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Automated/Autonomous Driving - Prediction and Planning in the Context of Cooperative Driving

Information on the Thesis

Type of Final Thesis: Bachelor, Master
Supervisor: Karl Kurzer
Research Group: Applied Technical Cognitive Systems

Archive Number: 4.160
Status of Thesis: Open
Date of start: 2019-04-09

Further Information

Automated, cooperative vehicles have to make decisions in road traffic in a highly dynamic, interacting and incompletely perceptible environment. Previous attempts are usually limited to situation assessment from an egocentric perspective, without taking cooperation aspects into account, or interactions between other road users.


For the prediction and planning of cooperative driving maneuvers, a procedure is to be developed in this thesis, which takes into account the interdependencies of the individual traffic participants, as well as modeling the system states probabilistically.


  • An interdisciplinary research environment with partners from science and industry
  • A constructive collaboration with bright, motivated employees
  • A pleasant working atmosphere


  • Knowledge in depth and breadth in the field of artificial intelligence, game theory or closely related areas
  • Ability to implement both state of the art, as well as experimental algorithms
  • Good C++ (C++11, STL, etc.) or Python Skills
  • Sound English skills
  • High creativity and productivity
  • Experiences with planning procedures, e.g. Monte Carlo tree search are a plus


  • current transcript of records
  • CV


Karl Kurzer