Yuanfei Lin joined the Cyber Physical Systems Group as a PhD candidate under the supervision of Prof. Dr.-Ing. Matthias Althoff in 2021. He graduated with the Master of Science degree in Mechanical Engineering from the Technical University of Munich, Germany, in 2020. He received the Bachelor of Engineering degree in Automotive Engineering from the Tongji University, Shanghai, China, in 2018. During the period from August 2023 to February 2024, he was a visiting research scholar at the University of California, Berkeley, working with Prof. Masayoshi Tomizuka.
His research focuses on safe motion planning for autonomous vehicles, safe cooperative motion planning, and formal methods. More information can be found in his personal page.
Research Highlight
DrPlanner: the first framework to autonomously diagnose and repair motion planners, harnessing the power of LLMs that improve as they scale
Model Predictive Robustness: a novel approach to determine the robustness of STL predicates, where the model capability for rule compliance is explicitly considered
Offered Thesis Topics
I am always looking for self-motivated students to solve interesting problems arising in my research areas. General ideas could be to apply formal methods and machine learning technologies to motion planning algorithms for autonomous vehicles to increase their safety, liability, and efficiency. If you are interested in one of the currently available topics, simply send me a mail with a short statement about your motivation, an up-to-date CV, and transcript of records attached.
[MA] Leveraging Large Language Models for Criticality Measures
[HIWI] Cooperative Autonomous Driving through Vehicle-to-Vehicle Communications
[Practical Course] Repairing Motion Planners using Large Language Models
Thesis & Hiwi
Bachelor Thesis
[BA] Carl Heimann - Risk-aware Motion Planning for Autonomous VehiclesMarch 2024
