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# Master / Bachelor - Survey of Vehicle AD - Software Architectures - Entwicklung, Forschung, IT

- **Company:** Deutsches Zentrum für Luft- und Raumfahrt e. V.
- **Location:** Weßling, Germany
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Middleware, Python (Programming Language), Open Source Technology, Software Architecture, Red Hat Enterprise Linux, Zotero, Large Language Models, Information Technology, Baidu
- **Published:** August 30, 2026
- **Apply:** https://www.adzuna.de/details/5860755864

## About the Role

* 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.

## Description

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.


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