Short-Term Traffic Flow Prediction Based on Combination of Predictive Models

In modern intelligent transportation systems,short-term traffic flow forecasting is one of the key technologies to achieve a real-time-traffic control and traffic guidance.In order to improve the precision of the short-term traffic flow forecasting,a short-term traffic flow prediction method is proposed based on the combination forecasting model.The future projections are dynamically adjusted according to the current traffic flow data in the first part.Meanwhile,through the analysis of spatial and temporal characteristics of historical traffic flow data,the historical curve similar to the current traffic flow characteristics is sought in another part to find the data that is matching to the predicted value.The information obtained by the both can be organically combinated in different ways to achieve the short-term traffic flow forecasting.Taking the traffic flow of Xiamen Lotus junction cross-section as an example,is the paper demonstrates that the average absolute relative deviations of the methods are all less than 10%,which is able to meet the requirements of the traffic guidance system(GIS).