Abstract: With the vigorous development of intelligent transportation systems(ITS), traffic control and traffic guidance have become a hot research issue. Real-time and accurate short-term forecasting of traffic flow is critical to traffic control and guidance, and the accuracy of forecasting directly influences the effect of traffic control and guidance. In order to improve forecast accuracy, this paper proposes a traffic flow forecasting method based on combination model, in which the historical trend model and the multiple regression model are weightedly combined to establish a forecasting model. Moreover, for the forecasting values of better accuracy, a larger weight will be given. By analyzing the forecasting results of Shanghai’s traffic flow in 2009, it is shown that the proposed method can improve the accuracy of forecast.