Publikationen
2023
- Diehl, C., T. Sievernich, M. Krüger, F. Hoffmann, T. Bertram: ”Uncertainty‑Aware Model‑Based Offline Reinforcement Learning for Automated Driving”, Robotics and Automation Letters (RA-L), 2023
- Osterburg, T., C. Diehl, T. Bertram: ”Social Behavior Prediction for Automated Vehicles Using Contrastive Learning”, IFToMM D‑A‑CH, 2023 (Accepted)
2022
- Krüger, M., P. Palmer, C. Diehl, T. Osterburg, T. Bertram: ”Recognition Beyond Perception: Environmental Model Completion by Reasoning for Occluded Vehicles”, IEEE Robotics and Automation Letters (RA-L), 2022.
- Diehl, C., T. Osterburg, N. Murzyn, G. Schneider, F. Hoffmann, T. Bertram: ”Conditional Behavior Prediction for Automated Driving on Highways”, Proc. 32. Workshop Computational Intelligence (CIW), 2022.
- Novo, A.S., M. Stolpe, C. Diehl, T. Osterburg, T. Bertram, V. Parsi, N. Murzyn, F. Mualla, G. Schneider, P. Töws: ”Mid‑term status report on KISSaF: AI‑based Situation Interpretation for Automated Driving”, Automotive meets Electronics (AME), 2022.
2021
- Nattermann,T. : Scene Prediction for ADAS/AD Functions
Scale Up 360: Advanced Driver Assistance Systems https://www.scale-up-360.com/en/adas/agenda#/ - Diehl C., T. Sievernich, M. Krüger, F. Hoffmann, T. Bertram: UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning, Advances in Neural Information Processing Systems 35 - Machine Learning for Autonomous Driving Workshop, 2021