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Bayesian Demand Calibration for Dynamic Traffic Simulations

Author

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  • Gunnar Flötteröd

    (École Polytechnique Fédérale de Lausanne (EFPL), School of Architecture, Civil and Environmental Engineering (ENAC), Transport and Mobility Laboratory (TRANSP-OR), 1015 Lausanne, Switzerland)

  • Michel Bierlaire

    (École Polytechnique Fédérale de Lausanne (EFPL), School of Architecture, Civil and Environmental Engineering (ENAC), Transport and Mobility Laboratory (TRANSP-OR), 1015 Lausanne, Switzerland)

  • Kai Nagel

    (Technische Universität Berlin (TUB), Institüt für Land- und Seeverkehr (ILS), Fachgebiet für Verkehrssystemplanung und Verkehrstelematik (VSP), 10623 Berlin, Germany)

Abstract

We present an operational framework for the calibration of demand models for dynamic traffic simulations, where calibration refers to the estimation of a structurally predefined model's parameters from real data. Our focus is on disaggregate simulators that represent every traveler individually. We calibrate, also at an individual level, arbitrary choice dimensions within a Bayesian framework, where the analyst's prior knowledge is represented by the dynamic traffic simulator itself and the measurements are comprised of time-dependent traffic counts. The approach is equally applicable to an equilibrium-based planning model and to a telematics model of spontaneous and imperfectly informed drivers. It is based on consistent mathematical arguments, yet it is applicable in a purely simulation-based environment and, as our experimental results show, is capable of handling large scenarios.

Suggested Citation

  • Gunnar Flötteröd & Michel Bierlaire & Kai Nagel, 2011. "Bayesian Demand Calibration for Dynamic Traffic Simulations," Transportation Science, INFORMS, vol. 45(4), pages 541-561, November.
    • Handle: RePEc:inm:ortrsc:v:45:y:2011:i:4:p:541-561
    DOI: 10.1287/trsc.1100.0367
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    References listed on IDEAS

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