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Master / Bachelor - Survey of Vehicle AD - Software Architectures (f/m/d)
Job Description
Req ID:  3643
Place of work:  Oberpfaffenhofen, Stuttgart
Starting date:  as soon as possible
Career level:  Internship, Student research project and final thesis, Student employment
Type of employment:  Part time
Duration of contract:  4-6 months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 11,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The Institute of Vehicle Concepts (FK) of the German Aerospace Centre (DLR) is internationally recognised for the design of future road and rail vehicles that enable climate and environmentally friendly mobility while being affordable and user-friendly at the same time.

We research and demonstrate the required key technologies  and maintain close cooperation with other scientific institutions as well as industrial and political bodies.

 

What to expect
You will work with our team on a systematic survey of software architectures for automated driving, focusing on end-to-end approaches, modular pipelines, and agentic AD systems (LLM-based, tool-using agents and orchestration).
You will develop a taxonomy of the different architectures, analyze relevant open-source stacks (e.g., Autoware, Baidu Apollo, potentially S-Core/Red Hat ecosystems) based on documentation, releases, and repositories, and derive technological trends, gaps, and actionable recommendations.

 

Your tasks

  • refine the topic and formulate precise research questions.
  • conduct a systematic literature search (IEEE, ACM, arXiv, Google Scholar), screen the studies, and extract relevant data.
  • develop a taxonomy of architectures: end-to-end vs. modular vs. agentic (roles, orchestration, tool use, safety/runtime aspects).
  • compare open-source AD stacks, analyzing architecture layers, middleware (e.g., ROS 2/CyberRT), APIs, roadmaps, releases, licensing/governance, community metrics, and maturity levels.
  • map agentic AD concepts, including agent roles (planner, safety critic/verifier, perception narrator, controller designer), communication patterns, knowledge integration (e.g., RAG), and integration points within existing stacks.
  • compile the landscape of relevant benchmarks and datasets, especially for scenarios such as parking or docking.
  • create evidence syntheses, comparison tables, and visualizations, deriving guidelines and research gaps.
  • contribute to scientific writing (DE/EN) and prepare the final presentation.

 

Your profile 

  • Academic studies in a relevant technical or engineering field such as Industrial Engineering, Mechanical Engineering, Automotive Engineering, Computer Science, Robotics, Electrical Engineering, Mechatronics, Control Engineering, Aerospace Engineering, or Technical Business Administration or similar
  • Interest in automated driving, software architectures, and agentic AD/LLM-based concepts.
  • Basic knowledge of literature research and academic referencing (e.g., BibTeX, Zotero, systematic screening).
  • Structured, analytical working style with precise documentation (EN/DE).
  • Beneficial: Basic skills in programming (e.g., Python/C++) and experience in open-source communities.
  • Remuneration is according to the German TVöD 05.

 

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 3643) please contact:

 

Daniel Diegel 
Tel.: 08153 28 4961 
Apply now