Safe Vehicle Trajectory Planning in an Autonomous Decision Support Framework for Emergency Situations

For a decade, researchers have focused on the development and deployment of road

automated mobility. In the development of autonomous driving embedded systems, several stages

are required. The first one deals with the perception layers. The second one is dedicated to the risk

assessment, the decision and strategy layers and the optimal trajectory planning. The last stage

addresses the vehicle control/command. This paper proposes an efficient solution to the second

stage and improves a virtual Cooperative Pilot (Co-Pilot) already proposed in 2012. This paper thus

introduces a trajectory planning algorithm for automated vehicles (AV), specifically designed for

emergency situations and based on the Autonomous Decision-Support Framework (ADSF) of the

EU project Trustonomy. This algorithm is an extended version of Elastic Band (EB) with no fixed

final position. A set of trajectory nodes is iteratively deduced from obstacles and constraints, thus

providing flexibility, fast computation, and physical realism. After introducing the project framework

for risk management and the general concept of ADSF, the emergency algorithm is presented and

tested under Matlab software. Finally, the Decision-Support framework is implemented under

RTMaps software and demonstrated within Pro-SiVIC, a realistic 3D simulation environment. Both

the previous virtual Co-Pilot and the new emergency algorithm are combined and used in a nearaccident

situation and shown in different risky scenarios.