社会価値志向を用いた無信号交差点における人間らしい意思決定
Human-like Decision-making at Unsignalized Intersection using Social Value Orientation
無信号交差点での自動運転車と人間運転車の協調のため、社会価値志向（SVO）を強化学習に組み込み、人間らしい意思決定を実現する手法を提案し、自然な走行軌跡を再現できることを示した。
著者: Yan Tong, Licheng Wen, Pinlong Cai, Daocheng Fu, Song Mao, Yikang Li
分類: cs.RO, cs.HC
原文アブストラクト
With the commercial application of automated vehicles (AVs), the sharing of roads between AVs and human-driven vehicles (HVs) becomes a common occurrence in the future. While research has focused on improving the safety and reliability of autonomous driving, it's also crucial to consider collaboration between AVs and HVs. Human-like interaction is a required capability for AVs, especially at common unsignalized intersections, as human drivers of HVs expect to maintain their driving habits for inter-vehicle interactions. This paper uses the social value orientation (SVO) in the decision-making of vehicles to describe the social interaction among multiple vehicles. Specifically, we define the quantitative calculation of the conflict-involved SVO at unsignalized intersections to enhance decision-making based on the reinforcement learning method. We use naturalistic driving scenarios with highly interactive motions for performance evaluation of the proposed method. Experimental results show that SVO is more effective in characterizing inter-vehicle interactions than conventional motion state parameters like velocity, and the proposed method can accurately reproduce naturalistic driving trajectories compared to behavior cloning.
