Flötteröd, G., Bierlaire, M., and Nagel, K. (2011)
Bayesian demand calibration for dynamic traffic simulations, Transportation Science 45(4):541-561.
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.
doi:10.1287/trsc.1100.0367 (click here for the full paper)