交通規則を優先度付きで満たす自動運転の最適制御
Rule-based Optimal Control for Autonomous Driving
交通法規や運転マナーを優先度付きルールとして定式化し、CLFとCBFを用いた最適制御で優先度の高いルールから順に満たす自動運転制御フレームワークを提案した。軌道の合否評価にも応用できる。
著者: Wei Xiao, Noushin Mehdipour, Anne Collin, Amitai Bin-Nun, Emilio Frazzoli, Radboud Duintjer Tebbens, Calin Belta
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
We develop optimal control strategies for Autonomous Vehicles (AVs) that are required to meet complex specifications imposed by traffic laws and cultural expectations of reasonable driving behavior. We formulate these specifications as rules, and specify their priorities by constructing a priority structure. We propose a recursive framework, in which the satisfaction of the rules in the priority structure are iteratively relaxed based on their priorities. Central to this framework is an optimal control problem, where convergence to desired states is achieved using Control Lyapunov Functions (CLFs), and safety is enforced through Control Barrier Functions (CBFs). We also show how the proposed framework can be used for after-the-fact, pass / fail evaluation of trajectories - a given trajectory is rejected if we can find a controller producing a trajectory that leads to less violation of the rule priority structure. We present case studies with multiple driving scenarios to demonstrate the effectiveness of the proposed framework.
