A Safety Monitoring Concept for Fully Automated Driving

Paper in proceeding, 2020

Safe motion planning for automated vehicles requires that a collision-free trajectory can be guaranteed. For that purpose, we propose a monitoring concept that would ensure safe vehicle states. Determining these safe states, however, is usually a computationally demanding task. To alleviate the computational demand, we investigate the possibility to compute the safe sets offline. To achieve this, we leverage backward reachability theory and compute the N-step robust backward reachable set offline. Based on the current disturbances, we demonstrate the possibility to adapt this set online. The safety guarantees are then provided by computing the robust one-step forward prediction of the state vector and checking if these states are members of the adapted safe set. The numerical example demonstrates that the approach is capable of avoiding hazardous vehicle states under an unsafe motion planning algorithm.