详情

原文传递 Recognizing Real-Time Transfer Patterns between Metro and Bus Systems Based on Spatial-Temporal Constraints

题名：	Recognizing Real-Time Transfer Patterns between Metro and Bus Systems Based on Spatial-Temporal Constraints
正文语种：	eng
作者：	Pan Wu;Lunhui Xu;Jinlong Li;Hengcong Guo;Zilin Huang
作者单位：	Dept. of Civil and Transportation Engineering South China Univ. of Technology Guangzhou 510641 China;Dept. of Civil and Transportation Engineering South China Univ. of Technology Guangzhou 510641 China;Dept. of Civil and Transportation Engineering South China Univ. of Technology Guangzhou 510641 China;Dept. of Civil and Environmental Engineering Univ. of North Carolina at Charlotte EPIC Bldg. Room 3366 Charlotte NC 28223;Center for Connected and Automated Transportation (CCAT) and Lyles School of Civil Engineering Purdue Univ. West Lafayette IN 47907
关键词：	Smart card (SC) data; Global Positioning System (GPS) data; Transfer identification; Metro-to-bus mode; Bus-to-metro mode
摘要：	The transfer between bus and metro is an integral part of the public transportation system, but accurately identifying transfer patterns and real-time transfer demands at each metro station for different transfer modes remains a vital issue. Existing identification methods are based mainly on a one-size-fits-all fixed transfer time threshold, or dynamic transfer identification methods only for the metro-to-bus mode, which is not sufficient for mining the hourly transfer characteristics of different transfer modes at each station. This study combined bus smart card (SC) data and the corresponding bus Global Positioning System (GPS) track data into one data set to infer the bus boarding stops. A new algorithm to identify transfer characteristics based on two rules about dynamic transfer time threshold and distance threshold is proposed for the metro-to-bus mode. A new method to recognize transfer patterns based on dynamic transfer time thresholds is presented for the bus-to-metro mode. The two proposed transfer recognition methods were validated using survey data from Shenzhen, China. The results show that the distribution of transfer time by the proposed methods is consistent with that of the survey data. The p-values of Mann-Whitney U tests of transfer data identified by the method and survey data all were greater than 0.05. This indicates that the methods proposed in this study can identify effectively the transfer patterns at each metro station per hour of the day, with good generalizability. Moreover, the proposed methods can explain transfer patterns and hourly transfer demand at each station for different transfer modes better than other methods.
出版年：	2022
期刊名称：	Journal of Transportation Engineering
卷：	148
期：	9
页码：	04022065.1-04022065.17