Algorithm Research on Freeway Incident Recognition and Risk Prediction

The construction of freeway has brought remarkable economic and social benefits. However, with the growth of traffic demands, freeway traffic incidents occur more and more frequently. The freeway traffic incidents will bring significant inconvenience to the road users. For the highway management administration, the appearance of the incident will disturb the normal operation order of the highway, it is necessary to take timely measures to reduce the impact of abnormal events. In this study, traffic flow status data such as freeway incident data, traffic flow, speed and occupancy were used to develop a Random Forest-Support Vector Machine (RF-SVM) method for incident recognition. The results show that the model is feasible to predict the risk of traffic incident.