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基于顺风车数据和聚类方法的都市圈区域划分与层级结构研究
引用本文:闫学东,郭浩楠,李永昌,王云,官云林. 基于顺风车数据和聚类方法的都市圈区域划分与层级结构研究[J]. 交通运输系统工程与信息, 2021, 21(4): 30-39. DOI: 10.16097/j.cnki.1009-6744.2021.04.004
作者姓名:闫学东  郭浩楠  李永昌  王云  官云林
作者单位:1. 北京交通大学,综合交通运输大数据行业重点实验室,北京 100044; 2. 山东省交通规划设计院集团有限公司,济南 250031
基金项目:国家自然科学基金重大研究计划 ;国家自然科学基金创新研究群体科学基金
摘    要:都市圈已经逐渐成为国家新型城镇化发展的主体形态之一,在区域经济一体化建设中起着十分重要的作用.本文基于顺风车数据,使用聚类分析方法,围绕北京都市圈区域划分与层级结构展开相关研究.首先,通过网格模型将研究区域网格化处理并作为基本处理单元,匹配获取的顺风车数据与POI数据到网格中,利用基于网格的改进K-means++聚类算...

关 键 词:城市交通  都市圈区域划分  聚类算法  都市圈  顺风车数据
收稿时间:2021-03-27

Regional Division and Hierarchical Structure of Metropolitan Area Based on Carpooling Data and Clustering Method
YAN Xue-dong,GUO Hao-nan,LI Yong-chang,WANG Yun,GUAN Yun-lin. Regional Division and Hierarchical Structure of Metropolitan Area Based on Carpooling Data and Clustering Method[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 30-39. DOI: 10.16097/j.cnki.1009-6744.2021.04.004
Authors:YAN Xue-dong  GUO Hao-nan  LI Yong-chang  WANG Yun  GUAN Yun-lin
Affiliation:1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University, Beijing 100044, China; 2. Shandong Provincial Communications Planning andDesign Institute Group Co. LTD, Jinan 250031, China
Abstract:Metropolitan area has gradually become one of the main forms of our country's new-type urbanization, and itplays a particularly important role in promoting the development of regional economic integration. Based on thecarpooling data, this paper uses the cluster analysis method for the regional definition and hierarchical structuredivision of Beijing metropolitan area. First, we divided the research area into grids as the basic processing unit, andmatched the carpooling data and the Point of Interest (POI) data to the grids. Then we combined the sum of the squarederrors and silhouette coefficient to determine the optimal number of clusters, and used the grid- based K- means ++clustering algorithm to identify the main functional areas of the Beijing metropolitan area. By analyzing the commutingcharacteristics in different functional areas, the evaluating indicators such as commuting intensity, commuting time,regional independence, and regional accessibility are proposed, which can be used to study the hierarchical structure ofBeijing metropolitan area by using the hierarchical clustering method. The results show that the method in this papercan overcome the influence of the random selection of the number of clusters in the traditional clustering algorithm,and can effectively divide and obtain 19 types of main functional areas of the Beijing metropolitan area, which hadbetter clustering effect. The clustering results of functional areas are different from the existing divisions ofadministrative areas in Beijing. Therefore, the administrative area barriers should be broken in the construction of themetropolitan area, and the overall planning should be implemented. According to the commuting characteristics andgeographical characteristics of different functional areas, the Beijing metropolitan area can be further divided into threedistinct circles, including the core layer, the suburban layer, and the outer suburban layer. Development strategiesshould be formulated according to regional characteristics, the commuting status of different circles can be improvedthrough the development of suburban railways or rail transit, and the overall commuting accessibility of the Beijingmetropolitan area should be improved. The results can help to formulate planning and management policies, which canimprove the function and structure, and promote the benign development of the metropolitan area.
Keywords:urban traffic   metropolitan area division   clustering algorithm   metropolitan area   carpooling data  
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