Bayesian demand calibration for dynamic traffic simulations
2011 (English)In: Transportation Science, ISSN 0041-1655, Vol. 45, no 4, 541-561 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2011. Vol. 45, no 4, 541-561 p.
disaggregate demand calibration, dynamic traffic assignment, microsimulation, path flow estimation, Bayesian estimation
Transport Systems and Logistics
IdentifiersURN: urn:nbn:se:kth:diva-76743DOI: 10.1287/trsc.1100.0367ISI: 000297208700006OAI: oai:DiVA.org:kth-76743DiVA: diva2:491116
FunderTrenOp, Transport Research Environment with Novel Perspectives
TSC import 811 2012-02-06. QC 201202072012-02-062012-02-062012-06-12Bibliographically approved