基于POI数据的时空差异化城市停车分区  

Urban Parking Zoning with Spatio-temporal Differentiation Based on POI Data

作　　者：蒋韶华 吕维珩 JIANG Shaohua;LVWeiheng(School of Transportation,Lanzhou Jiaotong University,Lanzhou 730000,China)

机构地区：[1]兰州交通大学交通运输学院,甘肃兰州730000

出　　处：《综合运输》2024年第7期107-112,共6页China Transportation Review

基　　金：甘肃省自然科学基金项目(22JR5RA364)。

摘　　要：近年来机动车保有量逐渐增加,停车难问题日益突出。分级权停车管理可以有效平衡停车需求。为使分区结果客观准确,依据相关标准选取评价指标,并利用熵权法计算各指标所占权重。进一步,采用基于熵权法的模糊C均值聚类算法,根据不同时期的停车需求以及各城市区域的评价指标值,将城市停车区域进行聚类分析,获得城市停车分区结果。为验证分区结果的有效性,利用高德地图爬取停车场、POI (停车需求点)等数据,借助Arc GIS对数据的空间分布特征进行可视化分析。以兰州市城关区进行实例验证,证明了基于熵权-FCM停车分区方法的可操作性,对停车分区方法具有参考意义。In recent years,the number of motor vehicles has gradually increased,and the problem of parking difficulty has become increasingly prominent.Hierarchical parking management can effectively balance parking demand.In order to make the zoning results objective and accurate,firstly,the evaluation indexes are selected according to relevant standards,and the weight of each index is calculated by entropy weight method.Secondly,the fuzzy C-means clustering algorithm based on entropy weight method is used to cluster the urban parking areas according to the parking demand in different periods and the evaluation index values of each urban area,and the results of urban parking zoning are obtained.In order to verify the validity of the zoning results,data such as parking lots and POI(parking demand points)are crawled by using Gaode map,and the spatial distribution characteristics of the data are visually analyzed by using ArcGIS.Finally,the example of Chengguan District of Lanzhou City proves the operability of the parking partition method based on entropy weight-FCM,which is of reference significance to the parking partition method.

关 键 词：静态交通 停车分区 熵权模糊C均值聚类算法 爬虫 ARCGIS POI 

分 类 号：U491[交通运输工程—交通运输规划与管理]