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Parameter estimation of social forces in pedestrian dynamics models via a probabilistic method
Eindhoven University of Technolology; Politecnio di Torino.
Eindhoven University of Technolology. (Mathematics)ORCID iD: 0000-0002-1160-0007
Eindhoven University of Technolology.
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) Published
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Abstract [en]

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.
Keyword [en]
Bayesian estimation, crowd dynamics, parameter estimation, data analysis, statistics
National Category
Probability Theory and Statistics Social Sciences
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:kau:diva-39775DOI: 10.3934/mbe.2015.12.337ISI: 000351562400007Scopus ID: 2-s2.0-84920170508OAI: oai:DiVA.org:kau-39775DiVA: diva2:901178
Available from: 2016-02-06 Created: 2016-02-06 Last updated: 2017-03-13

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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