标题：Better understanding the choice of travel mode by urban residents: New insights from the catchment areas of rail transit stations
作者：Luan, Xin; Cheng, Lin; Song, Yan; Zhao, Jinbao
作者机构：[Luan, Xin; Cheng, Lin; Zhao, Jinbao] Southeast Univ, Sch Transportat, 2 Southeast Univ Rd, Nanjing 211189, Peoples R China.; [Luan, Xin; Song, Yan] 更多
通讯作者：Cheng, Lin;Cheng, L
通讯作者地址：Cheng, L (corresponding author), Southeast Univ, Sch Transportat, 2 Southeast Univ Rd, Nanjing 211189, Peoples R China.
来源：SUSTAINABLE CITIES AND SOCIETY
关键词：Urban life; Travel mode choice; Behavioral characteristics; Catchment; areas of urban rail transit stations; Mixed-logit models; Transportation; planning; Policy orientation
摘要：The primary objective of this paper is to systematically and quantitatively analyze the peculiarities of the mode of travel chosen by residents. More specifically, this study focuses on two major aspects: (1) shedding light on the prominent factors that affect choice of travel mode from an innovative perspective of the catchment areas (CAs) of urban rail transit (URT) stations; and (2) mining and comparing the features and advantages of a diverse range of travel modes. Furthermore, it puts forward some proposals for optimizing the structure of the urban transportation system available to the residents. Using a valuable, screened and discretized, survey dataset of good size (10,385 travel activities of 4,080 individuals in 1,454 households in Nanjing, China), two mixed-logic (ML) models are established. One is based on trip origins/destinations within the CAs of the URT stations. The other is based on residence locations. The modeling results reveal that most residents, except those who own a car and/or driving license, are inclined to choose a slow mode of transport (including walking and cycling). Travelers do not notably err towards walking and bus modes during the peak hours and/or when going to work or school instead of cycling. Residents adjacent to the CAs of URT stations are attracted away from other travel modes and have a tendency to select non-motorized modes to access the URT (metro). The contrastive analysis and discussion results can help to provide urban planners, managers, decision and policy makers with useful suggestions and data support for exploring the various factors (household properties, individual attributes, and trip information) affecting residents' choice of travel mode and seeking the residents' travel rules. Moreover, our findings have important implications with respect to improving the structure of the choice of travel modes made available to residents and simultaneously be important in maintaining green, low-carbon, and sustainable development of urban traffic systems.