Adaptive Dynamic Multiple Traffic Light Control System using Genetic Algorithm

Belal Ali Alshami, Ossama M.Ismail, Khaled Mahar


In smart cities the traffic light control system is an old problem and new at the same time, and also it is a hard problem. So there are many researchers who addressed this problem in certain cases and due to the rapid development in technology, increases in vehicles numbers and speed and other causes of congestion at junctions which motivates the computer science researchers to develop dynamic system in order to manage different models of traffic lights to optimize and to coordinate the Traffic Signal Timing (TST). In this study, a dynamic program is proposed to simulate many of traffic lights models, which satisfy users requirement by defining parameters according to their need such as number of intersections N, number of phases (group light) P at each intersection, number of roads R connected to the intersections, and number of lanes movement L at each road. A Genetic Algorithm Traffic Signal Timing Management system (GATSTMS) is used to investigate the optimal solutions for cycle times, offset times and green times according to the sequence orders of a set of traffic lights. The fitness function is selected to minimizing the waiting time “delay” on the model. The proposed GATSTMS has the ability to handle and manage different models of traffic lights. We applied the GATSTMS on two models of traffic lights; the results showed that the GATSTMS produces good optimal solutions.

Keywords: Genetic algorithm, traffic light control system.

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