Cooperative Formation of Autonomous Vehicles in Mixed Traffic Flow: Beyond Platooning
Keqiang Li, Jiawei Wang, Yang Zheng
Abstract
Cooperative formation and control of autonomous vehicles (AVs) promise increased efficiency and safety on public roads. In single-lane mixed traffic consisting of AVs and human-driven vehicles (HDVs), the prevailing platooning of multiple AVs is not the only choice for cooperative formation. In this paper, we investigate how different formations of AVs impact traffic performance from a set-function optimization perspective. We first reveal a stability invariance property and a diminishing improvement property of noncooperative formation when AVs adopt an independently designed Adaptive Cruise Control (ACC) strategy. Then, we focus on the case of cooperative formation where AVs utilize a centralized optimal controller. We further investigate the corresponding optimal formation of multiple AVs using set-function optimization. Two predominant optimal formations, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , uniform distribution and platoon formation, emerge from extensive numerical experiments. Interestingly, platooning might have the least potential to improve traffic performance when HDVs have poor string stability behavior. These results suggest more opportunities for cooperative formation of AVs, beyond platooning, in practical mixed traffic flow.