Ontology-based digital map integration

Autonomous Driving (AD) systems use digital maps as a virtual sensor to perceive the environment around the car. As the field of digital maps continues to evolve, existing solutions face new challenges such as integration ability for different map formats, and providing a generic interface to access the road environmental knowledge. In this paper, we present a two-level ontology architecture, where a high-level map ontology provides a generic and unified road environment model over different low-level map ontologies for specific map formats. We propose a practical methodology to guide the two-level ontologies' development process. The evaluation results show that the two-level approach can integrate different map formats, reduce the data size and provide a unified high-level map view.