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Calibration of large-scale transport planning models: a structured approach

Author

Listed:
  • Ali Najmi

    (The University of New South Wales)

  • Taha H. Rashidi

    (The University of New South Wales)

  • James Vaughan

    (University of Toronto)

  • Eric J. Miller

    (University of Toronto)

Abstract

Traditionally, transport planning model systems are estimated and calibrated in an unstructured way, which does not allow for interactions among included parameters to be considered. Furthermore, the computational burden of model systems plays a key role in choosing a calibration approach, and usually forces modellers to calibrate demand-side and network models separately. Also, trial-and-error methods and expert opinion are currently the backbones of transport model calibration, which leaves room for error in the calibrated parameters. This paper addresses these challenges and suggests a structured approach for determining optimal calibrated transport model parameters. This approach involves joint estimation and calibration of demand and network models, with a major focus on avoiding any manipulation of the OD matrix. The approach can be applied to static or dynamic traffic assignments. The approach is applied by calibrating GTAModel—an example of a large-scale agent-based model system from Toronto, Canada.

Suggested Citation

  • Ali Najmi & Taha H. Rashidi & James Vaughan & Eric J. Miller, 2020. "Calibration of large-scale transport planning models: a structured approach," Transportation, Springer, vol. 47(4), pages 1867-1905, August.
    • Handle: RePEc:kap:transp:v:47:y:2020:i:4:d:10.1007_s11116-019-10018-6
    DOI: 10.1007/s11116-019-10018-6
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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.
    2. Najmi, Ali & Bostanara, Maryam & Gu, Ziyuan & Rashidi, Taha H., 2021. "On-street parking management and pricing policies: An evaluation from a system enhancement perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 128-151.

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