能動的インタラクションを考慮した時空間リシーディングホライズン制御：密集交通における自動運転に向けて
Spatiotemporal Receding Horizon Control with Proactive Interaction Towards Autonomous Driving in Dense Traffic
密集交通での自動運転のため、他車の予測誤差を能動的インタラクションで緩和する時空間安全バリアを組み込んだ計算効率の良い時空間リシーディングホライズン制御を提案し、安全性と効率を両立させた。
著者: Lei Zheng, Rui Yang, Zengqi Peng, Michael Yu Wang, Jun Ma
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In dense traffic scenarios, ensuring safety while keeping high task performance for autonomous driving is a critical challenge. To address this problem, this paper proposes a computationally-efficient spatiotemporal receding horizon control (ST-RHC) scheme to generate a safe, dynamically feasible, energy-efficient trajectory in control space, where different driving tasks in dense traffic can be achieved with high accuracy and safety in real time. In particular, an embodied spatiotemporal safety barrier module considering proactive interactions is devised to mitigate the effects of inaccuracies resulting from the trajectory prediction of other vehicles. Subsequently, the motion planning and control problem is formulated as a constrained nonlinear optimization problem, which favorably facilitates the effective use of off-the-shelf optimization solvers in conjunction with multiple shooting. The effectiveness of the proposed ST-RHC scheme is demonstrated through comprehensive comparisons with state-of-the-art algorithms on synthetic and real-world traffic datasets under dense traffic, and the attendant outcome of superior performance in terms of accuracy, efficiency and safety is achieved.
