4 papers
Generative AI in Systems Engineering: A Framework for Risk Assessment of Large Language Models
Stefan Otten, Philipp Reis, Philipp Rigoll +4
The increasing use of Large Language Models (LLMs) offers significant opportunities across the engineering lifecycle, including requirements engineering, software development, proc…
Structuring Automotive Data for Systems Engineering: A Taxonomy-Based Approach
Carl Philipp Hohl, Philipp Reis, Tobias Schürmann +2
Vehicle data is essential for advancing data-driven development throughout the automotive lifecycle, including requirements engineering, design, verification, and validation, and p…
A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording
Philipp Reis, Joshua Ransiek, David Petri +2
High-quality datasets are essential for training robust perception systems in autonomous driving. However, real-world data collection is often biased toward common scenes and objec…
A Framework for a Capability-driven Evaluation of Scenario Understanding for Multimodal Large Language Models in Autonomous Driving
Tin Stribor Sohn, Philipp Reis, Maximilian Dillitzer +3
Multimodal large language models (MLLMs) hold the potential to enhance autonomous driving by combining domain-independent world knowledge with context-specific language guidance. T…