Bayesian Demand Calibration for Dynamic Traffic Simulations

Gunnar Flötteröd (), Michel Bierlaire () and Kai Nagel ()
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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

Transportation Science, 2011, vol. 45, issue 4, 541-561

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.

Keywords: disaggregate demand calibration; dynamic traffic assignment; microsimulation; path flow estimation; Bayesian estimation (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:45:y:2011:i:4:p:541-561

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