3 papers
cs.RO2026
Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment
Jean-Pierre Busch, Guido Linden, Jan Bergmann +1
Recent research in machine and deep learning has shown the potential of learningbased motion planning approaches to improve the driving behavior of automated vehicles, especially i…
cs.CV2026
Robust Fusion of Object-Level V2X for Learned 3D Object Detection
Lukas Ostendorf, Lennart Reiher, Onn Haran +1
Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by line-of-sight and field-of-vi…
cs.CV2025
OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction
Severin Heidrich, Till Beemelmanns, Alexey Nekrasov +2
Autonomous driving has the potential to significantly enhance productivity and provide numerous societal benefits. Ensuring robustness in these safety-critical systems is essential…