2024/11/21 by Viranjan Bhattacharyya, Tyler Ard, Bhattacharyya, Viranjan +9
Engineering · #Electric Vehicles and Infrastructure #Electric and Hybrid Vehicle Technologies #FOS: Electrical engineering #Systems and Control (eess.SY) #Vehicle emissions and performance #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2411.14567
openalex publication_date 2024/11/21 · openalex created_date 2024/12/04 · openalex updated_date 2026/07/28
In this paper, a multi-agent motion planning problem is studied aiming to minimize energy consumption of connected automated vehicles (CAVs) in lane change scenarios. We model this interactive motion planning as a generalized Nash equilibrium problem and formalize how vehicle-to-vehicle intention sharing enables solution of the game between multiple CAVs as an optimal control problem for each agent, to arrive at a generalized Nash equilibrium. The method is implemented via model predictive control (MPC) and compared with an advanced baseline MPC which utilizes unilateral predictions of other agents' future states. A ROS-based in-the-loop testbed is developed: the method is first evaluated in software-in-the-loop and then vehicle-in-the-loop experiments are conducted. Experimental results demonstrate energy and travel time benefits of the presented method in interactive lane change maneuvers.