Online Support Vector Regression Model for Short-term TrafficForecasting

摘要

In this paper, a new short-term traffic flow prediction model and method based on online support vector regression (OSVR) is proposed, according to the data collected sequentially by the probe vehicle or the loop detectors, which can update the forecasting function in real time via online learning way. As a result, it is fitter for a real engineering application. The OSVR model was tested by using I-880 database, the result shows that this model is superior to the back-propagation neural network (BPNN) model.