Short-term Traffic Flow Prediction for Urban Streets Based on Feedback Mechanism
Fine management of transportation has put forward higher requirements for grasping the law of traffic flow,and traffic flow prediction is an important guarantee for improving traffic control and management level.A traffic flow prediction method is proposed,which consists of two modules,namely feedback module and prediction module.Traffic flow data in Shanghai is used to verify the ef-fectiveness of the method.The results show that the average,absolute and relative errors of proposed method for all intervals are less than those of the single model based on feedback mechanism and the single or hybrid model without feedback mechanism.The proposed method can effectively improve the accuracy of short-term traffic flow prediction.
ITSurban streetshybrid prediction modelfeedback mechanismspatial and temporal correlations
万方数据
维普
