自動運転のための常識的視覚理解：視覚と意味論を統合する汎用ニューロシンボリック・オンライン推論
Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics
視覚認識と意味論的推論をニューロシンボリックに統合し、ASPを用いて自動運転のオンライン視覚理解（説明可能性や常識補間を含む）を実現する枠組みを提案・実装した論文。
著者: Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
分類: cs.AI, cs.CV, cs.LG, cs.RO
原文アブストラクト
We demonstrate the need and potential of systematically integrated vision and semantics solutions for visual sensemaking in the backdrop of autonomous driving. A general neurosymbolic method for online visual sensemaking using answer set programming (ASP) is systematically formalised and fully implemented. The method integrates state of the art in visual computing, and is developed as a modular framework that is generally usable within hybrid architectures for realtime perception and control. We evaluate and demonstrate with community established benchmarks KITTIMOD, MOT-2017, and MOT-2020. As use-case, we focus on the significance of human-centred visual sensemaking -- e.g., involving semantic representation and explainability, question-answering, commonsense interpolation -- in safety-critical autonomous driving situations. The developed neurosymbolic framework is domain-independent, with the case of autonomous driving designed to serve as an exemplar for online visual sensemaking in diverse cognitive interaction settings in the backdrop of select human-centred AI technology design considerations. Keywords: Cognitive Vision, Deep Semantics, Declarative Spatial Reasoning, Knowledge Representation and Reasoning, Commonsense Reasoning, Visual Abduction, Answer Set Programming, Autonomous Driving, Human-Centred Computing and Design, Standardisation in Driving Technology, Spatial Cognition and AI.
