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dc.contributor.author
García Nieto, José M.
dc.contributor.author
Alba, Enrique
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dc.contributor.author
Olivera, Ana Carolina
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dc.date.available
2023-04-04T13:30:45Z
dc.date.issued
2012-03
dc.identifier.citation
García Nieto, José M.; Alba, Enrique; Olivera, Ana Carolina; Swarm intelligence for traffic light scheduling: Application to real urban areas; Pergamon-Elsevier Science Ltd; Engineering Applications Of Artificial Intelligence; 25; 2; 3-2012; 274-283
dc.identifier.issn
0952-1976
dc.identifier.uri
http://hdl.handle.net/11336/192649
dc.description.abstract
Congestion, 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.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
CYCLE PROGRAM OPTIMIZATION
dc.subject
PARTICLE SWARM OPTIMIZATION
dc.subject
REALISTIC TRAFFIC INSTANCES
dc.subject
SUMO MICROSCOPIC SIMULATOR OF URBAN MOBILITY
dc.subject
TRAFFIC LIGHT SCHEDULING
dc.subject.classification
Ciencias de la Computación
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dc.subject.classification
Ciencias de la Computación e Información
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Swarm intelligence for traffic light scheduling: Application to real urban areas
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-03-23T12:38:52Z
dc.journal.volume
25
dc.journal.number
2
dc.journal.pagination
274-283
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: García Nieto, José M.. Universidad de Málaga; España
dc.description.fil
Fil: Alba, Enrique. Universidad de Málaga; España
dc.description.fil
Fil: Olivera, Ana Carolina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina
dc.journal.title
Engineering Applications Of Artificial Intelligence
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence/
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.engappai.2011.04.011
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