A decision support framework for autonomous driving in normal and emergencysituations | IEEE Conference Publication | IEEE Xplore

A decision support framework for autonomous driving in normal and emergencysituations | IEEE Conference Publication | IEEE Xplore

For a decade, a lot of researches have focused on the development and the deployment of automated mobility services and means for road networks (urban, suburb, rural, highway). In the development of autonomous driving embedded systems, several stages are needed. The first one concerns the perception layers. The second one is dedicated to the risk assessment, the decision and strategy layers and the optimal path planning. The last one addresses the control/command parts. Based on the Autonomous Decision-Support Framework (ADSF) of the EU project Trustonomy, this paper proposes a risk assessment and decision-making framework to the second stage and improves an existing virtual co-pilot by combining a new emergency mode and corresponding trajectory planning algorithm. After introducing the project framework for risk management and the general co-pilot concept developed in the University Gustave Eiffel, the Decision-Support framework, implemented in RTMaps platform, is demonstrated within a realistic 3D simulation environment called Pro-SiVIC. Both the previous virtual copilot and the new emergency algorithm are combined and a switching strategy between the different modes is tested in a near-accident situation.

W. Xu, R. Sainct, D. Gruyer and O. Orfila, "A decision support framework for autonomous driving in normal and emergencysituations," 2021 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE), 2021, pp. 1-6, doi: 10.23919/AEITAUTOMOTIVE52815.2021.9662696.