Lars Ullrich, M. Sc.
Lars Ullrich, M.Sc.
Research Interests
- Consistent consideration of uncertainties in non-linear systems
- Real-time control and reliable stochastic model predictive control
- Embedded and real-time AI & optimization methods
Biography
- Since May 2022 Research Assistant, Chair of Automatic Control Engineering, FAU Erlangen-Nuremberg
- 2019-2022 Study of Mechatronics (M.Sc.), FAU Erlangen-Nuremberg
- 2020-2021 Study of Control, Robotics and Autonomous Systems, Aalto University
- 2016-2019 Study of Mechatronics (B.Eng.), DHBW Mosbach
- 2018 Fulbright Intercultural Communication Program, Georgia Institute of Technology
Publications
2025
- Ullrich, L., Buchholz, M., Petit, J., Dietmayer, K., & Graichen, K. (2025). A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differences. In Proceedings of the 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC). Gold Coast (Australia).
- Ullrich, L., Mujirishvili, Z., & Graichen, K. (2025). Enhancing system self-awareness and trust of AI: A case study in trajectory prediction and planning. In Proceedings of the 36th IEEE Intelligent Vehicles Symposium (IV). Cluj-Napoca (Romania).
- Ullrich, L., Zimmer, W., Greer, R., Graichen, K., Knoll, A.C., & Trivedi, M. (2025). A New Perspective On AI Safety Through Control Theory Methodologies. IEEE Open Journal of Intelligent Transportation Systems. https://doi.org/10.1109/OJITS.2025.3585274
2024
- Rabenstein, G., Ullrich, L., & Graichen, K. (2024). Sampling for model predictive trajectory planning in autonomous driving using normalizing flows. In Proceedings of the 35th IEEE Intelligent Vehicles Symposium (IV) (pp. 2091-2096). Jeju Island (Korea).
- Ullrich, L., Buchholz, M., Dietmayer, K., & Graichen, K. (2024). AI safety assurance for automated vehicles: A survey on research, standardization, regulation. IEEE Transactions on Intelligent Vehicles. https://doi.org/10.1109/TIV.2024.3496797
- Ullrich, L., Buchholz, M., Dietmayer, K., & Graichen, K. (2024). Expanding the Classical V-Model for the Development of Complex Systems Incorporating AI. IEEE Transactions on Intelligent Vehicles. https://doi.org/10.1109/TIV.2024.3434515
- Ullrich, L., McMaster, A., & Graichen, K. (2024). Transfer learning study of motion transformer based trajectory predictions. In Proceedings of the 35th IEEE Intelligent Vehicles Symposium (IV) (pp. 110-117). Jeju Island (Korea).
2023
- Ullrich, L., Völz, A., & Graichen, K. (2023). Robust meta-learning of vehicle yaw rate dynamics via conditional neural processes. In Proceedings of the 62nd IEEE Conference on Decision and Control (CDC). Marina Bay Sands (Singapore).
Open theses
Current and completed theses
- Trajectory Planning in Autonomous Driving
- Safety Assurance for Meta-Learning in Autonomous Driving (HiWi)
- Investigation of the transferability of data-driven prediction models of other traffic participants in the field of highly automated driving. (MA)
- Implementation and integration of data-driven prediction models of other traffic participants into an existing software stack. (HiWi)
- Implementation and evaluation of data-driven motion prediction models of dynamic road traffic objects for autonomous driving. (FP)
- Investigation of neuromorphic computing for model predictive control with emphasis on trajectory optimization. (HiWi)
- Investigating the capabilities of stochastic normalizing flows for trajectory planning in autonomous driving. (MA)
- Modeling and evaluation of vehicle models using state of the art simulation software. (HiWi)