由于智能网联车的不断发展，未来将出现智能网联车和人工驾驶车共同存在的混合交通流，因此，研究道路上的混合交通有助于解决交通拥堵等问题，具有一定的现实意义。为探究这类混合交通流的流量、密度和速度之间的关系，文中综合考虑智能网联车辆退化和车辆时延，建立了自动驾驶环境下混合交通流的基本图模型。首先，确定交通流中的车辆类型和不同类型车辆的比例，并考虑联网智能车辆跟随人工车辆时发生的车辆功能退化；然后，确定3种车辆的延迟时间并改进每种车辆的跟驰模型；在此基础上，同时考虑车辆时延和车辆功能退化两种因素，推导出交通流平衡时的基本图模型，并对模型中的自由流速度参数进行敏感度分析。研究结果表明，智能网联车对混合交通流的最大流量和最佳密度有积极影响，车辆时延有消极影响，自由流速度则对混合交通流的最大流量有积极影响，对最佳密度有消极影响。SUMO仿真结果表明，在不同场景下仿真得到的流量?密度分布点符合理论曲线，验证了文中理论模型的准确性。

Due to the continuous development of connected and automated vehicles, there will be a mixed traffic flow in which intelligent networked vehicles and manual driving vehicles coexist in the future. Therefore, the study of mixed traffic on the road can effectively solve traffic congestion and other problems, so it has certain practical significance. In order to explore the relationship between the flow, density and speed of this type of mixed traffic flow, this paper established a fundamental diagram model of the mixed traffic flow in an autonomous driving environment based on the comprehensive consideration of the degradation of intelligent networked vehicles and the delay between vehicles. First, it determined the types of vehicles in the traffic flow and the proportion of different types of vehicle, and considered the vehicle functional degradation when connected intelligent vehicles follow artificial vehicles. Then, the delay time of each type of three vehicles was determined and the following model of each vehicle was improved. On this basis, considering both the vehicle delay and the vehicle function degradation, the fundamental diagram model of traffic flow balance was derived, and the sensitivity analysis of free flow speed parameter in the model was carried out. The research result shows that connected and automated vehicles have a positive impact on the maximum flow and optimal density of mixed traffic flows, while vehicle delays have a negative impact; the free flow speed has a positive impact on the maximum flow and a negative impact on the optimal density of mixed traffic flow. The SUMO simulation results show that the simulated flow-density distribution points in different scenarios conform to the theoretical curve, which verifies the accuracy of the theoretical model in the paper.