Research on Urban Short-term Traffic Flow Forecasting Model

Abstract

Short-term traffic flow forecasting is one of the key technologies of ITS, and it is also the basis of traffic control and road navigation. According to the characteristics of short-term traffic flow, combining with the actual traffic flow data of an intersection in Hefei City, a prediction model based on BP neural network is constructed. The experimental results show that the model reflects the change rule and trend of short-term traffic flow, and the prediction accuracy is high.