Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China
Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China作者机构:School of ArchitectureState Key Laboratory of Subtropical Building ScienceSouth China University of TechnologyGuangzhou 510641China School of Architecture and Urban PlanningNanjing UniversityJiangsu Provincial Engineering Laboratory of Smart City Design Simulation&VisualizationNanjing 210093China Guangzhou Institute of GeographyGuangzhou 510070China
出 版 物:《Chinese Geographical Science》 (中国地理科学(英文版))
年 卷 期:2021年第31卷第1期
页 面:54-69页
核心收录:
学科分类:0303[法学-社会学] 08[工学] 0708[理学-地球物理学] 082303[工学-交通运输规划与管理] 0705[理学-地理学] 0813[工学-建筑学] 0704[理学-天文学] 0833[工学-城乡规划学] 082302[工学-交通信息工程及控制] 0823[工学-交通运输工程]
基 金:Under the auspices of National Natural Science Foundation of China(No.41801150,41571146,41801144) Natural Science Foundation of Guangdong Province(No.2018A030310392) Guangdong Planning Project of Philosophy and Social Science(No.GD17YGL01) Science and Technology Program of Guangzhou(No.201906010033) GDAS’(Guangdong Academy of Sciences)Project of Science and Technology Development(No.2020GDASYL-20200104007)
主 题:sharing bicycles travel behaviours smart societies geographically weighted regression analysis Guangzhou,China
摘 要:Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China;furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest(POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.