Picture of Edmond Irani Liu

Edmond Irani Liu, M.Sc.

Technical University of Munich

Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems (Prof. Knoll)

Postal address

Boltzmannstr. 3
85748 Garching b. München

Curriculum Vitae

Edmond Irani Liu joined the Cyber-Physical Systems Group in 2019 as a Research Assistant and Ph.D. student under the supervison of Prof. Dr.-Ing. Matthias Althoff. In 2015 and 2018,  he received his bachelor's degree in Automation and master's degree in Control Science and Engineering, both from Shanghai Jiao Tong University, respectively.

His current research focuses on provably-safe cooperative driving of automated vehicles. He is a participant in the project Cooperative and Intrinsically-Correct Control of Vehicles in Diverse Environments (CoInCIDE) within the Priority Program Cooperatively Interacting Automobiles (SPP1835), funded by the German Research Foundation (DFG).

Offered Thesis Topics

I am always looking for self-motivated students to solve interesting problems arising in my research areas. If you are interested in one of the currently available topics, simply send me a mail with your up-to-date CV and transcript of records attached. A guide to writing good thesis can be found here.

Currently Available:

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Teaching Experience

  • Practical course - Motion Planning for Autonomous Vehicles (since WS 2019)
    • CommonRoad Interactive Benchmark Generation
    • Developing a Hierarchical A* Motion Planning Algorithm
    • Improving a Graph Search-Based Motion Planning Algorithm
    • Formation of Cooperative Groups for Automated Vehicles
  • Seminar course -  Cyber-Physical Systems (since WS 2019)
    • Safe and Efficient Cooperation Strategies at Intersections



  • Irani Liu, Edmond; Pek, Christian; Althoff, Matthias: Provably-Safe Cooperative Driving via Invariably Safe Sets. 2020 IEEE Intelligent Vehicles Symposium (IV), 2020, 1-8 mehr… Volltext (mediaTUM)
  • Klischat, Moritz; Irani Liu, Edmond; Höltke, Fabian; Althoff, Matthias: Scenario Factory: Creating Safety-Critical Traffic Scenarios for Automated Vehicles. 2020 IEEE International Conference on Intelligent Transportation Systems (ITSC), 2020 mehr… Volltext (mediaTUM)


  • Irani Liu, Edmond; Wang, Jingchuan; Chen, Weidong: A Localizability Constraint-Based Path Planning Method for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems 20 (7), 2019, 2593-2604 mehr… Volltext ( DOI )


  • Irani Liu, Edmond; Chen, Weidong; Wang, Jingchuan: A Localizability Constraint-Based Path Planning Method for Unmanned Aerial Vehicle. In: Intelligent Autonomous Systems 15. Springer International Publishing, 2018 mehr… Volltext ( DOI )

Last updated: 18.05.2020