Analysis of progressive stability of mixed traffic flow of intelligent networked vehicles

Due to the traditional method in the analysis of traffic flow stability, there is no analysis of the influence factors, resulting in the analysis results are not reliable, and can not accurately analyze the traffic flow in different periods. Therefore, this paper proposes a new type of intelligent network connected vehicle hybrid traffic flow progressive stability analysis method. This method establishes a basic graph model of mixed traffic flow, and analyzes the relationship between traffic flow density, flow and speed through this model. Establish a car-following model to reflect the relationship between the traffic flow and the speed difference, vehicle speed, and headway distance of hybrid intelligent networked vehicles and manually driven vehicles. According to the analysis results, the vehicle collision index, vehicle collision time and vehicle speed dispersion are selected as indicators to analyze the factors affecting the stability of traffic flow, and complete the progressive stability analysis of the mixed traffic flow of intelligent networked vehicles. The results show that the analysis results of this method are highly reliable and can accurately analyze the traffic flow in different periods. © 2021, Aracne Editrice. All rights reserved.