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dc.contributor.author
Sticco, Ignacio Mariano
dc.contributor.author
Frank, Guillermo Alberto
dc.contributor.author
Dorso, Claudio Oscar
dc.date.available
2021-11-03T13:11:15Z
dc.date.issued
2021-01
dc.identifier.citation
Sticco, Ignacio Mariano; Frank, Guillermo Alberto; Dorso, Claudio Oscar; Social Force Model parameter testing and optimization using a high stress real-life situation; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 561; 1-2021; 1-12
dc.identifier.issn
0378-4371
dc.identifier.uri
http://hdl.handle.net/11336/145806
dc.description.abstract
The escape panic version of the Social Force Model (SFM) is a suitable model for describing emergency evacuations. In this research, we analyze a real-life video, recorded at the opening of a store during a Black Friday event, which resembles an emergency evacuation (November 2017, South Africa). We measure the flow of pedestrians entering the store and found a higher value (〈J〉=6.7±0.8p/s) than the usually reported in “laboratory” conditions. We performed numerical simulations to recreate this event. The empirical measurements were compared against simulated evacuation curves corresponding to different sets of parameters currently in use in the literature. The results obtained suggest that the set of parameters corresponding to calibrations from laboratory experiments (involving pedestrians in which the safety of the participants is of major concern) or situations where the physical contact is negligible, produce simulations in which the agents evacuate faster than in the empirical scenario. To conclude the paper, we optimize two parameters of the model: the friction coefficient kt and the body force coefficient kn. The best fit we found could replicate the qualitative and quantitative behavior of the empirical evacuation curve. We also found that many different combinations in the parameter space can produce similar results in terms of the goodness of fit.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
EMPIRICAL MEASUREMENT
dc.subject
PEDESTRIAN DYNAMICS
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SOCIAL FORCE MODEL
dc.subject.classification
Otras Ciencias Físicas
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Ciencias Físicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Social Force Model parameter testing and optimization using a high stress real-life situation
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-09-20T14:31:47Z
dc.journal.volume
561
dc.journal.pagination
1-12
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Sticco, Ignacio Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
dc.description.fil
Fil: Frank, Guillermo Alberto. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
dc.journal.title
Physica A: Statistical Mechanics and its Applications
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0378437120306853
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.physa.2020.125299
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