Xubin Sun, Yue Zhang, Gao-You Qin, Hai-rong Dong, F. Guan
{"title":"Pedestrian transfer time optimization of urban rail transit based on ACP approach","authors":"Xubin Sun, Yue Zhang, Gao-You Qin, Hai-rong Dong, F. Guan","doi":"10.1109/ICAL.2012.6308176","DOIUrl":null,"url":null,"abstract":"This paper investigates the coordination of two subway lines with computational experiments based on ACP approach. The arriving interval of the two subway lines at the transfer station is optimized, making the average transfer time shortest. Firstly, the subway station artificial system is established, where the pedestrians are modeled using social force model. Secondly, computational experiments are executed in a transfer station taking train arrival interval of two subway lines as optimization variable. Optimal arrival interval is obtained which makes the average transfer time shortest. Finally, further computational experiments are made considering pedestrian characteristics, including pedestrian velocity and density. The average transfer time can be reduced by 7.91%, using the optimal train arrival interval of two subway lines. Pedestrian transfer time optimization is an efficient way to relieve subway congestion and improve coordination of subway lines.","PeriodicalId":373152,"journal":{"name":"2012 IEEE International Conference on Automation and Logistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Automation and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2012.6308176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper investigates the coordination of two subway lines with computational experiments based on ACP approach. The arriving interval of the two subway lines at the transfer station is optimized, making the average transfer time shortest. Firstly, the subway station artificial system is established, where the pedestrians are modeled using social force model. Secondly, computational experiments are executed in a transfer station taking train arrival interval of two subway lines as optimization variable. Optimal arrival interval is obtained which makes the average transfer time shortest. Finally, further computational experiments are made considering pedestrian characteristics, including pedestrian velocity and density. The average transfer time can be reduced by 7.91%, using the optimal train arrival interval of two subway lines. Pedestrian transfer time optimization is an efficient way to relieve subway congestion and improve coordination of subway lines.