Abstract: Aiming at the issue about short-term traffic flow forecasting,a prediction model combining with Kalman filtering and support vector machine was proposed．The model adopts appropriate forecast method intelligently in each prediction period by the standards of error sum of squares and vector cosine of the angle,utilizes the stability of SVM and the real-time nature of Kalman filter comprehensively,and takes respective advantages of the two models．Experiments show that the model’s error indicators are lower than single forecast model．In particular,the model in the peak hours,which average relative error is maintained at less than 8%,is a feasible and effective method of short-term traffic flow forecasting.

Key words: Traffic flow,Combining forecasting,Support vector machine,Kalman filter