Performance analysis of support vector machine for traffic flow prediction

With the successive increase in usage of vehicles, severe traffic congestion is on the rise. This in turn leads to increase in environmental pollution and accidents which ultimately affects the safety, time consumed and money spent of the transport users. The solution to this critical problem is traffic flow prediction depending on which traffic control measures and traffic management can be done. Short term traffic flow prediction has become one of the hot topics of research in intelligent transportation system (ITS). It predicts the traffic flow count in the next time interval that usually varies in the range of five minutes to half an hour. This work presents the application of Support vector machine (SVM) for predicting the traffic flow in a short span. Highway data of midblock segment collected from Chennai, India is used for the analysis. Improved performance measure shows satisfactory results upon application of SVM.