Short-term Traffic Flow Prediction Based on Incremental Support Vector Regression

Abstract

In this paper, a new short-term traffic flow prediction model and method based on incremental support vector regression (ISVR) is proposed, according to the data collected sequentially by the probe vehicle or loop detectors, which can update the prediction function in real time via incremental learning way. As a result, it is fitter for the real engineering application. The ISVR model was tested by using the 1-880 database, and the result shows that this model is superior to the back-propagation neural network (BPNN) model.