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Discrete Dynamics in Nature and Society
Volume 2017, Article ID 4373871, 10 pages
Research Article

Assigning Passenger Flows on a Metro Network Based on Automatic Fare Collection Data and Timetable

Ling Hong,1,2 Wei Li,1,2 and Wei Zhu1,2

1Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China
2College of Transportation Engineering, Tongji University, Shanghai 201804, China

Correspondence should be addressed to Wei Zhu; moc.361@liamiewuhz

Received 1 January 2017; Accepted 11 April 2017; Published 16 May 2017

Academic Editor: Lu Zhen

Copyright © 2017 Ling Hong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Assigning passenger flows on a metro network plays an important role in passenger flow analysis that is the foundation of metro operation. Traditional transit assignment models are becoming increasingly complex and inefficient. These models may even not be valid in case of sudden changes in the timetable or disruptions in the metro system. We propose a methodology for assigning passenger flows on a metro network based on automatic fare collection (AFC) data and realized timetable. We find that the routes connecting a given origin and destination (O-D) pair are related to their observed travel times (OTTs) especially their pure travel times (PTTs) abstracted from AFC data combined with the realized timetable. A novel clustering algorithm is used to cluster trips between a given O-D pair based on PTTs/OTTs and complete the assignment. An initial application to categorical O-D pairs on the Shanghai metro system, which is one of the largest systems in the world, shows that the proposed methodology works well. Accompanying the initial application, an interesting approach is also provided for determining the theoretical maximum accuracy of the new assignment model.