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A novel approach for systematically calibrating transport planning model systems

Author

Listed:
  • Ali Najmi

    (The University of New South Wales)

  • Taha H. Rashidi

    (The University of New South Wales)

  • Eric J. Miller

    (University of Toronto)

Abstract

Calibration of a transport planning model system is a complex process. While trial-and-error methods and modelling expertise are still the backbone of calibration of transport models, analytical approaches automating the calibration process can improve the accuracy of the models. Introducing a model to guide modellers in the calibration process of large-scale transport planning model systems is the core of this study, where a systematic model for choosing the most appropriate models and parameters is discussed. The effectiveness of the proposed model is investigated by comparing three scenarios which are built on the Travel/Activity Scheduler for Household Agents model as a large-scale agent-based model system.

Suggested Citation

  • Ali Najmi & Taha H. Rashidi & Eric J. Miller, 2019. "A novel approach for systematically calibrating transport planning model systems," Transportation, Springer, vol. 46(5), pages 1915-1950, October.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:5:d:10.1007_s11116-018-9911-6
    DOI: 10.1007/s11116-018-9911-6
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    References listed on IDEAS

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    Cited by:

    1. Ali Najmi & Sahar Nazari & Farshid Safarighouzhdi & Eric J. Miller & Raina MacIntyre & Taha H. Rashidi, 2022. "Easing or tightening control strategies: determination of COVID-19 parameters for an agent-based model," Transportation, Springer, vol. 49(5), pages 1265-1293, October.

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