Optimizing urban traffic flow using Genetic Algorithm with Petri net analysis as fitness function

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 o...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2014-01, Vol.124, p.162-167
Main Authors: Dezani, Henrique, Bassi, Regiane D.S., Marranghello, Norian, Gomes, Luís, Damiani, Furio, Nunes da Silva, Ivan
Format: Article
Language:English
Subjects:
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Computer science
control theory
systems
Exact sciences and technology
Fitness
Genetic Algorithm
Genetic algorithms
Ground, air and sea transportation, marine construction
Optimization
Petri net
Road transportation and traffic
Roads
Theoretical computing
Traffic engineering
Traffic flow
Urban traffic
Vehicles
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Summary: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.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2013.07.015