Knowledge-Based Approach for the Perception Enhancement of a Vehicle

Abstract

An autonomous vehicle relies on sensors in order to perceive its surroundings. However, there are multiple causes that would hinder a sensor’s proper functioning, such as bad weather or lighting conditions. Studies have shown that rainfall and fog lead to a reduced visibility, which is one of the main causes of accidents. This work proposes the use of a drone in order to enhance the vehicle’s perception, making use of both embedded sensors and its advantageous 3D positioning. The environment perception and vehicle/Unmanned Aerial Vehicle (UAV) interactions are managed by a knowledge base in the form of an ontology, and logical rules are used in order to detect and infer the environmental context and UAV management. The model was tested and validated in a simulation made on Unity.