Using genetic algorithm for traffic light control system with a pedestrian crossing

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Turky A.M.
Ahmad M.S.
Yusoff M.Z.M.
Hammad B.T.
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In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better. � 2009 Springer Berlin Heidelberg.
Cellular Automata , Genetic Algorithm , Traffic Control Systems , Cellular automata , Control system analysis , Control systems , Controllers , Crossings (pipe and cable) , Dynamical systems , Footbridges , Fuzzy sets , Genetic algorithms , Light transmission , Pattern recognition systems , Pedestrian safety , Rough set theory , Traffic control , Translation (languages) , Vehicles , Dynamic Systems , Green light , Number of vehicles , Pedestrian crossing , Performance comparison , Red light , Time control , Time controller , Traffic light , Traffic light control systems , Two-lane traffic , Genetic engineering