Impact of vehicle arrangement in mixed autonomy traffic on emissions
利用Waymo开放数据集，研究了混合自主交通中不同车辆排列（人类驾驶车在前、自动驾驶车在前等）对自动驾驶车驾驶行为和排放的影响，发现自动驾驶车领队时环境效益最大，但跟随时因安全驾驶导致排放更高。
The environmental impact of the driving behaviour of autonomous vehicles (AVs) is not yet well-understood due to the scarcity of empirical mixed autonomy trajectory data. This study utilizes the Waymo Open Dataset to assess the environmental impact of mixed autonomy traffic considering different vehicle arrangements in a platoon: Human-driven Vehicle (HV) following AV, AV following HV, and HV following HV. Findings suggest that vehicle arrangements in a platoon have a significant impact on the AVs’ driving behavior and, consequently, on traffic emissions. The largest environmental benefits were found when an AV is in the lead position. However, when an AV is following an HV, the AVs were observed to drive more conservatively for safety purposes, with a larger time gap and deceleration, resulting in higher emissions compared to when an HV is following another HV. The results provide insights into the complexity of the environmental assessment of AVs in mixed autonomy traffic.