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

Focusing on a specific crowd dynamics situation, including real lifeexperiments and measurements, our paper targets a twofold aim: (1) wepresent a Bayesian probabilistic method to estimate the value and theuncertainty (in the form of a probability density function) ofparameters in crowd dynamic mode...

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Bibliographic Details
Main Authors: Alessandro Corbetta, Adrian Muntean, Kiamars Vafayi
Format: Article
Language:English
Published: AIMS Press 2014-11-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2015.12.337
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Summary:Focusing on a specific crowd dynamics situation, including real lifeexperiments and measurements, our paper targets a twofold aim: (1) wepresent a Bayesian probabilistic method to estimate the value and theuncertainty (in the form of a probability density function) ofparameters in crowd dynamic models from the experimental data; and (2)we introduce a fitness measure for the models to classify acouple of model structures (forces) according to their fitness to theexperimental data, preparing the stage for a more generalmodel-selection and validation strategy inspired by probabilistic dataanalysis. Finally, we review the essential aspects of our experimentalsetup and measurement technique.
ISSN:1551-0018