A stochastic schedule-following simulation model of bus routes

Le Minh Kieu, Dong Ngoduy, Nicolas Malleson, Edward Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)


Microsimulation models of bus routes allow transit operators to both better understand the dynamics of bus routes and facilitate better policy making. Several simulation models of bus routes have been proposed in the literature, including cellular-automata, bus-following and traffic-following models. The majority of these approaches aim to simulate the interactions of a bus with other buses (the bus-following model), with passengers or the surrounding traffic (the traffic-following model), but they all fail to consider the important interactions between buses and their schedules. In a conventional schedule-based public transport system, bus drivers aim to arrive at each stop on time. This means that they will either speed up or slow down if their vehicles are not meeting the schedule. The research within this paper is a novel contribution to the literature of bus route simulation. We introduce the first schedule-following model where buses try to adhere to their schedule in a conventional schedule-based public transport system. A simulated numerical analysis shows the characteristics of the proposed schedule-following model and compares it to existing models. Finally, the model is calibrated using Automatic Vehicle Location and Smart Card data from Brisbane, Australia. The results show good model performance against the observed data. The model is relatively simple, yet the fundamental mechanisms that drive the model are novel and it has the potential to be applied in any city with well-defined bus schedules.

Original languageEnglish
Pages (from-to)1588-1610
Number of pages23
JournalTransportmetrica B
Issue number1
Publication statusPublished - 23 Dec 2019


  • Bus route model
  • cross-entropy method
  • schedule-following

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Transportation


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