Analysis and Control of Intelligent Traffic Signal System Based on Adaptive Fuzzy Neural Network

The paper proposes an intelligent traffic signal control system based on AFNN (Adaptive Fuzzy Neural Network) algorithm, which can adjust the signal cycle and green split to improve traffic efficiency. First, based on V2X (Vehicle to X) intelligent networking technology, the numbers of waiting vehicles at traffic light intersections are real-timely detected. Then, an AFNN algorithm is used to get the knowledge of experience and online self-adjustment is followed according to traffic state to optimize light signal control scheme. Finally, the validity and rationality of the system are verified by the system simulation model. The results show that with the help of the adaptive control system, the average delay time was reduced by 8.45%, and the average fuel economy increased by 24.04%.