Parameter estimation of social forces in pedestrian dynamics models via a probabilistic method
2015 (English)In: Mathematical Biosciences and Engineering, ISSN 1547-1063, E-ISSN 1551-0018, Vol. 12, no 2, 337-356 p.Article in journal (Refereed) PublishedText
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.
Place, publisher, year, edition, pages
American Institute of Mathematical Sciences, 2015. Vol. 12, no 2, 337-356 p.
Bayesian estimation, crowd dynamics, parameter estimation, data analysis, statistics
Probability Theory and Statistics Social Sciences
Research subject Mathematics
IdentifiersURN: urn:nbn:se:kau:diva-39775DOI: 10.3934/mbe.2015.12.337ISI: 000351562400007ScopusID: 2-s2.0-84920170508OAI: oai:DiVA.org:kau-39775DiVA: diva2:901178