Thema4160/en: Unterschied zwischen den Versionen
Co1539 (Diskussion | Beiträge) |
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'''TASKS''' | '''TASKS''' | ||
| − | For the prediction and planning of cooperative driving maneuvers, a method is to be developed | + | 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''' | '''WE OFFER''' | ||
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*Sound English or German skills | *Sound English or German skills | ||
*High creativity and productivity | *High creativity and productivity | ||
| − | *Knowledge in the field of artificial intelligence, game theory or related areas | + | *Knowledge in the field of artificial intelligence (especially searching and learning), game theory or related areas |
| − | *Experiences with | + | *Experiences with methods for searching and learning, e.g. Monte Carlo tree search/Reinforcement Learning are a plus |
'''REQUIRED DOCUMENTS''' | '''REQUIRED DOCUMENTS''' | ||
Version vom 25. September 2018, 14:13 Uhr
Type of Final Thesis:
Bachelor
Supervisor: Selina Schüler, Andreas 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
Sorry, no english description available!
Prediction and Planning of Cooperative Driving Maneuvers
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