高レベル運転指示に対する自動運転のロバスト性評価
Evaluating Robustness over High Level Driving Instruction for Autonomous Driving
都市環境の自動運転エージェントが誤った高レベル指示を受けた際の安全性を評価するベンチマーク手法を提案した論文。
著者: Florence Carton, David Filliat, Jaonary Rabarisoa, Quoc Cuong Pham
分類: cs.LG, cs.AI, cs.CV, cs.RO
原文アブストラクト
In recent years, we have witnessed increasingly high performance in the field of autonomous end-to-end driving. In particular, more and more research is being done on driving in urban environments, where the car has to follow high level commands to navigate. However, few evaluations are made on the ability of these agents to react in an unexpected situation. Specifically, no evaluations are conducted on the robustness of driving agents in the event of a bad high-level command. We propose here an evaluation method, namely a benchmark that allows to assess the robustness of an agent, and to appreciate its understanding of the environment through its ability to keep a safe behavior, regardless of the instruction.
