部分的に遮蔽された市街交通環境における自動運転エージェントの安全性向上：表現ベースシールディング
Enhancing Safety for Autonomous Agents in Partly Concealed Urban Traffic Environments Through Representation-Based Shielding
見通しの悪い無信号交差点での自動運転の衝突防止に向け、エージェントが知覚できる情報に基づく新しい状態表現を強化学習に導入し、安全性とエネルギー効率を改善した。
著者: Pierre Haritz, David Wanke, Thomas Liebig
分類: cs.RO, cs.LG
原文アブストラクト
Navigating unsignalized intersections in urban environments poses a complex challenge for self-driving vehicles, where issues such as view obstructions, unpredictable pedestrian crossings, and diverse traffic participants demand a great focus on crash prevention. In this paper, we propose a novel state representation for Reinforcement Learning (RL) agents centered around the information perceivable by an autonomous agent, enabling the safe navigation of previously uncharted road maps. Our approach surpasses several baseline models by a sig nificant margin in terms of safety and energy consumption metrics. These improvements are achieved while maintaining a competitive average travel speed. Our findings pave the way for more robust and reliable autonomous navigation strategies, promising safer and more efficient urban traffic environments.