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

Yanshuo Sun (), Jungang Shi () and Paul M. Schonfeld ()
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Yanshuo Sun: University of Maryland
Jungang Shi: East China Jiaotong University
Paul M. Schonfeld: University of Maryland

Public Transport, 2016, vol. 8, issue 3, No 1, 363 pages

Abstract: Abstract 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.

Keywords: Automatic fare collection data; Travel time reliability; Rail transit flow characteristics; Shanghai Metro (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (15)

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DOI: 10.1007/s12469-016-0137-8

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