Cooperative Formation of Autonomous Vehicles in Mixed Traffic Flow: Beyond Platooning

TL;DR

This paper explores how different cooperative formations of autonomous vehicles, beyond traditional platooning, affect traffic efficiency and safety in mixed traffic flow through set-function optimization, revealing new formation strategies.

Contribution

It introduces a set-function optimization framework to analyze various AV formations, identifying optimal configurations like uniform distribution and platooning, and highlights the limitations of platooning in certain traffic conditions.

Findings

Platooning may offer limited improvements with poor HDV stability.

Uniform distribution can outperform platooning in mixed traffic.

Cooperative formation strategies can enhance traffic flow beyond traditional platooning.

Abstract

Cooperative formation and control of autonomous vehicles (AVs) promise increased efficiency and safety on public roads. In mixed traffic flow 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 typical Adaptive Cruise Control (ACC) strategies. Then, we focus on the case of cooperative formation where the AV controllers are cooperatively designed %redesign the control strategies of AVs in different formations and investigate the optimal formation of multiple AVs using set-function optimization. Two predominant optimal formations, i.e., 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.