Distributed graph-based convoy control for networked intelligent vehicles

Abstract

Abstract-This paper presents an approach for formation control of multi-lane vehicular convoys in highways. We extend a Laplacian graph-based, distributed control law such that networked intelligent vehicles can join or leave the formation dynamically without jeopardizing the ensemble's stability. Additionally, we integrate two essential control behaviors for lane-keeping and obstacle avoidance into the controller. To increase the performance of the convoy controller in terms of formation maintenance and fuel economy, the parameters of the controller are optimized in realistic scenarios using Particle Swarm Optimization (PSO), a powerful metaheuristic optimization method well-suited for large parameter spaces. The performances of the optimized controllers are evaluated in high-fidelity multi-vehicle simulations outlining the efficiency and robustness of the proposed strategy.

A distributed MPC framework for road-following formation control of car-like vehicles

“…Moreover, the formation is determined in advance and cannot be reconfigured. Other approaches include Laplacianbased control [14], graph searching methods [4], etc.. This paper proposes and validates a novel on-road formation control framework established on the theoretical results of distributed MPC, upon which we propose multiple adaptations to handle the challenges raised by the on-road driving setting.…”

Formation Control for a Fleet of Autonomous Ground Vehicles: A Survey

“…A distributed and dynamic graph-based formation control approach was presented for vehicles to join, leave, or change lanes without affecting the stability of the convoy. Here, PSO was implemented to optimize the parameters of the control law (lane keeping and obstacle avoidance) and to reduce the overall formation control errors [108]. In this paper, a vision sensor was used for the lane keeping and LIDAR was used for the obstacle avoidance.…”

Cooperative Automated Maneuvering at the 2016 Grand Cooperative Driving Challenge

“…It should be noted that in the context of the GCDC, it was not feasible to apply an architecture that supports formationlike controllers [30], [31] or even a more generic approach based on consensus seeking [32], since this would require all vehicles to implement exactly the same type of vehicle motion controller, whereas in the GCDC, the control approach could be freely chosen by each participant. Nevertheless, the presented architecture does assume all vehicles to be cooperative.…”