Master Thesis in Closed-Loop Behavior Planning for Urban Automated Driving
Master Thesis in Closed-Loop Behavior Planning for Urban Automated Driving
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Job Description
- During your thesis you will identify or create scenarios set up evaluation pipelines and define metrics for performance and safety.
- As learning approaches you will implement and compare various techniques be it Reinforcement Learning Imitation Learning or Adversarial Imitation Learning within the established pipeline.
- In form of extensive simulation you will run largescale experiments to assess convergence training stability and hardware requirements.
- Furthermore you will conduct a comparative analysis to track key metrics (collisions route completion computational efficiency) and benchmark against rulebased or learned baselines.
- Finally you will report your findings by documenting insights highlighting strengths and weaknesses of each approach and compile the results in a final report or publicationready manuscript.
Qualifications :
- Education: Master studies in the field of Computer Science Electrical Engineering Mechatronics Mathematics or comparable
- Experience and Knowledge: in Python PyTorch; knowledge of Deep Learning NumPy Reinforcement Learning Inverse Reinforcement Learning
- Personality and Working Practice: you have an analytical mindset with excellent communication skills and are selfdriven plus eager to solve realworld challenges in automated driving
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Jrgen Mathes (Functional Department)
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
