Dynamic High-speed Traffic Flow Statistics Algorithm Based on Artificial Intelligence Simulation Technology

The rapid development of urbanization brings a large number of people to the city, and the traffic demand generated by people’s travel has exceeded the traffic supply capacity of urban roads, resulting in the overload of traffic infrastructure. Urban traffic flow statistics is an important link of state road traffic control and management, is the foundation of the intelligent traffic analysis, as the city scale expands unceasingly, traffic present a variety of complex shape, how to doing a lot of congestion in complex scene surveillance video for accurate statistical traffic has become one of research hotspots in the field of intelligence traffic. This paper mainly carries on the research of dynamic high-speed traffic flow statistics algorithm based on artificial intelligence simulation technology. Firstly, the YOLO algorithm is optimized for vehicle detection, and a high-speed traffic flow statistics system based on YOLO algorithm is designed and implemented. The UA-DeTRAc data set is used to test the system performance, and the detection result shows that the system accuracy of this paper is up to 95%.