dc.contributorFaculdade de Tecnologia de Rio Preto (FATEC)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2015-04-27T11:56:00Z
dc.date.available2015-04-27T11:56:00Z
dc.date.created2015-04-27T11:56:00Z
dc.date.issued2013
dc.identifierNeurocomputing, v. 124, p. 162-167, 2013.
dc.identifier0925-2312
dc.identifierhttp://hdl.handle.net/11449/122748
dc.identifier10.1016/j.neucom.2013.07.015
dc.identifier2098623262892719
dc.identifier2663276714773913
dc.identifier0000-0003-1086-3312
dc.description.abstractThis paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.
dc.languageeng
dc.relationNeurocomputing
dc.relation3.241
dc.relation1,073
dc.rightsAcesso aberto
dc.sourceCurrículo Lattes
dc.subjectAlgoritmos Genéticos
dc.subjectRedes de Petri
dc.subjectEmbedded Systems
dc.subjectSistemas de Tempo Real
dc.subjectSistemas Inteligentes
dc.subjectUrban traffic
dc.subjectGenetic Algorithm
dc.subjectPetri net
dc.subjectOptimization
dc.titleOptimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function
dc.typeArtículos de revistas


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