Estimation method for railway passengers' train choice behavior with smart card transaction data

Takahiko Kusakabe, Takamasa Iryo, Yasuo Asakura

Research output: Contribution to journalArticlepeer-review

95 Citations (Scopus)

Abstract

Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused on train choices made by railway passengers. If each passenger's train choice can be identified over a long period of time, this information would be useful for improving the customer relationship management of the railway company and for improving train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns from smart card transaction data collected over a long time period.

Original languageEnglish
Pages (from-to)731-749
Number of pages19
JournalTransportation
Volume37
Issue number5
DOIs
Publication statusPublished - 2010 Jun 30
Externally publishedYes

Keywords

  • Railway passenger
  • Smart card data
  • Train timetable
  • Travel behavior

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Development
  • Transportation

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