Dynamical capacity drop in a nonlinear stochastic traffic model

Detalhes bibliográficos
Autor(a) principal: Qian, Wei-Liang [UNESP]
Data de Publicação: 2017
Outros Autores: Siqueira, Adriano F., Machado, Romuel F., Lin, Kai, Grant, Ted W.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
DOI: 10.1016/j.trb.2017.09.017
Texto Completo: http://dx.doi.org/10.1016/j.trb.2017.09.017
http://hdl.handle.net/11449/163504
Resumo: In this work, we show that the inverse-lambda shape in the fundamental diagram of traffic flow can be produced dynamically by a simple nonlinear mesoscopic model with stochastic noises. The proposed model is based on the gas-kinetic theory of the traffic system. In our approach, the nonlinearity leads to the coexistence of different traffic states. The scattering of the data is thus attributed to the noise terms introduced in the stochastic differential equations and the transition among the various traffic states. Most importantly, the observed inverse-lambda shape and the associated sudden jump of physical quantities arise due to the effect of stochastic noises on the stability of the system. The model parameters are calibrated, and a qualitative agreement is obtained between the data and the numerical simulations. (C) 2017 Elsevier Ltd. All rights reserved.
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spelling Dynamical capacity drop in a nonlinear stochastic traffic modelIn this work, we show that the inverse-lambda shape in the fundamental diagram of traffic flow can be produced dynamically by a simple nonlinear mesoscopic model with stochastic noises. The proposed model is based on the gas-kinetic theory of the traffic system. In our approach, the nonlinearity leads to the coexistence of different traffic states. The scattering of the data is thus attributed to the noise terms introduced in the stochastic differential equations and the transition among the various traffic states. Most importantly, the observed inverse-lambda shape and the associated sudden jump of physical quantities arise due to the effect of stochastic noises on the stability of the system. The model parameters are calibrated, and a qualitative agreement is obtained between the data and the numerical simulations. (C) 2017 Elsevier Ltd. All rights reserved.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Sao Paulo, Escola Engn Lorena, Dept Ciencias Baicas & Ambientais, BR-12602810 Lorena, SP, BrazilUniv Estadual Paulista, Fac Engn Guaratingueta, Dept Fis & Quim, BR-12516410 Guaratingueta, SP, BrazilUniv Fed Ouro Preto, Dept Fis, BR-45300000 Ouro Preto, MG, BrazilUniv Estadual Paulista, Fac Engn Guaratingueta, Dept Fis & Quim, BR-12516410 Guaratingueta, SP, BrazilElsevier B.V.Universidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Univ Fed Ouro PretoQian, Wei-Liang [UNESP]Siqueira, Adriano F.Machado, Romuel F.Lin, KaiGrant, Ted W.2018-11-26T17:42:18Z2018-11-26T17:42:18Z2017-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article328-339application/pdfhttp://dx.doi.org/10.1016/j.trb.2017.09.017Transportation Research Part B-methodological. Oxford: Pergamon-elsevier Science Ltd, v. 105, p. 328-339, 2017.0191-2615http://hdl.handle.net/11449/16350410.1016/j.trb.2017.09.017WOS:000415780700016WOS000415780700016.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengTransportation Research Part B-methodological3,109info:eu-repo/semantics/openAccess2024-07-01T20:52:08Zoai:repositorio.unesp.br:11449/163504Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:13:33.283068Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Dynamical capacity drop in a nonlinear stochastic traffic model
title Dynamical capacity drop in a nonlinear stochastic traffic model
spellingShingle Dynamical capacity drop in a nonlinear stochastic traffic model
Dynamical capacity drop in a nonlinear stochastic traffic model
Qian, Wei-Liang [UNESP]
Qian, Wei-Liang [UNESP]
title_short Dynamical capacity drop in a nonlinear stochastic traffic model
title_full Dynamical capacity drop in a nonlinear stochastic traffic model
title_fullStr Dynamical capacity drop in a nonlinear stochastic traffic model
Dynamical capacity drop in a nonlinear stochastic traffic model
title_full_unstemmed Dynamical capacity drop in a nonlinear stochastic traffic model
Dynamical capacity drop in a nonlinear stochastic traffic model
title_sort Dynamical capacity drop in a nonlinear stochastic traffic model
author Qian, Wei-Liang [UNESP]
author_facet Qian, Wei-Liang [UNESP]
Qian, Wei-Liang [UNESP]
Siqueira, Adriano F.
Machado, Romuel F.
Lin, Kai
Grant, Ted W.
Siqueira, Adriano F.
Machado, Romuel F.
Lin, Kai
Grant, Ted W.
author_role author
author2 Siqueira, Adriano F.
Machado, Romuel F.
Lin, Kai
Grant, Ted W.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
Univ Fed Ouro Preto
dc.contributor.author.fl_str_mv Qian, Wei-Liang [UNESP]
Siqueira, Adriano F.
Machado, Romuel F.
Lin, Kai
Grant, Ted W.
description In this work, we show that the inverse-lambda shape in the fundamental diagram of traffic flow can be produced dynamically by a simple nonlinear mesoscopic model with stochastic noises. The proposed model is based on the gas-kinetic theory of the traffic system. In our approach, the nonlinearity leads to the coexistence of different traffic states. The scattering of the data is thus attributed to the noise terms introduced in the stochastic differential equations and the transition among the various traffic states. Most importantly, the observed inverse-lambda shape and the associated sudden jump of physical quantities arise due to the effect of stochastic noises on the stability of the system. The model parameters are calibrated, and a qualitative agreement is obtained between the data and the numerical simulations. (C) 2017 Elsevier Ltd. All rights reserved.
publishDate 2017
dc.date.none.fl_str_mv 2017-11-01
2018-11-26T17:42:18Z
2018-11-26T17:42:18Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.trb.2017.09.017
Transportation Research Part B-methodological. Oxford: Pergamon-elsevier Science Ltd, v. 105, p. 328-339, 2017.
0191-2615
http://hdl.handle.net/11449/163504
10.1016/j.trb.2017.09.017
WOS:000415780700016
WOS000415780700016.pdf
url http://dx.doi.org/10.1016/j.trb.2017.09.017
http://hdl.handle.net/11449/163504
identifier_str_mv Transportation Research Part B-methodological. Oxford: Pergamon-elsevier Science Ltd, v. 105, p. 328-339, 2017.
0191-2615
10.1016/j.trb.2017.09.017
WOS:000415780700016
WOS000415780700016.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Transportation Research Part B-methodological
3,109
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 328-339
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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dc.identifier.doi.none.fl_str_mv 10.1016/j.trb.2017.09.017