Stochastic vs deterministic traffic simulator. comparative study for its use within a traffic light cycles optimization architecture

Authors:
Javier Sánchez Medina;Manuel Galán Moreno;Enrique Rubio Royo
Affiliations:
Innovation Center for Information Society – C.I.C.E.I., University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain;Innovation Center for Information Society – C.I.C.E.I., University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain;Innovation Center for Information Society – C.I.C.E.I., University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
Venue:
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Year:
2005

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Abstract

Last 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.