Abstract

AbstractLast year we presented at the CEC2004 conference a novel architecture for traffic light cycles optimization. The heart of this architecture is a Traffic Simulator used as the evaluation tool (fitness function) within the Genetic Algorithm. Initially we allowed the simulator to have a random behavior. Although the results from this sort of simulation were consistent, it was necessary to run a huge amount of simulations before we could get a significant value for the fitness of each individual of the population . So we assumed some simplifications to be able to use a deterministic simulator instead of the stochastic one. In this paper we will confirm that it was the right decision; we will show that there is a strong linear correlation between the results of both simulators. Hence we show that the fitness ranking obtained by the deterministic simulator is as good as the obtained with the stochastic one.KeywordsGenetic AlgorithmCellular AutomatonStochastic SimulatorIntelligent Transportation SystemNetwork ScaleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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