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An Ontology-based Approach to Generate the Advanced Driver Assistance Use Cases of Highway Traffic

Abstract : Autonomous vehicles perceive the environment with different kinds of sensors (camera, radar, lidar...). They must evolve in an unpredictable environment and a wide context of dynamic execution, with strong interactions. In order to generate the safety of the autonomous vehicle, its occupants and the others road users, it is necessary to validate the decisions of the algorithms for all the situations that will be met. These situations are described and generated as different use cases of automated vehicles. In this work, we propose an approach to generate automatically use cases of autonomous vehicle for highway. This approach is based on a three layers hierarchy, which exploits static and mobile concepts we have defined in the context of three ontologies: highway, weather and vehicle. The highway ontology and the weather ontology conceptualize the environment in which evolves the autonomous vehicle, and the vehicle ontology consists of the vehicle devices and the control actions. To apply our approach, we consider a running example about the insertion of a vehicle by the right entrance lane of a highway.
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  • HAL Id : hal-01835139, version 1


Wei Chen, Leila Kloul. An Ontology-based Approach to Generate the Advanced Driver Assistance Use Cases of Highway Traffic. 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management., Sep 2018, Seville, Spain. ⟨hal-01835139⟩



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