EURO Journal on Transportation and Logistics

, Volume 6, Issue 3, pp 247–270 | Cite as

Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty

  • Oded CatsEmail author
  • Zafeira Gkioulou
Research Paper


Public transport systems are subject to uncertainties related to traffic dynamic, operations, and passenger demand. Passenger waiting time is thus a random variable subject to day-to-day variations and the interaction between vehicle and passenger stochastic arrival processes. While the provision of real-time information could potentially reduce travel uncertainty, its impacts depend on the underlying service reliability, the performance of the prognosis scheme, and its perceived credibility. This paper presents a modeling framework for analyzing passengers’ learning process and adaptation with respect to waiting-time uncertainty and travel information. The model consists of a within-day network loading procedure and a day-to-day learning process, which are implemented in an agent-based simulation model. Each loop of within-day dynamics assigns travelers to paths by simulating the progress of individual travelers and vehicles as well as the generation and dissemination of travel information. The day-to-day learning model updates the accumulated memory of each traveler and updates consequently the credibility attributed to each information source based on the experienced waiting time. A case study in Stockholm demonstrates model capabilities and emphasizes the importance of behavioral adaptation when evaluating alternative measures which aim to improve service reliability.


Public transport Assignment model Waiting time Reliability Real-time information Learning 



The authors wish to thank Jens West for his invaluable critique, and the two reviewers for their constructive comments.


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Copyright information

© Springer-Verlag Berlin Heidelberg and EURO - The Association of European Operational Research Societies 2014

Authors and Affiliations

  1. 1.Department of Transport and PlanningDelft University of TechnologyDelftThe Netherlands
  2. 2.Department of Transport ScienceKTH Royal Institute of TechnologyStockholmSweden

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