| Modeling Interactions of Autonomous Vehicles and Pedestrians with Deep Multi-Agent Reinforcement Learning for Collision Avoidance R Trumpp, H Bayerlein, D Gesbert 2022 IEEE Intelligent Vehicles Symposium (IV), 331-336, 2022 | 16 | 2022 |
| Residual Policy Learning for Vehicle Control of Autonomous Racing Cars R Trumpp, D Hoornaert, M Caccamo 2023 IEEE Intelligent Vehicles Symposium (IV), 1-6, 2023 | 5 | 2023 |
| Efficient Learning of Urban Driving Policies Using Bird'View State Representations R Trumpp, M Büchner, A Valada, M Caccamo 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 2* | 2023 |
| Learning to Generate All Feasible Actions M Theile, D Bernardini, R Trumpp, C Piazza, M Caccamo, ... IEEE Access, 2024 | | 2024 |
| RaceMOP: Mapless online path planning for multi-agent autonomous racing using residual policy learning R Trumpp, E Javanmardi, J Nakazato, M Tsukada, M Caccamo arXiv preprint arXiv:2403.07129, 2024 | | 2024 |
| Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks BD Evans, R Trumpp, M Caccamo, HW Jordaan, HA Engelbrecht arXiv preprint arXiv:2402.18558, 2024 | | 2024 |
| Implementierung des Poly-reference Least Square Complex Frequency (p-LSCF) Algorithmus zur Operational Modal Analysis (OMA) RF Trumpp | | 2017 |
