歩行者と車両の安全なインタラクションのためのオンラインモニタリング
Online monitoring for safe pedestrian-vehicle interactions
歩行者の意図推定を自律走行スタックに統合し、到達可能性に基づくオンラインモニタリングで人とロボットのインタラクションの安全性を形式的に保証する手法を提案し、実車実験で有効性を示した。
著者: Peter Du, Zhe Huang, Tianqi Liu, Ke Xu, Qichao Gao, Hussein Sibai, Katherine Driggs-Campbell, Sayan Mitra
分類: cs.RO, cs.MA, eess.SP
原文アブストラクト
As autonomous systems begin to operate amongst humans, methods for safe interaction must be investigated. We consider an example of a small autonomous vehicle in a pedestrian zone that must safely maneuver around people in a free-form fashion. We investigate two key questions: How can we effectively integrate pedestrian intent estimation into our autonomous stack. Can we develop an online monitoring framework to give formal guarantees on the safety of such human-robot interactions. We present a pedestrian intent estimation framework that can accurately predict future pedestrian trajectories given multiple possible goal locations. We integrate this into a reachability-based online monitoring scheme that formally assesses the safety of these interactions with nearly real-time performance (approximately 0.3 seconds). These techniques are integrated on a test vehicle with a complete in-house autonomous stack, demonstrating effective and safe interaction in real-world experiments.
