Traffic Detection Algorithm Based on Outlier Mining

The first problem of traffic incident management is the detection and confirmation of traffic accidents. The detection method based on coil and video data is limited to practical application due to its high cost and insignificant detection effect. This paper presents a traffic incident detection algorithm based on outlier mining. The algorithm extracts characteristics of traffic event and builds a set of eigenvectors by using the new real-time traffic information released by NavInfo. The algorithm is simple, efficient and easy to deploy. Experimental results show that compared with traffic incident detection based on pattern recognition, the proposed algorithm has higher accuracy and can effectively distinguish between conventional congestion and traffic incidents.