基于泰森多边形的地铁换乘量生成模型及影响因素分析

A Generation Model of Metro Transfer Flow and Analysis on Its Influencing Factors Based on Voronoi Polygons

在多式联运的公共交通网络中,换乘是不可避免的。与门到门服务相比,换乘的便捷程度会影响公共交通出行吸引力。因此,规划和管理有效的换乘衔接非常重要,这需要了解影响换乘的因素。以地铁站为研究对象,分析了在以公交、地铁和自行车组成的城市公共交通最后一公里出行中,哪些因素会影响地铁站周边的自行车和公交车换乘出行量。通过研究公交、地铁和自行车联合网络中出行量与地铁周边区域的公共交通网络特征之间的关系,并以泰森多边形的不同圈层来表征不同区域的交通生成的影响力,建立了基于泰森多边形的地铁换乘量生成模型,以此来解释由自行车和公交到达地铁站的换乘量及相关影响因素。首先,生成基于地铁站网络的泰森多边形。其次,通过计算泰森多边形不同圈层的POI数量及自行车出行量得到泰森多边形的影响系数。再次,得到了公交站点数、公交到地铁换乘时间、不同类别的POI数量等多个变量,并建立了换乘量生成模型。利用北京市的智能卡数据、公共交通网络数据和POI数据,模型表现良好。该模型可预测规划中的地铁站点的周边区域(泰森多边形中)的慢行交通出行量,为新建地铁站点的公共自行车投放量及最后一公里公共交通规划提供依据。

In a multimodal public transport network,transfers are inevitable.Compared to door-to-door service,the ease of transfer affects the attractiveness of public transport.Planning and managing an efficient transfer connection is thus important,requiring understanding the factors that influence those transfers.Taking subway stations as the research object,we analyzed which factors affect the transport flow of bicycle and bus transfer trips around subway stations in the last mile of urban public transport consisting of buses,subways and bicycles.In the joint network of bus,metro and bicycle,we studied the relationship between the characteristics of the public transport network around the metro station and the transfer flow.Using different circles of Tyson polygons to characterize the influence of transport generation in different areas,we developed a Tyson polygon based model for metro transfer flow generation.The model could explain the transfer flow and related influencing factors for arriving at metro stations by bicycle and bus.First,the Tyson polygons based on the metro station network are generated.Second,the influence coefficients of the Tyson polygon are obtained by calculating the number of POIs and bicycle trips in different circles of the Tyson polygons.Third,several variables such as the number of bus stops,transfer time from bus to metro,and the number of POIs in different types are obtained,and a transfer flow generation model is established.Using smart card data,public transport network data and POI data of Beijing,our model performs well.This suggests that the model can predict the amount of slow transport trips in the surrounding area(in the Tyson polygon)of the planned metro station,and provides a basis for public bicycle placement at new metro stations and last-mile public transport planning .