Parameter estimation of social forces in crowd dynamics models via a probabilistic method

A. Corbetta, A. Muntean, F. Toschi, K. Vafayi

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Abstract

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.
Original languageEnglish
Place of PublicationEindhoven
PublisherTechnische Universiteit Eindhoven
Number of pages20
Publication statusPublished - 2014

Publication series

NameCASA-report
Volume1408
ISSN (Print)0926-4507

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  • Cite this

    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.