Dynamical capacity drop in a nonlinear stochastic traffic model
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1822182509217054720 |
dc.identifier.doi.none.fl_str_mv |
10.1016/j.trb.2017.09.017 |