Traffic Signal control optimization based on fuzzy neural network

With the development of road transport, traffic problems seriously interfere with the cities. Traffic Signal control optimization is the main way to solve this problem. This paper presents a control method which based on fuzzy neural network. Separately, using the number of vehicles on the queue for the current and next phase as input, as well as using green delay for the current phase as output. Simulation results show that this method can effectively lower the average vehicle delay than the traditional signal timing method (Weber Staffa), thereby increasing the traffic capacity of the intersection. Given the traffic problems in harsh environment, a new function is added in the signal timing calculation, which reduces the average delay time effectively and optimizes the system better.