1 citations · 1 across the 18 of their papers we have counts for
22 papers
Porimon: An LLM-Based Pokémon Battle Agent Enhanced by Long/Short-Term Knowledge Augmented Generation
Dongyin Zhuo, Fengjunjie Pan, Nenad Petrovic +1
In this paper, we use Pokémon Battles as a case study to investigate how to improve the performance of LLM-based agents in tasks that require opponent-aware planning without additi…
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…
Dr. AGENTONOMICS: A Didactic Experiment of AGENTONOMICS
Fengjunjie Pan, Alois Knoll
AGENTONOMICS is a framework that treats AI agents as economic entities that can be designed, managed, and governed through an integrated management architecture. Dr. AGENTONOMICS i…
Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis
Linus Sander, Fengjunjie Pan, Vahid Zolfaghari +3
LLM-based multi-agent systems have the potential to enable collective intelligence and scale toward solving highly complex tasks through coordinated ensembles of specialized agents…
LLM-Empowered Functional Safety and Security by Design in Automotive Systems
Nenad Petrovic, Vahid Zolfaghari, Fengjunjie Pan +1
This paper presents LLM-empowered workflow to support Software Defined Vehicle (SDV) software development, covering the aspects of security-aware system topology design, as well as…
LLM-Empowered Event-Chain Driven Code Generation for ADAS in SDV systems
Nenad Petrovic, Norbert Kroth, Axel Torschmied +9
This paper presents an event-chain-driven, LLM-empowered workflow for generating validated, automotive code from natural-language requirements. A Retrieval-Augmented Generation (RA…
Hallucination in LLM-Based Code Generation: An Automotive Case Study
Marc Pavel, Nenad Petrovic, Lukasz Mazur +3
Large Language Models (LLMs) have shown significant potential in automating code generation tasks offering new opportunities across software engineering domains. However, their pra…
GenAI for Automotive Software Development: From Requirements to Wheels
Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari +3
This paper introduces a GenAI-empowered approach to automated development of automotive software, with emphasis on autonomous and Advanced Driver Assistance Systems (ADAS) capabili…
Survey of GenAI for Automotive Software Development: From Requirements to Executable Code
Nenad Petrovic, Vahid Zolfaghari, Andre Schamschurko +10
Adoption of state-of-art Generative Artificial Intelligence (GenAI) aims to revolutionize many industrial areas by reducing the amount of human intervention needed and effort for h…
Are requirements really all you need? A case study of LLM-driven configuration code generation for automotive simulations
Krzysztof Lebioda, Nenad Petrovic, Fengjunjie Pan +3
Large Language Models (LLMs) are taking many industries by storm. They possess impressive reasoning capabilities and are capable of handling complex problems, as shown by their ste…
Optimizing Retrieval Augmented Generation for Object Constraint Language
Kevin Chenhao Li, Vahid Zolfaghari, Nenad Petrovic +2
The Object Constraint Language (OCL) is essential for defining precise constraints within Model-Based Systems Engineering (MBSE). However, manually writing OCL rules is complex and…
Automating Automotive Software Development: A Synergy of Generative AI and Model-Based Methods
Fengjunjie Pan, Yinglei Song, Long Wen +3
As the automotive industry shifts its focus toward software-defined vehicles, the need for faster and reliable software development continues to grow. However, traditional methods…
LLM-enabled Instance Model Generation
Fengjunjie Pan, Nenad Petrovic, Vahid Zolfaghari +2
In the domain of model-based engineering, models are essential components that enable system design and analysis. Traditionally, the creation of these models has been a manual proc…
LLM-based Iterative Approach to Metamodeling in Automotive
Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari +1
In this paper, we introduce an automated approach to domain-specific metamodel construction relying on Large Language Model (LLM). The main focus is adoption in automotive domain.…
Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study
Nenad Petrovic, Yurui Zhang, Moaad Maaroufi +5
Multimodal summarization integrating information from diverse data modalities presents a promising solution to aid the understanding of information within various processes. Howeve…
Virtualization & Microservice Architecture for Software-Defined Vehicles: An Evaluation and Exploration
Long Wen, Markus Rickert, Fengjunjie Pan +4
The emergence of Software-Defined Vehicles (SDVs) signifies a shift from a distributed network of electronic control units (ECUs) to a centralized computing architecture within the…
Gassidy: Gaussian Splatting SLAM in Dynamic Environments
Long Wen, Shixin Li, Yu Zhang +5
3D Gaussian Splatting (3DGS) allows flexible adjustments to scene representation, enabling continuous optimization of scene quality during dense visual simultaneous localization an…
Adopting RAG for LLM-Aided Future Vehicle Design
Vahid Zolfaghari, Nenad Petrovic, Fengjunjie Pan +2
In this paper, we explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) to enhance automated design and software development in the auto…
Automatic Platform Configuration and Software Integration for Software-Defined Vehicles
Fengjunjie Pan, Jianjie Lin, Markus Rickert
In the automotive industry, platform configuration and software integration are mostly manual tasks performed during the development phase, requiring consideration of various safet…
A Containerized Microservice Architecture for a ROS 2 Autonomous Driving Software: An End-to-End Latency Evaluation
Tobias Betz, Long Wen, Fengjunjie Pan +6
The automotive industry is transitioning from traditional ECU-based systems to software-defined vehicles. A central role of this revolution is played by containers, lightweight vir…
Synergy of Large Language Model and Model Driven Engineering for Automated Development of Centralized Vehicular Systems
Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda +6
We present a prototype of a tool leveraging the synergy of model driven engineering (MDE) and Large Language Models (LLM) for the purpose of software development process automation…
Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow
Krzysztof Lebioda, Viktor Vorobev, Nenad Petrovic +3
We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined. Instead, it emerges from an i…