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Decentralised urban traffic control using genetic algorithm and cellular automata

This paper describes a traffic control simulation based on exchange of messages between local intersections which incorporate dynamically assembled cellular automata. A genetic algorithm is employed to determine parameters governing the messaging and cellular behaviour. This paper reports both on the convergence of the genetic algorithm towards fittest solutions; and on the performance of the genetic algorithm plus cellular automata combination, under various configurations.