Study of Traffic Flow Prediction Model at Intersection Based on R-FNN

Urban transport problems have become severe social problems with the motorization and urbanization. In order to solve these problems, and achieve better effect of real-time traffic control, aiming at the signalized intersections of urban road network, some researches are made on the prediction of traffic flow in this paper. On the basis of it, a prediction model is constructed by using a superiority rough-fuzzy neural network (R-FNN), and a practical case is also done. Practical case research shows that the predicted result of this method is famous, and this method has biggish applied potentials in the region of traffic control.