Real-Time Optimal Control of Traffic Flow Based on Fuzzy Wavelet Neural Networks

The forecast of real-time traffic flow is one of important contents of intelligent transportation system research. Based on the related knowledge of wavelet analysis and fuzzy neural networks, this paper proposes the fuzzy wavelet neural networks control method. It takes wavelet function as fuzzy membership function, uses neural networks to realize fuzzy reasoning, and finishes the estimate of next cyclical traffic flow. Simultaneously the genetic algorithm is used to optimize the overall network. After the field data test, this method is high precise, stable and compatible.