Estimation of behavioural change of railway passengers using smart card data

Yasuo Asakura, Takamasa Iryo, Yoshiki Nakajima, Takahiko Kusakabe

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


Smart card systems are becoming increasingly popular on a global scale, not just for purchasing general goods and services, but also for paying public transport fares. When a traveller uses a public transport smart card, the exact time of their passage through ticket gates are recorded in the smart card system database. However, these data have not yet been sufficiently studied in the field of transport research. The aims of this paper are to estimate the behaviour of railway passengers by using smart card data and to evaluate the effects of train operations. In particular, the analysis is focused on the comparison of passengers' travel choice behaviour before and after the railway company altered the train timetable. This paper describes how the passing times of individual passengers at entrance and exit ticket gates are aggregated for a small discrete time interval. Analysis of the departure, travel, and arrival time distributions shows that passengers smoothly adjusted their travel behaviour to the new train timetable. Analysis of the passing times at origin and destination station ticket gates in combination with the train timetable makes it possible to identify which train each traveller was likely to have boarded. This paper also proposes a method to assign a passenger to a combination of trains between an origin and destination stations. The method is examined using actual smart card data.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalPublic Transport
Issue number1
Publication statusPublished - 2012 Jul
Externally publishedYes


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

ASJC Scopus subject areas

  • Information Systems
  • Transportation
  • Mechanical Engineering
  • Management Science and Operations Research


Dive into the research topics of 'Estimation of behavioural change of railway passengers using smart card data'. Together they form a unique fingerprint.

Cite this