混合自律交通における車線合流の協調計画
Collaborative Planning for Mixed-Autonomy Lane Merging
人間運転車と自動運転車が共存する合流場面で、利己性パラメータで相手の報酬を考慮する計画手法を提案し、ユーザー研究でバランスの取れた設定が合流時間を短縮することを示した。
著者: Shray Bansal, Akansel Cosgun, Alireza Nakhaei, Kikuo Fujimura
分類: cs.AI, cs.MA, cs.RO
原文アブストラクト
Driving is a social activity: drivers often indicate their intent to change lanes via motion cues. We consider mixed-autonomy traffic where a Human-driven Vehicle (HV) and an Autonomous Vehicle (AV) drive together. We propose a planning framework where the degree to which the AV considers the other agent's reward is controlled by a selfishness factor. We test our approach on a simulated two-lane highway where the AV and HV merge into each other's lanes. In a user study with 21 subjects and 6 different selfishness factors, we found that our planning approach was sound and that both agents had less merging times when a factor that balances the rewards for the two agents was chosen. Our results on double lane merging suggest it to be a non-zero-sum game and encourage further investigation on collaborative decision making algorithms for mixed-autonomy traffic.
