モデル予測による軌道最適化と追従制御を統合した自動運転車両の制御手法
Model predictive trajectory optimization and tracking for on-road autonomous vehicles
自動運転車の軌道計画をモデル予測的に最適化し、フィードバック・フィードフォワード制御で高精度に追従させる制御スキームを提案し、回避操舵のシミュレーションで性能を検証した。
著者: Peng Liu, Brian Paden, Umit Ozguner
分類: cs.RO, math.OC
原文アブストラクト
Motion planning for autonomous vehicles requires spatio-temporal motion plans (i.e. state trajectories) to account for dynamic obstacles. This requires a trajectory tracking control process which faithfully tracks planned trajectories. In this paper, a control scheme is presented which first optimizes a planned trajectory and then tracks the optimized trajectory using a feedback-feedforward controller. The feedforward element is calculated in a model predictive manner with a cost function focusing on driving performance. Stability of the error dynamic is then guaranteed by the design of the feedback-feedforward controller. The tracking performance of the control system is tested in a realistic simulated scenario where the control system must track an evasive lateral maneuver. The proposed controller performs well in simulation and can be easily adapted to different dynamic vehicle models. The uniqueness of the solution to the control synthesis eliminates any nondeterminism that could arise with switching between numerical solvers for the underlying mathematical program.
