Focusing on a specific crowd dynamics situation, including real life experiments and measurements, our paper targets a twofold aim: (1) we present a Bayesian probabilistic method to estimate the value and the uncertainty (in the form of a probability density function) of parameters in crowd dynamic models from the experimental data; and (2) we introduce a fitness measure for the models to classify a couple of model structures (forces) according to their fitness to the experimental data, preparing the stage for a more general model-selection and validation strategy inspired by probabilistic data analysis. Finally, we review the essential aspects of our experimental setup and measurement technique. Keywords: Crowd dynamics, parameter estimation, Bayes theorem, models classification, data analysis.
|Place of Publication||Eindhoven|
|Publisher||Technische Universiteit Eindhoven|
|Number of pages||20|
|Publication status||Published - 2014|
Corbetta, A., Muntean, A., Toschi, F., & Vafayi, K. (2014). Parameter estimation of social forces in crowd dynamics models via a probabilistic method. (CASA-report; Vol. 1408). Technische Universiteit Eindhoven.