Section: New Results

Other

A Framework for Proactive Assistance

Participants : Alexandre Armand, David Filliat [correspondant] .

We worked in collaboration with Renault on the problems of adapting driving assitance systems by learning individual drivers behaviours and of integrating more advanced perception in these systems. Advanced Driving Assistance Systems usually provide assistance to drivers only once a high risk situation has been detected. Indeed, it is difficult for an embedded system to understand driving situations, and to predict early enough that it is to become uncomfortable or dangerous. Most of ADAS work assume that interactions between road entities do not exist (or are limited), and that all drivers react in the same manner in similar conditions. We propose a framework that enables to fill these gaps. On one hand, an ontology which is a conceptual description of entities present in driving spaces is used to understand how all the perceived entities interact together with the subject vehicle, and govern its behavior. On the other hand, a dynamic Bayesian Network enables to estimate the driver situation awareness with regard to the perceived objects, based on the ontology inferences, map information, driver actuation and learned driving style. This work was published in a workshop [33] and a conference paper [32] .