Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization

Nowadays in current cities the increasing levels of pollution emissions and fuel consumption derived from the road traffic directly affect to the air quality, the economy, and specially the health of citizens. Therefore, improving the traffic flow is a mandatory task in order to mitigate such critic...

Descripción completa

Detalles Bibliográficos
Autores: Olivera, Ana Carolina, García Nieto, José Manuel, Alba, Enrique
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2015
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/108923
Acceso en línea:https://hdl.handle.net/11441/108923
https://doi.org/10.1007/s10489-014-0604-3
Access Level:acceso abierto
Palabra clave:Traffic Signal Timing
Particle Swarm Optimization
SUMO Microscopic Simulator of Urban Mobility
HBEFA Traffic Emission Model
id ES_d49e27893a5fc76be809f93d6bc1fbf7
oai_identifier_str oai:idus.us.es:11441/108923
network_acronym_str ES
network_name_str España
repository_id_str
spelling Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm OptimizationOlivera, Ana CarolinaGarcía Nieto, José ManuelAlba, EnriqueTraffic Signal TimingParticle Swarm OptimizationSUMO Microscopic Simulator of Urban MobilityHBEFA Traffic Emission ModelNowadays in current cities the increasing levels of pollution emissions and fuel consumption derived from the road traffic directly affect to the air quality, the economy, and specially the health of citizens. Therefore, improving the traffic flow is a mandatory task in order to mitigate such critical problems. In this work, we propose a Swarm Intelligence approach for optimizing signal light timing programs in metropolitan areas. In this way, we can improve the traffic flow of vehicles with the global target of reducing their fuel consumption and gas emissions (CO and NOx). In this article we optimize the timing programs of signal lights and analyze their effect in pollution by following the standard HBEFA as traffic emission model. In concrete, we are focused here on two large and heterogeneous urban instances located in the cities of Malaga and Seville (in Spain). In comparison with timing programs of signal lights predefined by experts (close to real ones), our proposal obtains significant reductions in terms of the emission rate and the total fuel consumption.Junta de Andalucía P07-TIC-03044Ministerio de Ciencia e Innovación TIN2011-28194Ministerio de Ciencia e Innovación TIN2008-06491-C04-01Ministerio de Ciencia, Innovación y Universidades BES-2009-018767SpringerCiencias de la Computación e Inteligencia ArtificialJunta de AndalucíaMinisterio de Ciencia e Innovación (MICIN). EspañaMinisterio de Ciencia, Innovación y Universidades (MICINN). España2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/108923https://doi.org/10.1007/s10489-014-0604-3reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésApplied Intelligence, 42, 389-405.P07-TIC- 03044TIN2011-28194TIN2008-06491-C04-01BES-2009-018767https://link.springer.com/article/10.1007/s10489-014-0604-3info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1089232026-06-17T12:51:07Z
dc.title.none.fl_str_mv Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
title Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
spellingShingle Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
Olivera, Ana Carolina
Traffic Signal Timing
Particle Swarm Optimization
SUMO Microscopic Simulator of Urban Mobility
HBEFA Traffic Emission Model
title_short Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
title_full Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
title_fullStr Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
title_full_unstemmed Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
title_sort Reducing Vehicle Emissions and Fuel Consumption in the City by Using Particle Swarm Optimization
dc.creator.none.fl_str_mv Olivera, Ana Carolina
García Nieto, José Manuel
Alba, Enrique
author Olivera, Ana Carolina
author_facet Olivera, Ana Carolina
García Nieto, José Manuel
Alba, Enrique
author_role author
author2 García Nieto, José Manuel
Alba, Enrique
author2_role author
author
dc.contributor.none.fl_str_mv Ciencias de la Computación e Inteligencia Artificial
Junta de Andalucía
Ministerio de Ciencia e Innovación (MICIN). España
Ministerio de Ciencia, Innovación y Universidades (MICINN). España
dc.subject.none.fl_str_mv Traffic Signal Timing
Particle Swarm Optimization
SUMO Microscopic Simulator of Urban Mobility
HBEFA Traffic Emission Model
topic Traffic Signal Timing
Particle Swarm Optimization
SUMO Microscopic Simulator of Urban Mobility
HBEFA Traffic Emission Model
description Nowadays in current cities the increasing levels of pollution emissions and fuel consumption derived from the road traffic directly affect to the air quality, the economy, and specially the health of citizens. Therefore, improving the traffic flow is a mandatory task in order to mitigate such critical problems. In this work, we propose a Swarm Intelligence approach for optimizing signal light timing programs in metropolitan areas. In this way, we can improve the traffic flow of vehicles with the global target of reducing their fuel consumption and gas emissions (CO and NOx). In this article we optimize the timing programs of signal lights and analyze their effect in pollution by following the standard HBEFA as traffic emission model. In concrete, we are focused here on two large and heterogeneous urban instances located in the cities of Malaga and Seville (in Spain). In comparison with timing programs of signal lights predefined by experts (close to real ones), our proposal obtains significant reductions in terms of the emission rate and the total fuel consumption.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/108923
https://doi.org/10.1007/s10489-014-0604-3
url https://hdl.handle.net/11441/108923
https://doi.org/10.1007/s10489-014-0604-3
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Applied Intelligence, 42, 389-405.
P07-TIC- 03044
TIN2011-28194
TIN2008-06491-C04-01
BES-2009-018767
https://link.springer.com/article/10.1007/s10489-014-0604-3
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869420562724421632
score 15,300719

Similares en LA Referencia