25 papers
Stateful Multi-Agent LLMs for Cross-View Interface Alignment in Automotive Model-Based Systems Engineering
Aleksei Velsh, Nenad Petrovic, Alois Knoll
While Large Language Models (LLMs) can accelerate Model-Based Systems Engineering (MBSE) for software-defined vehicles, their probabilistic nature causes "architectural drift", fab…
CyberLLM: A Multi-Agent LLM Framework for Autonomous Detection and Guarded Response in Automotive Cybersecurity
Nenad Petrovic, Oussama Jeddou, Feres Ben Fraj +4
Software-Defined Vehicles (SDVs) expand the automotive attack surface across source code, runtime logs, and deployment topologies, while safety constraints forbid autonomous agents…
Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis
Linus Sander, Fengjunjie Pan, Vahid Zolfaghari +3
The paper identifies four design principles for building scalable large‑language‑model‑driven multi‑agent systems, proposes a reference architecture based on a constrained directed…
LLM-Driven Approach to Modeling Tool Interoperability in Automotive Domain
Nenad Petrovic, Jiajie Zhang, Vahid Zolfaghari +1
The paper proposes using large language models to automate the mapping and merging of heterogeneous modeling tool metamodels in the automotive domain, enabling cross‑tool model int…
GenAI-Driven Approach to RISC-V Supply Chain Exploration
Nenad Petrovic, Andre Schamschurko, Yingjie Xu +1
This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-Language Models (VLMs) and Model-Driven Engineering (MDE) to enable comprehensive…
From Code to Road: A Vehicle-in-the-Loop and Digital Twin-Based Framework for Central Car Server Testing in Autonomous Driving
Chengdong Wu, Sven Kirchner, Nils Purschke +9
Simulation is one of the most essential parts in the development stage of automotive software. However, purely virtual simulations often struggle to accurately capture all real-wor…