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Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

作     者:Andreas Keler Jukka M.Krisp Linfang Ding 

作者机构:Institute of Geography University of Augsburg Augsburg Germany 

出 版 物:《Geo-Spatial Information Science》 (地球空间信息科学学报(英文))

年 卷 期:2017年第20卷第4期

页      面:333-344页

核心收录:

学科分类:0303[法学-社会学] 0709[理学-地质学] 1002[医学-临床医学] 0708[理学-地球物理学] 0705[理学-地理学] 0813[工学-建筑学] 100214[医学-肿瘤学] 0833[工学-城乡规划学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 10[医学] 

基  金:Laboratory for Wireless and Sensor Networks at Shanghai Jiao Tong University Wireless and Sensor networks Lab Shanghai Jiao Tong University, SJTU 

主  题:Floating Car Data (FCD) moving objects transportation infrastructure spatio-temporal patterns 

摘      要:Detecting and describing movement of vehicles in established transportation infrastructures is an important *** helps to predict periodical traffic patterns for optimizing traffic regulations and extending the functions of established transportation *** detection of traffic patterns consists not only of analyses of arrangement patterns of multiple vehicle trajectories,but also of the inspection of the embedded geographical *** this paper,we introduce a method for intersecting vehicle trajectories and extracting their intersection points for selected rush hours in urban *** vehicle trajectory intersection points (TIP) are frequently visited locations within urban road networks and are subsequently formed into density-connected clusters,which are then represented as *** representing temporal variations of the created polygons,we enrich these with vehicle trajectories of other times of the day and additional road network *** a case study,we test our approach on massive taxi Floating Car Data (FCD) from Shanghai and road network data from the OpenStreetMap (OSM) *** first test results show strong correlations with periodical traffic events in *** on these results,we reason out the usefulness of polygons representing frequently visited locations for analyses in urban planning and traffic engineering.

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