Public Transport

, Volume 4, Issue 1, pp 1–16 | Cite as

Estimation of behavioural change of railway passengers using smart card data

  • Yasuo Asakura
  • Takamasa Iryo
  • Yoshiki Nakajima
  • Takahiko Kusakabe
Original Paper

Abstract

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.

Keywords

Smart card data Travel behaviour Railway passenger Train timetable 

References

  1. Asakura Y, Iryo T, Nakajima Y, Sugita K, Kitano S (2008a) TDM experiment of railway and a shopping centre using smart card system. In: Proc TDM symp 2008 in Wien Google Scholar
  2. Asakura Y, Iryo T, Nakajima Y, Kusakabe T, Takagi Y, Kashiwadani M (2008b) Behavioural analysis of railway passengers using smart card data. In: Proc urban transp 2008 in Malta Google Scholar
  3. Bagchi M, White PR (2005) The potential of public transport smart card data. Transp Policy 12(5):464–472 CrossRefGoogle Scholar
  4. Chu KKA, Chapleau R (2008) Enriching archived smart card transaction data for transit demand modeling. Transp res board 87th annu meet 2007 Paper #08-0596 Google Scholar
  5. Kusakabe T, Takagi Y, Iryo T, Asakura Y (2010) Estimation method for railway passengers’ train choice behavior with smart card transaction data. Transportation 37(5):731–749 CrossRefGoogle Scholar
  6. Lehtonen M, Rosenberg M, Rasanen J, Sirkia A (2002) Utilization of the smart card payment system (SCPS) data in public transport planning and statistics. In: 9th world congr intell transp syst, ITS America Google Scholar
  7. Morency C, Trepanier M, Agard B (2007) Measuring transit use variability with smart-card data. Transp Policy 14(3):193–203 CrossRefGoogle Scholar
  8. Sahin I, Altun YB (2007) Potential uses of electronic fare payment records for public transit agencies. ITE J 77(12):22–27 Google Scholar
  9. Trepanier M, Tranchant N, Chapleau R (2007) Individual trip destination estimation in a transit smart card automated fare collection system. J Intell Transp Syst 11(1):1–14 CrossRefGoogle Scholar
  10. Utsunomiya M, Attanucci J, Wilson N (2006) Potential uses of transit smart card registration and transaction data to improve transit planning. Transp Res Rec 1971:119–126 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Yasuo Asakura
    • 1
  • Takamasa Iryo
    • 2
  • Yoshiki Nakajima
    • 2
  • Takahiko Kusakabe
    • 1
  1. 1.Department of Civil EngineeringTokyo Institute of TechnologyMeguro-ku, TokyoJapan
  2. 2.Department of Civil EngineeringKobe UniversityKobeJapan

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