自动驾驶车辆对人工驾驶车辆跟驰行为影响分析

针对自动驾驶车辆（automated vehicle, AV）与人工驾驶车辆（manual vehicle, MV）组成的混行跟驰环境，基于Waymo公开数据集研究混行环境中AV前车对MV后车跟驰行为的影响。首先，探究混行环境中期望安全裕度模型和智能驾驶人模型的建模能力和模型参数变化，研究表明，混行环境中MV跟驰行为的机制没有发生变化，但是MV驾驶人的减速敏感程度更低。其次，从跟驰安全性、稳定性和环境效应3个方面对混行跟驰行为进行进一步分析得到，混行环境中的MV跟驰行为的稳定性和环境效应得到了改善，但是安全性并没有发生变化。最后，通过对前车速度波动性进行讨论发现，AV前车主要是通过降低自身速度波动性，从而抑制MV后车的速度波动性，改善MV后车在稳定性及环境效应方面的表现。

Analysis of the impact of automated vehicle on the car-following behavior of manual vehicle

Aiming at the mixed car-following environment composed of automated vehicles (AV) and manual vehicles (MV), the impact of AV on car-following behavior of MV based on Waymo open dataset was studied. The modeling ability and model parameter changes of the desired safety margin model and the intelligent driver model in the mixed driving environment were explored, and the results showed that the mechanism of car-following behavior of MV in the mixed driving environment did not change, but the MV driver was less sensitive to deceleration. In addition, the MV car-following behavior of the mixed environment in terms of safety, stability and environmental performance was further analyzed, and the results showed that the stability and environmental performance were improved, but the safety did not change. Moreover, the speed volatilities of the leading vehicles were discussed, and the results showed that the leading vehicles of AV mainly suppressed the speed volatility of the rear vehicles of MV by reducing its own speed volatility, so as to improve the performance of the rear vehicles of MV in terms of stability and environmental performance.