3 citations · 5 across the 4 of their papers we have counts for
4 papers
Safety Reinforced Model Predictive Control (SRMPC): Improving MPC with Reinforcement Learning for Motion Planning in Autonomous Driving
Johannes Fischer, Marlon Steiner, Ömer Sahin Tas +1
Model predictive control (MPC) is widely used for motion planning, particularly in autonomous driving. Real-time capability of the planner requires utilizing convex approximation o…
PITA: Physics-Informed Trajectory Autoencoder
Johannes Fischer, Kevin Rösch, Martin Lauer +1
Validating robotic systems in safety-critical appli-cations requires testing in many scenarios including rare edgecases that are unlikely to occur, requiring to complement real-wor…
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments
Arec Jamgochian, Etienne Buehrle, Johannes Fischer +1
Designing a safe and human-like decision-making system for an autonomous vehicle is a challenging task. Generative imitation learning is one possible approach for automating policy…
Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning
Danial Kamran, Tizian Engelgeh, Marvin Busch +2
Despite recent advances in reinforcement learning (RL), its application in safety critical domains like autonomous vehicles is still challenging. Although punishing RL agents for r…