Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm

Autores
Nesmachnow, Sergio; Massobrio, Renzo; Arreche, Efraín; Mumford, Christine; Olivera, Ana Carolina; Vidal, Pablo Javier; Tchernykh, Andrei
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article presents a parallel evolutionary algorithm for public transport optimization by synchronizing traffic lights in the context of Bus Rapid Transit systems. The related optimization problem is NP-hard, so exact computational methods are not useful to solve real-world instances. Our research introduces a parallel evolutionary algorithm to efficiently configure and synchronize traffic lights and improve the average speed of buses and other vehicles. The Bus Rapid Transit on Garzón Avenue (Montevideo, Uruguay) is used as a case study. This is an interesting complex urban scenario due to the number of crossings, streets, and traffic lights in the zone. The experimental analysis compares the numerical results computed by the parallel evolutionary algorithm with a scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service when compared with the current reality, improving up to 15.3% the average bus speed and 24.8% the average speed of other vehicles. A multiobjective optimization analysis also demonstrates that additional improvements can be achieved by assigning different priorities to buses and other vehicles. In addition, further improvements can be achieved on a modified scenario simply by deleting a few bus stops and changing some traffic lights rules. The benefits of using a parallel solver are also highlighted, as the parallel version is able to accelerate the execution times up to 26.9× when compared with the sequential version.
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
Fil: Massobrio, Renzo. Universidad de la República; Uruguay
Fil: Arreche, Efraín. Universidad de la República; Uruguay
Fil: Mumford, Christine. Cardiff University; Reino Unido
Fil: Olivera, Ana Carolina. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Fil: Vidal, Pablo Javier. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Fil: Tchernykh, Andrei. Cicese Research Center; México
Materia
BUS RAPID TRANSIT
EVOLUTIONARY ALGORITHMS
TRAFFIC LIGHTS SYNCHRONIZATION
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:11336/174898
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithmNesmachnow, SergioMassobrio, RenzoArreche, EfraínMumford, ChristineOlivera, Ana CarolinaVidal, Pablo JavierTchernykh, AndreiBUS RAPID TRANSITEVOLUTIONARY ALGORITHMSTRAFFIC LIGHTS SYNCHRONIZATIONhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1This article presents a parallel evolutionary algorithm for public transport optimization by synchronizing traffic lights in the context of Bus Rapid Transit systems. The related optimization problem is NP-hard, so exact computational methods are not useful to solve real-world instances. Our research introduces a parallel evolutionary algorithm to efficiently configure and synchronize traffic lights and improve the average speed of buses and other vehicles. The Bus Rapid Transit on Garzón Avenue (Montevideo, Uruguay) is used as a case study. This is an interesting complex urban scenario due to the number of crossings, streets, and traffic lights in the zone. The experimental analysis compares the numerical results computed by the parallel evolutionary algorithm with a scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service when compared with the current reality, improving up to 15.3% the average bus speed and 24.8% the average speed of other vehicles. A multiobjective optimization analysis also demonstrates that additional improvements can be achieved by assigning different priorities to buses and other vehicles. In addition, further improvements can be achieved on a modified scenario simply by deleting a few bus stops and changing some traffic lights rules. The benefits of using a parallel solver are also highlighted, as the parallel version is able to accelerate the execution times up to 26.9× when compared with the sequential version.Fil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Massobrio, Renzo. Universidad de la República; UruguayFil: Arreche, Efraín. Universidad de la República; UruguayFil: Mumford, Christine. Cardiff University; Reino UnidoFil: Olivera, Ana Carolina. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Vidal, Pablo Javier. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Tchernykh, Andrei. Cicese Research Center; MéxicoElsevier2019-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/174898Nesmachnow, Sergio; Massobrio, Renzo; Arreche, Efraín; Mumford, Christine; Olivera, Ana Carolina; et al.; Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm; Elsevier; International Journal of Transportation Science and Technology; 8; 1; 3-2019; 53-672046-0430CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S2046043018300339info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijtst.2018.10.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:56:17Zoai:ri.conicet.gov.ar:11336/174898instacron: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 09:56:17.953CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
title Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
spellingShingle Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
Nesmachnow, Sergio
BUS RAPID TRANSIT
EVOLUTIONARY ALGORITHMS
TRAFFIC LIGHTS SYNCHRONIZATION
title_short Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
title_full Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
title_fullStr Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
title_full_unstemmed Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
title_sort Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm
dc.creator.none.fl_str_mv Nesmachnow, Sergio
Massobrio, Renzo
Arreche, Efraín
Mumford, Christine
Olivera, Ana Carolina
Vidal, Pablo Javier
Tchernykh, Andrei
author Nesmachnow, Sergio
author_facet Nesmachnow, Sergio
Massobrio, Renzo
Arreche, Efraín
Mumford, Christine
Olivera, Ana Carolina
Vidal, Pablo Javier
Tchernykh, Andrei
author_role author
author2 Massobrio, Renzo
Arreche, Efraín
Mumford, Christine
Olivera, Ana Carolina
Vidal, Pablo Javier
Tchernykh, Andrei
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv BUS RAPID TRANSIT
EVOLUTIONARY ALGORITHMS
TRAFFIC LIGHTS SYNCHRONIZATION
topic BUS RAPID TRANSIT
EVOLUTIONARY ALGORITHMS
TRAFFIC LIGHTS SYNCHRONIZATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This article presents a parallel evolutionary algorithm for public transport optimization by synchronizing traffic lights in the context of Bus Rapid Transit systems. The related optimization problem is NP-hard, so exact computational methods are not useful to solve real-world instances. Our research introduces a parallel evolutionary algorithm to efficiently configure and synchronize traffic lights and improve the average speed of buses and other vehicles. The Bus Rapid Transit on Garzón Avenue (Montevideo, Uruguay) is used as a case study. This is an interesting complex urban scenario due to the number of crossings, streets, and traffic lights in the zone. The experimental analysis compares the numerical results computed by the parallel evolutionary algorithm with a scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service when compared with the current reality, improving up to 15.3% the average bus speed and 24.8% the average speed of other vehicles. A multiobjective optimization analysis also demonstrates that additional improvements can be achieved by assigning different priorities to buses and other vehicles. In addition, further improvements can be achieved on a modified scenario simply by deleting a few bus stops and changing some traffic lights rules. The benefits of using a parallel solver are also highlighted, as the parallel version is able to accelerate the execution times up to 26.9× when compared with the sequential version.
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
Fil: Massobrio, Renzo. Universidad de la República; Uruguay
Fil: Arreche, Efraín. Universidad de la República; Uruguay
Fil: Mumford, Christine. Cardiff University; Reino Unido
Fil: Olivera, Ana Carolina. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Fil: Vidal, Pablo Javier. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
Fil: Tchernykh, Andrei. Cicese Research Center; México
description This article presents a parallel evolutionary algorithm for public transport optimization by synchronizing traffic lights in the context of Bus Rapid Transit systems. The related optimization problem is NP-hard, so exact computational methods are not useful to solve real-world instances. Our research introduces a parallel evolutionary algorithm to efficiently configure and synchronize traffic lights and improve the average speed of buses and other vehicles. The Bus Rapid Transit on Garzón Avenue (Montevideo, Uruguay) is used as a case study. This is an interesting complex urban scenario due to the number of crossings, streets, and traffic lights in the zone. The experimental analysis compares the numerical results computed by the parallel evolutionary algorithm with a scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service when compared with the current reality, improving up to 15.3% the average bus speed and 24.8% the average speed of other vehicles. A multiobjective optimization analysis also demonstrates that additional improvements can be achieved by assigning different priorities to buses and other vehicles. In addition, further improvements can be achieved on a modified scenario simply by deleting a few bus stops and changing some traffic lights rules. The benefits of using a parallel solver are also highlighted, as the parallel version is able to accelerate the execution times up to 26.9× when compared with the sequential version.
publishDate 2019
dc.date.none.fl_str_mv 2019-03
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 http://hdl.handle.net/11336/174898
Nesmachnow, Sergio; Massobrio, Renzo; Arreche, Efraín; Mumford, Christine; Olivera, Ana Carolina; et al.; Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm; Elsevier; International Journal of Transportation Science and Technology; 8; 1; 3-2019; 53-67
2046-0430
CONICET Digital
CONICET
url http://hdl.handle.net/11336/174898
identifier_str_mv Nesmachnow, Sergio; Massobrio, Renzo; Arreche, Efraín; Mumford, Christine; Olivera, Ana Carolina; et al.; Traffic lights synchronization for Bus Rapid Transit using a parallel evolutionary algorithm; Elsevier; International Journal of Transportation Science and Technology; 8; 1; 3-2019; 53-67
2046-0430
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://linkinghub.elsevier.com/retrieve/pii/S2046043018300339
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijtst.2018.10.002
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.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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