A Freeway Traffic Incident Detection Algorithm Based on Neural Networks

Abstract

This paper proposes a novel freeway traffic incident detection algorithm. Two stages are involved. First, get the freeway traffic flow model based on BP neural networks and use the model to obtain the output prediction. The residual signals will be gotten from the comparison between the actual and prediction states. Second, a SOM neural networks is trained to classify characteristics contained in the residuals. Hence, based on the classification given by the SOM neural networks, traffic incidents can be detected. Both theory analysis and simulation research show that this algorithm is effective.