An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice

Understand

The autonomous driving (AD) industry is exploring the use of knowledge graphs (KGs) to manage the vast amount of heterogeneous data generated from vehicular sensors.

• The various types of equipped sensors include video, LIDAR and RADAR.
• Scene understanding is an important topic in AD which requires consideration of various aspects of a scene, such as detected objects, events, time and location.
• Recent work on knowledge graph embeddings (KGEs) - an approach that facilitates neuro-symbolic fusion - has shown to improve the predictive performance of machine learning models.