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arXiv · 2411.14567

Energy Efficient Automated Driving as a GNEP: Vehicle-in-the-loop Experiments

Viranjan Bhattacharyya·Tyler Ard·Rongyao Wang·Ardalan Vahidi·Yunyi Jia·Jihun Han
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Abstract

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.

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Viranjan Bhattacharyya, Tyler Ard, Rongyao Wang, Ardalan Vahidi, Yunyi Jia, Jihun Han. 2024-11-21. Energy Efficient Automated Driving as a GNEP: Vehicle-in-the-loop Experiments. https://arxiv.org/abs/2411.14567

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