With the development of connected automated vehicles (CAVs), traffic flow on the road is generally mixed with human-driven vehicles (HDVs) and CAVs，CAVs have the advantage of being able to alleviate traffic congestion and reduce traffic accidents to a certain extent relative to HDVs.In order to better develop CAVs, it is planned to set up dedicated lanes for autonomous vehicle on the highway. In this paper, two different car-following models are adopted for the dedicated lanes for autonomous and the highway traditional car lane in the simulation platform. Based on the constant traffic flow, the parameters of the traditional lane are simulated based on the car-following model. Under normal circumstances, the traffic capacity data continuously changes the penetration rate of the self-driving car in the dedicated lane following model, and obtains the traffic capacity status data corresponding to the dedicated lanes under different penetration rates. Comparing the data of the traditional lane with the data of the dedicated lane, the effect that the automatic driving lane can obtain compared with the traditional lane under different autonomous vehicle penetration rates is obtained. Taking the above method will eventually get the corresponding best self-driving car penetration rate to maximize the advantages of CAVs.

CICTP