Show simple item record

Article

dc.creatorGarcía Nieto, José Manueles
dc.creatorAlba, Enriquees
dc.creatorOlivera, Ana Carolinaes
dc.date.accessioned2021-05-14T07:27:26Z
dc.date.available2021-05-14T07:27:26Z
dc.date.issued2012
dc.identifier.citationGarcía Nieto, J.M., Alba, E. y Olivera, A.C. (2012). Swarm intelligence for traffic light scheduling: Application to real urban areas. Engineering Applications of Artificial Intelligence, 25 (2), 274-283.
dc.identifier.issn0952-1976es
dc.identifier.urihttps://hdl.handle.net/11441/109031
dc.description.abstractCongestion, pollution, security, parking, noise, and many other problems derived from vehicular traffic are present every day in most cities around the world. The growing number of traffic lights that control the vehicular flow requires a complex scheduling, and hence, automatic systems are indispensable nowadays for optimally tackling this task. In this work, we propose a Swarm Intelligence approach to find successful cycle programs of traffic lights. Using a microscopic traffic simulator, the solutions obtained by our algorithm are evaluated in the context of two large and heterogeneous metropolitan areas located in the cities of Málaga and Sevilla (in Spain). In comparison with cycle programs predefined by experts (close to real ones), our proposal obtains significant profits in terms of two main indicators: the number of vehicles that reach their destinations on time and the global trip time.es
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades TIN2008-06491-C04-01es
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades BES-2009-018767es
dc.description.sponsorshipJunta de Andalucía P07-TIC-03044es
dc.formatapplication/pdfes
dc.format.extent10es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofEngineering Applications of Artificial Intelligence, 25 (2), 274-283.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectTraffic Light Schedulinges
dc.subjectParticle Swarm Optimizationes
dc.subjectSUMO Microscopic Simulator of Urban Mobilityes
dc.subjectCycle program optimizationes
dc.subjectRealistic traffic instanceses
dc.titleSwarm intelligence for traffic light scheduling: Application to real urban areases
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDTIN2008-06491-C04-01es
dc.relation.projectIDBES-2009-018767es
dc.relation.projectIDP07-TIC-03044es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0952197611000777es
dc.identifier.doi10.1016/j.engappai.2011.04.011es
dc.journaltitleEngineering Applications of Artificial Intelligencees
dc.publication.volumen25es
dc.publication.issue2es
dc.publication.initialPage274es
dc.publication.endPage283es
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (MICINN). Españaes
dc.contributor.funderJunta de Andalucíaes

FilesSizeFormatViewDescription
Swarm intelligence for traffic ...1.283MbIcon   [PDF] View/Open  

This item appears in the following collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as: Attribution-NonCommercial-NoDerivatives 4.0 Internacional