車種別ウェイポイント生成
Vehicle Type Specific Waypoint Generation
運転行動の確率基盤モデルを強化学習の副産物で条件付けし、車種ごとに物理的に妥当なウェイポイント列を生成する手法を提案した。
著者: Yunpeng Liu, Jonathan Wilder Lavington, Adam Scibior, Frank Wood
分類: cs.AI, cs.HC, cs.RO, cs.SY, eess.SY
原文アブストラクト
We develop a generic mechanism for generating vehicle-type specific sequences of waypoints from a probabilistic foundation model of driving behavior. Many foundation behavior models are trained on data that does not include vehicle information, which limits their utility in downstream applications such as planning. Our novel methodology conditionally specializes such a behavior predictive model to a vehicle-type by utilizing byproducts of the reinforcement learning algorithms used to produce vehicle specific controllers. We show how to compose a vehicle specific value function estimate with a generic probabilistic behavior model to generate vehicle-type specific waypoint sequences that are more likely to be physically plausible then their vehicle-agnostic counterparts.
