マルチレベル融合による運転行動の説明生成
Driving Behavior Explanation with Multi-level Fusion
軌道予測モデルの判断根拠を高レベルな運転説明として生成する深層学習手法BEEFを提案し、HDDとBDD-Xデータセットで有効性を示した論文。
著者: Hédi Ben-Younes, Éloi Zablocki, Patrick Pérez, Matthieu Cord
分類: cs.LG, cs.AI, cs.CV, cs.RO
原文アブストラクト
In this era of active development of autonomous vehicles, it becomes crucial to provide driving systems with the capacity to explain their decisions. In this work, we focus on generating high-level driving explanations as the vehicle drives. We present BEEF, for BEhavior Explanation with Fusion, a deep architecture which explains the behavior of a trajectory prediction model. Supervised by annotations of human driving decisions justifications, BEEF learns to fuse features from multiple levels. Leveraging recent advances in the multi-modal fusion literature, BEEF is carefully designed to model the correlations between high-level decisions features and mid-level perceptual features. The flexibility and efficiency of our approach are validated with extensive experiments on the HDD and BDD-X datasets.
