Optimal control based heuristic for congestion reduction in traffic networks

Autores
Mayorano, Fernando Javier; Rubiales, Aldo José; Lotito, Pablo Andrés
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The principal purpose of this work is to test the TUC strategy in a simple case using a micro-simulator designed ad hoc, previous to its real implementation. Using concepts of traffic engineering we describe a well known dynamic linear model of traffic flow in a urban traffic network that is controlled using the traffic-light times. This simplified model allows to obtain a Riccati feedback matrix and compute traffic-light times that will improve the congestion levels. We present some numerical experiments made with the model on an academic example and we validated them with a microscopic simulator that we have created based on Car Following theory and discrete event models.
Materia
Ciencias de la Computación
Optimal Control
LQ-Control
Urban traffic models
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/3997
Acceder
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oai_identifier_str oai:digital.cic.gba.gob.ar:11746/3997
network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Optimal control based heuristic for congestion reduction in traffic networksMayorano, Fernando JavierRubiales, Aldo JoséLotito, Pablo AndrésCiencias de la ComputaciónOptimal ControlLQ-ControlUrban traffic modelsThe principal purpose of this work is to test the TUC strategy in a simple case using a micro-simulator designed ad hoc, previous to its real implementation. Using concepts of traffic engineering we describe a well known dynamic linear model of traffic flow in a urban traffic network that is controlled using the traffic-light times. This simplified model allows to obtain a Riccati feedback matrix and compute traffic-light times that will improve the congestion levels. We present some numerical experiments made with the model on an academic example and we validated them with a microscopic simulator that we have created based on Car Following theory and discrete event models.UNS Printing Office2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/3997enginfo:eu-repo/semantics/altIdentifier/issn/0327-0793info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-11-13T08:42:53Zoai:digital.cic.gba.gob.ar:11746/3997Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-11-13 08:42:53.657CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Optimal control based heuristic for congestion reduction in traffic networks
title Optimal control based heuristic for congestion reduction in traffic networks
spellingShingle Optimal control based heuristic for congestion reduction in traffic networks
Mayorano, Fernando Javier
Ciencias de la Computación
Optimal Control
LQ-Control
Urban traffic models
title_short Optimal control based heuristic for congestion reduction in traffic networks
title_full Optimal control based heuristic for congestion reduction in traffic networks
title_fullStr Optimal control based heuristic for congestion reduction in traffic networks
title_full_unstemmed Optimal control based heuristic for congestion reduction in traffic networks
title_sort Optimal control based heuristic for congestion reduction in traffic networks
dc.creator.none.fl_str_mv Mayorano, Fernando Javier
Rubiales, Aldo José
Lotito, Pablo Andrés
author Mayorano, Fernando Javier
author_facet Mayorano, Fernando Javier
Rubiales, Aldo José
Lotito, Pablo Andrés
author_role author
author2 Rubiales, Aldo José
Lotito, Pablo Andrés
author2_role author
author
dc.subject.none.fl_str_mv Ciencias de la Computación
Optimal Control
LQ-Control
Urban traffic models
topic Ciencias de la Computación
Optimal Control
LQ-Control
Urban traffic models
dc.description.none.fl_txt_mv The principal purpose of this work is to test the TUC strategy in a simple case using a micro-simulator designed ad hoc, previous to its real implementation. Using concepts of traffic engineering we describe a well known dynamic linear model of traffic flow in a urban traffic network that is controlled using the traffic-light times. This simplified model allows to obtain a Riccati feedback matrix and compute traffic-light times that will improve the congestion levels. We present some numerical experiments made with the model on an academic example and we validated them with a microscopic simulator that we have created based on Car Following theory and discrete event models.
description The principal purpose of this work is to test the TUC strategy in a simple case using a micro-simulator designed ad hoc, previous to its real implementation. Using concepts of traffic engineering we describe a well known dynamic linear model of traffic flow in a urban traffic network that is controlled using the traffic-light times. This simplified model allows to obtain a Riccati feedback matrix and compute traffic-light times that will improve the congestion levels. We present some numerical experiments made with the model on an academic example and we validated them with a microscopic simulator that we have created based on Car Following theory and discrete event models.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/3997
url https://digital.cic.gba.gob.ar/handle/11746/3997
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0327-0793
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv UNS Printing Office
publisher.none.fl_str_mv UNS Printing Office
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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