An Ontology-based Approach to Relax Traffic Regulation for Autonomous Vehicle Assistance

Philippe Morignot and Fawzi Nashashibi


Knowlege representation, Law, Intelligent Vehicle


Traffic regulation must be respected by all vehicles, either humanor computerdriven. However, extreme traffic situations might exhibit practical cases in which a vehicle should safely and reasonably relax traffic regulation, e.g., in order not to be indefinitely blocked and to keep circulating. In this paper, we propose a high-level representation of an automated vehicle, other vehicles and their environment, which can assist drivers in taking such “illegal” but practical relaxation decisions. This high-level representation (an ontology) includes topological knowledge and inference rules, in order to compute the next high-level motion an automated vehicle should take, as assistance to a driver. Results on practical cases are presented.

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