Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44294
Title: Global speed vs. mean travel time. Polynomial dependence analysis in traffic signals optimization using genetic algorithms and parallel computing
Authors: Sánchez-Medina, Javier J. 
Galán-Moreno, M. J.
Rubio-Royo, Enrique 
UNESCO Clasification: 120304 Inteligencia artificial
332907 Transporte
Keywords: Beowulf cluster
Cellular automata microsimulation
Genetic algorithms
Parallel computing
Traffic flow optimization
Traffic signals
Issue Date: 2009
Conference: 2009 International Conference on Artificial Intelligence, ICAI 2009 
Abstract: In our group we have developed a traffic lights programming optimization model based on the combination of Genetic Algorithms and Microsimulation running over a Beowulf Cluster parallel computer. So far, in this architecture we have used a single variable for the fitness function. In this research our aim is to explore any polynomial dependence - up to a 12 th degree - between two candidate variables as potential participants in the fitness function: Global Speed and the Mean Travel Time. All tests have been fulfilled using data from a real world scenario located in Saragossa, Spain. We have used the supplied traffic lights provided, and also traffic statistics from the zone.
URI: http://hdl.handle.net/10553/44294
ISBN: 978-1-60132-109-1
Source: Proceedings of the 2009 International Conference on Artificial Intelligence, ICAI 2009, v. 2, p. 980-986
Appears in Collections:Actas de congresos
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