Distributed multilane merging for connected autonomous vehicle platooning

In the context of coordination of connected autonomous vehicles (CAVs), the platooning operation is a promising application. The formulation of a single stream of CAVs is conducive to traffic efficiency and merging operations extend the benefits for multilane road users. However, the problem of simultaneous merging and platooning lacks comprehensive investigation. A solution is formulated in this paper through a new scheme that considers inter-vehicle safety distance constraints and distributed deployment utilizing local inter-vehicle information exchanges. A distributed consensus-based controller synthesized with a collision avoidance design is developed to direct the CAVs to maintain the velocity and spacing required to avoid inter-vehicle collisions. Furthermore, a framework fusing an agent motion model with vehicle controllers based on a dynamics model that facilitates both longitudinal and lateral controls is proposed, contributing to a cross-model planning-tracking controller. Theoretical proof of asymptotic stability of the proposed controller and its collision avoidance capability are also elaborated. The merging and platooning function was tested in a hardware-in-the-loop (HiL) experiment, demonstrating the precise tracking performance and comparable merging responses to a typical multiagent system. In comparison with trajectory-based merging algorithms, the proposed framework is able to achieve finer stepwise tracking results without centralized coordination or predefined trajectories.