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= Automated/Autonomous Driving - Prediction and Planning in the Context of Cooperative Driving =
 
  
 
Automated, cooperative vehicles have to make decisions in road traffic in a highly dynamic, interacting and incompletely perceptible environment. Previous approaches are usually only considering an egocentric perspective, without considering any cooperative aspects, with or between others.
 
Automated, cooperative vehicles have to make decisions in road traffic in a highly dynamic, interacting and incompletely perceptible environment. Previous approaches are usually only considering an egocentric perspective, without considering any cooperative aspects, with or between others.

Version vom 14. Januar 2019, 10:41 Uhr


Prozessmodellgenerierung im Kontext der Nutzung mobiler Endgeräte


Julia Anna-Maria Kuhn


Information on the Thesis

Type of Final Thesis: Bachelor
Supervisor: Selina SchülerAndreas Oberweis
Research Group: Business Information Systems

Archive Number: 4.160
Status of Thesis: Completed
Date of start: 2021-12-24
Date of submission: 2022-05-16

Further Information

Sorry, no english description available!




Automated, cooperative vehicles have to make decisions in road traffic in a highly dynamic, interacting and incompletely perceptible environment. Previous approaches are usually only considering an egocentric perspective, without considering any cooperative aspects, with or between others.

TASKS

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

WE OFFER

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

WE EXPECT

  • Ability to implement both state of the art and experimental algorithms
  • Basic C++ knowledge (C++11, STL, etc.)
  • Sound English or German skills
  • High creativity and productivity
  • Knowledge in the field of artificial intelligence (especially searching and learning), game theory or related areas
  • Experiences with methods for searching and learning, e.g. Monte Carlo tree search/Reinforcement Learning are a plus

REQUIRED DOCUMENTS

  • current transcript of records
  • CV

CONTACT

Karl Kurzer