Ponencia en Congreso: Data-driven simulation for pedestrian avoiding a fixed obstacle
dc.contributor.author | Martin, Rafael F. | |
dc.contributor.author | Parisi, Daniel | |
dc.date.accessioned | 2022-04-28T16:10:35Z | |
dc.date.available | 2022-04-28T16:10:35Z | |
dc.date.issued | 2019-07 | |
dc.description.abstract | "Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which does not have to deal with a huge number of free parameters as in the case of multilayer neural networks. Although the method is general, we focus on the one pedestrian—one obstacle problem. The proposed model allows us to simulate the trajectory of a pedestrian avoiding an obstacle from any direction." | en |
dc.identifier.issn | 0930-8989 | |
dc.identifier.uri | http://ri.itba.edu.ar/handle/123456789/3827 | |
dc.language.iso | en | en |
dc.relation | info:eu-repo/grantAgreement/ANPCyT/PID/2015-003/AR. Ciudad Autónoma de Buenos Aires | |
dc.relation | info:eu-repo/grantAgreement/ITBACyT/2018-42/AR. Ciudad Autónoma de Buenos Aires | |
dc.relation | info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-55973-1_25 | |
dc.subject | FLUJO CONFINADO | es |
dc.subject | MATERIALES GRANULARES | es |
dc.subject | PEATONES | es |
dc.subject | REDES NEURONALES | es |
dc.title | Data-driven simulation for pedestrian avoiding a fixed obstacle | en |
dc.type | Ponencias en Congresos | es |
dc.type | info:eu-repo/semantics/acceptedVersion | |
dspace.entity.type | Ponencia en Congreso | |
itba.description.filiation | Fil: Martin, Rafael F. Instituto Tecnológico de Buenos Aires; Argentina. | |
itba.description.filiation | Fil: Parisi, Daniel. Instituto Tecnológico de Buenos Aires; Argentina. | |
itba.description.filiation | Fil: Parisi, Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. |
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