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Development of a vehicle and pedestrian simulation environment with M.I.S.O. fuzzy logic controlled intelligent traffic light system

Pre-timed traffic light system, which is currently used, is no longer sufficient at handling vehicular congestion. Various intelligent traffic control signals are present to replace the currently used system. These systems only focused on the parameters of the vehicles. Most intersections contain traffic signals for pedestrians and vehicles, pedestrian lanes must also be considered in the decision making of the intelligent traffic signals. Cameras were used to estimate the number of pedestrian and vehicle at an intersection. A fuzzy logic controller is used to receive and process the information for the decision making of the traffic light system. NetLogo — a multi-agent programmable modeling environment was used to create a traffic model and a simulation environment to simulate and test the developed fuzzy logic system. Results shows that the fuzzy logic system poses a lower rate of car congestion compared to the pre timed system, and this is tested for 3 sets of data including a different time. A lesser number of vehicles congestion will result to less waiting time at a traffic intersection. The developed fuzzy logic based adaptive traffic light system has proven the effectiveness of reducing the congestion and waiting time of vehicles.