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Exploring the Evolution of Passenger Flow and Travel Time Reliability with the Expanding Process of Metro System Using Smartcard Data

Exploring the Evolution of Passenger Flow and Travel Time Reliability with the Expanding Process of Metro System Using Smartcard Data

作     者:Xinwei Ma Yanjie Ji Yao Fan Chenyu Yi 

作者机构:School of TransportationSoutheast University 

出 版 物:《Journal of Harbin Institute of Technology(New Series)》 (哈尔滨工业大学学报(英文版))

年 卷 期:2019年第26卷第1期

页      面:17-29页

学科分类:0810[工学-信息与通信工程] 08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:Sponsored by Projects of International Cooperation and Exchange of the National Natural Science Foundation of China(Grant No.51561135003) Key Project of National Natural Science Foundation of China(Grant No.51338003) 

主  题:metro expansion smart card data passenger flow characteristics travel time reliability visualization 

摘      要:Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper s main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for analysis.Results showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.

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