A nonlinear algorithm for traffic estimation with state constraints

Autores
Risso, Mariano Angel; Bhouri, Neila; Lotito, Pablo Andres; Rubiales, Aldo Jose
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
We present a real-time traffic state estimation algorithm for motorways. Natural constraints on the variables, like practical bounds on densities and velocities, are incorporated in the estimation process aiming to obtain better estimation results.The dynamic equation for the evolution of the traffic is defined by a second order macroscopic model which computes the density, the flow and the mean speed according to several nonlinear equations, but nothing avoids the results being out of those practical bounds. Different extensions of the Kalman method were already applied to this problem, but none of them consider natural constraints in the variables. On the other hand, general filter methods have been designed to cope with a constrained state. In order to incorporate the natural constraints of the traffic model, we adapt one of those methods based on the Unscented Kalman Filter. To validate the approach, many simulation cases over a freeway section were made using a microscopic simulation tool and comparing the Extended Kalman Approach with the proposed one.
Fil: Risso, Mariano Angel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
Fil: Bhouri, Neila. Université Paris Est; Francia
Fil: Lotito, Pablo Andres. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
Fil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
20th EURO Working Group on Transportation Meeting (EWGT 2017)
Budapest
Hungría
Budapest University of Technology and Economics
Materia
ESTIMACION
ESTADO
TRAFICO
KALMAN
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/137242
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A nonlinear algorithm for traffic estimation with state constraintsRisso, Mariano AngelBhouri, NeilaLotito, Pablo AndresRubiales, Aldo JoseESTIMACIONESTADOTRAFICOKALMANhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1We present a real-time traffic state estimation algorithm for motorways. Natural constraints on the variables, like practical bounds on densities and velocities, are incorporated in the estimation process aiming to obtain better estimation results.The dynamic equation for the evolution of the traffic is defined by a second order macroscopic model which computes the density, the flow and the mean speed according to several nonlinear equations, but nothing avoids the results being out of those practical bounds. Different extensions of the Kalman method were already applied to this problem, but none of them consider natural constraints in the variables. On the other hand, general filter methods have been designed to cope with a constrained state. In order to incorporate the natural constraints of the traffic model, we adapt one of those methods based on the Unscented Kalman Filter. To validate the approach, many simulation cases over a freeway section were made using a microscopic simulation tool and comparing the Extended Kalman Approach with the proposed one.Fil: Risso, Mariano Angel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: Bhouri, Neila. Université Paris Est; FranciaFil: Lotito, Pablo Andres. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; ArgentinaFil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina20th EURO Working Group on Transportation Meeting (EWGT 2017)BudapestHungríaBudapest University of Technology and EconomicsElsevierEsztergár Kiss. DomokosMátrai, TamásTóth, JánosVarga, István2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectOtroJournalhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/137242A nonlinear algorithm for traffic estimation with state constraints; 20th EURO Working Group on Transportation Meeting (EWGT 2017); Budapest; Hungría; 2017; 600-6082352-1465CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2352146517310256info:eu-repo/semantics/altIdentifier/doi/10.1016/j.trpro.2017.12.128Internacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:57:45Zoai:ri.conicet.gov.ar:11336/137242instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:57:45.977CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A nonlinear algorithm for traffic estimation with state constraints
title A nonlinear algorithm for traffic estimation with state constraints
spellingShingle A nonlinear algorithm for traffic estimation with state constraints
Risso, Mariano Angel
ESTIMACION
ESTADO
TRAFICO
KALMAN
title_short A nonlinear algorithm for traffic estimation with state constraints
title_full A nonlinear algorithm for traffic estimation with state constraints
title_fullStr A nonlinear algorithm for traffic estimation with state constraints
title_full_unstemmed A nonlinear algorithm for traffic estimation with state constraints
title_sort A nonlinear algorithm for traffic estimation with state constraints
dc.creator.none.fl_str_mv Risso, Mariano Angel
Bhouri, Neila
Lotito, Pablo Andres
Rubiales, Aldo Jose
author Risso, Mariano Angel
author_facet Risso, Mariano Angel
Bhouri, Neila
Lotito, Pablo Andres
Rubiales, Aldo Jose
author_role author
author2 Bhouri, Neila
Lotito, Pablo Andres
Rubiales, Aldo Jose
author2_role author
author
author
dc.contributor.none.fl_str_mv Esztergár Kiss. Domokos
Mátrai, Tamás
Tóth, János
Varga, István
dc.subject.none.fl_str_mv ESTIMACION
ESTADO
TRAFICO
KALMAN
topic ESTIMACION
ESTADO
TRAFICO
KALMAN
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We present a real-time traffic state estimation algorithm for motorways. Natural constraints on the variables, like practical bounds on densities and velocities, are incorporated in the estimation process aiming to obtain better estimation results.The dynamic equation for the evolution of the traffic is defined by a second order macroscopic model which computes the density, the flow and the mean speed according to several nonlinear equations, but nothing avoids the results being out of those practical bounds. Different extensions of the Kalman method were already applied to this problem, but none of them consider natural constraints in the variables. On the other hand, general filter methods have been designed to cope with a constrained state. In order to incorporate the natural constraints of the traffic model, we adapt one of those methods based on the Unscented Kalman Filter. To validate the approach, many simulation cases over a freeway section were made using a microscopic simulation tool and comparing the Extended Kalman Approach with the proposed one.
Fil: Risso, Mariano Angel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
Fil: Bhouri, Neila. Université Paris Est; Francia
Fil: Lotito, Pablo Andres. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
Fil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina
20th EURO Working Group on Transportation Meeting (EWGT 2017)
Budapest
Hungría
Budapest University of Technology and Economics
description We present a real-time traffic state estimation algorithm for motorways. Natural constraints on the variables, like practical bounds on densities and velocities, are incorporated in the estimation process aiming to obtain better estimation results.The dynamic equation for the evolution of the traffic is defined by a second order macroscopic model which computes the density, the flow and the mean speed according to several nonlinear equations, but nothing avoids the results being out of those practical bounds. Different extensions of the Kalman method were already applied to this problem, but none of them consider natural constraints in the variables. On the other hand, general filter methods have been designed to cope with a constrained state. In order to incorporate the natural constraints of the traffic model, we adapt one of those methods based on the Unscented Kalman Filter. To validate the approach, many simulation cases over a freeway section were made using a microscopic simulation tool and comparing the Extended Kalman Approach with the proposed one.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Otro
Journal
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/137242
A nonlinear algorithm for traffic estimation with state constraints; 20th EURO Working Group on Transportation Meeting (EWGT 2017); Budapest; Hungría; 2017; 600-608
2352-1465
CONICET Digital
CONICET
url http://hdl.handle.net/11336/137242
identifier_str_mv A nonlinear algorithm for traffic estimation with state constraints; 20th EURO Working Group on Transportation Meeting (EWGT 2017); Budapest; Hungría; 2017; 600-608
2352-1465
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2352146517310256
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.trpro.2017.12.128
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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