Knowledge Graphs of Driving Scenes to Empower the Emerging Capabilities of Neurosymbolic AI

Ruwan Wickramarachchi, Cory A. Henson, Amit P. Sheth

Abstract: In the era of generative artificial intelligence (AI), neurosymbolic AI is emerging as a powerful approach for tasks spanning from perception to cognition. The use of neurosymbolic AI has been shown to achieve enhanced capabilities, including improved grounding, alignment, explainability, and reliability. However, due to its nascent stage, there is a lack of widely available real-world benchmark datasets that are tailored to neurosymbolic AI tasks. To address this gap and support the evaluation of current and future methods, we introduce DSceneKG (Driving Scenes Knowledge Graph), a suite of KGs of driving scenes that is built from real-world, high-quality scenes from multiple open autonomous driving datasets. In this article, we detail the construction process of DSceneKG and highlight its application in seven different tasks.