Estimation of optimal green time simulation using fuzzy neural network

In the past, when there were few vehicles on the road, the TOD (time of day) traffic signal worked very well. The TOD signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, the paper proposes a concept of the optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. The fuzzy neural network will consistently improve average waiting time, vehicle speed, and fuel consumption.