Data-driven simulation for pedestrian avoiding a  fixed obstacle

Martin, Rafael F.; Parisi, Daniel

ponencia en congreso.page.titleprefix
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.