交渉を考慮した到達可能性に基づく自動運転の安全性検証
Negotiation-Aware Reachability-Based Safety Verification for AutonomousDriving in Interactive Scenarios
学習ベースの予測とゲーム理論的人間行動モデルを組み合わせ、後方到達可能性解析の保守性をオンラインで調整する自動運転の安全検証手法を提案し、実走行データで有効性を示した。
著者: Ran Tian, Anjian Li, Masayoshi Tomizuka, Liting Sun
分類: cs.RO
原文アブストラクト
Safety assurance is a critical yet challenging aspect when developing self-driving technologies. Hamilton-Jacobi backward-reachability analysis is a formal verification tool for verifying the safety of dynamic systems in the presence of disturbances. However, the standard approach is too conservative to be applied to self-driving applications due to its worst-case assumption on humans' behaviors (i.e., guard against worst-case outcomes). In this work, we integrate a learning-based prediction algorithm and a game-theoretic human behavioral model to online update the conservativeness of backward-reachability analysis. We evaluate our approach using real driving data. The results show that, with reasonable assumptions on human behaviors, our approach can effectively reduce the conservativeness of the standard approach without sacrificing its safety verification ability.
