Towards Semantic Modeling for Assisted Driving: BFO-Compliant Ontology to Represent Ride Quality Knowledge

Abstract

A BFO-Compliant Ontology to Represent Ride Quality Knowledge is a step toward semantic modeling for assisted driving. Semantic reasoning helps to create knowledge from sensor data that is published in RDF using domain ontology. The fundamental requirements for the collection, publishing, and reasoning of knowledge to assist in such a scenario are presented here. This paper proposes ontology to represent the ride quality of a vehicle through semantic knowledge. To support interoperability among multiple domains, we propose an ontology that follows the standard basic formal ontology. The domains addressed are road infrastructure and assisted driving. Taking the example of mapping road quality by estimating degraded roads, bumps, potholes, and hazardous turns, an assisted driving application can guide a driver to slow down for a bump ahead or a sharp turns ahead enabling it to slow down based on geo-mapping the quality through sensors. The same knowledge can be exploited for automated vehicles and other domains related to vehicles, manufacturing, and road infrastructure. The ontology design is intended to support semantic reasoning at the edge.