Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function


Autoria(s): Dezani, Henrique; Bassi, Regiane Denise Solgon; Marranghello, Norian; Gomes, Luis Filipe dos Santos; Damiani, Furio; Silva, Ivan Nunes da
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/04/2015

27/04/2015

2013

Resumo

This 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.

Formato

162-167

Identificador

http://www.sciencedirect.com/science/article/pii/S0925231213007571

Neurocomputing, v. 124, p. 162-167, 2013.

0925-2312

http://hdl.handle.net/11449/122748

http://dx.doi.org/10.1016/j.neucom.2013.07.015

2098623262892719

2663276714773913

Idioma(s)

eng

Relação

Neurocomputing

Direitos

openAccess

Palavras-Chave #Algoritmos Genéticos #Redes de Petri #Embedded Systems #Sistemas de Tempo Real #Sistemas Inteligentes #Urban traffic #Genetic Algorithm #Petri net #Optimization
Tipo

info:eu-repo/semantics/article