Prediction and identification of urban traffic flow based on features

Identifying and predicting the situation of traffic flow play an important role in traveler information broadcast and real-time traffic control. In this paper, to pick up the effective characteristic parameters of traffic, the features and the transition between different situations in traffic are studied and analyzed, A hybrid Elman neural network and Fuzzy techniques are good at working out the non-linear problem and identifying the state of system, so they can apply to predict and distinguish the traffic situation in short term. As a result, it proves that there are some advantages, e.g. simple configuration, good prediction and exact identification. So it is fit to online predict and identify the traffic flow in urban expressway.