Study on the Impact of Complex Traffic Flow on Mixed Traffic

Abstract

With the rise of AI (Artificial Intelligence), many industries have become closely related to AI, while making autonomous driving a reality step by step. The coexistence of human-driven vehicles with autonomous vehicles is a necessary stage to achieve fully autonomous driving. In this paper, we study the expected impact on urban road traffic flow due to the implementation of different char-acteristics and penetration rates of smart driving vehicles. This paper establishes a model describing intelligent and human-driven vehicles and uses adaptive priority algorithms to investigate the different state evolution processes of human-machine driven hybrid traffic flows, laying the foundation for the study of the theory and methodology of hybrid traffic flows. The study found that under different weather conditions, with the different penetration rate distribution of autonomous vehicles, the traffic and environment of mixed traffic flow were positively affected to a certain extent, and the overall running time was optimized by 7.68% when the penetration rate of intelligent vehicles was increased to about 50%. Under the condition of snow and ice, when the penetration rate of intelligent driving vehicle increases to 30%, the optimization rate of running time reaches the highest value of 5.01%. This shows that the increasing number of smart driving vehicles will help reduce traffic congestion.