| Tum autonomous motorsport: An autonomous racing software for the indy autonomous challenge J Betz, T Betz, F Fent, M Geisslinger, A Heilmeier, L Hermansdorfer, ... Journal of Field Robotics 40 (4), 783-809, 2023 | 70 | 2023 |
| Indy autonomous challenge-autonomous race cars at the handling limits A Wischnewski, M Geisslinger, J Betz, T Betz, F Fent, A Heilmeier, ... 12th International Munich Chassis Symposium 2021: chassis. tech plus, 163-182, 2022 | 61 | 2022 |
| End-to-end neural network for vehicle dynamics modeling L Hermansdorfer, R Trauth, J Betz, M Lienkamp 2020 6th IEEE Congress on Information Science and Technology (CiSt), 407-412, 2021 | 39 | 2021 |
| Investigating accountability for artificial intelligence through risk governance: A workshop-based exploratory study E Hohma, A Boch, R Trauth, C Lütge Frontiers in Psychology 14, 1073686, 2023 | 35 | 2023 |
| Toward safer autonomous vehicles: Occlusion-aware trajectory planning to minimize risky behavior R Trauth, K Moller, J Betz IEEE Open Journal of Intelligent Transportation Systems 4, 929-942, 2023 | 23 | 2023 |
| EDGAR: An Autonomous Driving Research Platform--From Feature Development to Real-World Application P Karle, T Betz, M Bosk, F Fent, N Gehrke, M Geisslinger, L Gressenbuch, ... arXiv preprint arXiv:2309.15492, 2023 | 23 | 2023 |
| Maximum acceptable risk as criterion for decision-making in autonomous vehicle trajectory planning M Geisslinger, R Trauth, G Kaljavesi, M Lienkamp IEEE Open Journal of Intelligent Transportation Systems, 2023 | 18 | 2023 |
| Towards an accountability framework for AI: Ethical and legal considerations A Boch, E Hohma, R Trauth Institute for Ethics in AI, Technical University of Munich: Munich, Germany, 2022 | 11 | 2022 |
| Learning and adapting behavior of autonomous vehicles through inverse reinforcement learning R Trauth, M Kaufeld, M Geisslinger, J Betz 2023 IEEE Intelligent Vehicles Symposium (IV), 1-8, 2023 | 7 | 2023 |
| A Reinforcement Learning-Boosted Motion Planning Framework: Comprehensive Generalization Performance in Autonomous Driving R Trauth, A Hobmeier, J Betz arXiv preprint arXiv:2402.01465, 2024 | 4 | 2024 |
| FRENETIX: A high-performance and modular motion planning framework for autonomous driving R Trauth, K Moller, G Würsching, J Betz IEEE Access, 2024 | 3 | 2024 |
| An end-to-end optimization framework for autonomous driving software R Trauth, P Karle, T Betz, J Betz 2023 3rd International Conference on Computer, Control and Robotics (ICCCR …, 2023 | 3 | 2023 |
| Frenetix Motion Planner: High-Performance and Modular Trajectory Planning Algorithm for Complex Autonomous Driving Scenarios K Moller, R Trauth, G Wuersching, J Betz arXiv preprint arXiv:2402.01443, 2024 | 2 | 2024 |
| Overcoming Blind Spots: Occlusion Considerations for Improved Autonomous Driving Safety K Moller, R Trauth, J Betz arXiv preprint arXiv:2402.01507, 2024 | 2 | 2024 |
| Towards an Accountability Framework for Artificial Intelligence Systems E Hohma, A Boch, R Trauth TUM IEAI Whitepaper TUM Institute for Ethics in Artificial Intelligence …, 2022 | 2 | 2022 |
| Investigating Driving Interactions: A Robust Multi-Agent Simulation Framework for Autonomous Vehicles M Kaufeld, R Trauth, J Betz arXiv preprint arXiv:2402.04720, 2024 | 1 | 2024 |
| Autonomous Driving Software Engineering IM Lienkamp, P Karle | | |