Context Modelling applied to the Intelligent Vehicle Navigation

Federico Faruffini (1) , Hugo Pousseur (1) , Alessandro Corrêa Victorino (1) , Marie-Hélène Abel (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

This paper faces the problem of intelligent vehicles in interaction with their occupants and the environment, by modelling the semantic context associated to the navigation. With a semantically modelled context, an intelligent vehicle will not only drive itself safely, but it will also be able to reason on the situation and act accordingly. To do so, it is necessary to first define the Context of Navigation, and then to set the inference rules for it, in order to enrich the robot's comprehension of the situation. In this paper we propose our definition of the Context of Navigation, based on the information that could be needed by the vehicle's controller. We split it into two components: the Dynamic Context and the Static Context. In this paper we will focus on the latter. We then model the Static Context of Navigation of the autonomous driving-for instance the passengers' driving preferences-and to make the robotic car adapt its behaviour to this new information in real time. Finally, a short practical example of our proposition is shown and discussed.

Mots clés: Human Factors; Assistive Technology; Human-Machine Cooperation and Systems

Domaines: Informatique; Automatique / Robotique

Federico Faruffini, Hugo Pousseur, Alessandro Corrêa Victorino, Marie-Hélène Abel. Context Modelling applied to the Intelligent Vehicle Navigation. 47th Annual Conference of the IEEE Industrial Electronics Society (IECON 2021), Oct 2021, Toronto, Canada. pp.1-6, ⟨10.1109/IECON48115.2021.9589399⟩. ⟨hal-03523249⟩