shared bicycle influence area defining method


    Additional title:

    基于多源数据的轨道交通换乘共享单车影响区界定方法


    Contributors:
    CHEN JUN (author) / HAO JUN (author) / ZENG YU (author) / ZHANG XIANMING (author)

    Publication date :

    2021-04-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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