Identifying passenger flow characteristics and evaluating travel time reliability by visualizing AFC data: a case study of Shanghai Metro

被引：44
作者：
Sun Y. [1 ]
Shi J. [2 ]
Schonfeld P.M. [1 ]
机构：
[1] Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park
[2] School of Transportation and Logistics, East China Jiaotong University, 808 Shuanggang Dong Rd, Nanchang
来源：
Sun, Yanshuo (yssun@umd.edu) | 2016年 / Springer Verlag卷 / 08期
关键词：
Automatic fare collection data; Rail transit flow characteristics; Shanghai Metro; Travel time reliability;
D O I：
10.1007/s12469-016-0137-8
中图分类号：
学科分类号：
摘要：
This paper contributes to the emerging applications of automatically collected data in revealing the aggregate patterns of passenger flows and monitoring system performance from the passengers’ perspective. The paper’s main objectives are to (1) analyze passenger flow characteristics and (2) evaluate travel time reliability for the Shanghai Metro network by visualizing the automatic fare collection (AFC) data. First, key characteristics of passenger flows are identified by examining three major aspects, namely, spatial distribution of trips over the network, temporal distribution of passenger entries at the line level and station inflow/outflow imbalances. Second, travel time reliability analyses from the users’ perspective are performed, after a new metric of travel time reliability is designed. Comparisons of travel time reliability at the OD level are provided and the network reliabilities across multiple periods are also evaluated. Thus, this paper provides a comprehensive and holistic view of passenger travel experiences. Although the case study focuses on Shanghai Metro, the same analysis framework can be applied to other transit networks equipped with similar AFC systems. © 2016, Springer-Verlag Berlin Heidelberg.
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收藏
页码：341 / 363
页数：22
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