Impact of vehicle arrangement in mixed autonomy traffic on emissions
Abdulrahman Alhariqi, Ziyuan Gu, Meead Saberi
Abstract
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.