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AI-Based End-to-End Automotive Design and Software Development for SDVs

N. Petrovic, A. C. Knoll · 2026 · Verein Deutscher Ingenieure e.V. eBooks

DOI: 10.51202/9783181024751-39 · cited by 0 works (OpenAlex) · open-access PDF

Hindi

इस लेख में सॉफ्टवेयर परिभाषित वाहनों (SDVs) के लिए अंत-उत्तर ऑटोमोबाइल डिजाइन और सॉफ्टवेयर विकास को सक्षम करने के लिए कृत्रिम बुद्धि (AI) की क्षमता का पता लगाया गया है। केंद्रीय कार सर्वर (CeCaS) और अनुसरण यूरोपीय संघ द्वारा वित्त पोषित परियोजनाओं के भीतर हमारे योगदान के आधार पर, हम एक एआई-आधारित टूलचेन पेश करते हैं जो मॉडल-ड्राइव इंजीनियरिंग (MDE) के साथ बड़े भाषा मॉडल (LLMs) को एकीकृत करता है ताकि प्राकृतिक भाषा आवश्यकताओं को सिस्टम आर्किटेक्चर, संचालित सॉफ्टवेयर और सत्यापन आर्टिफैक्ट में बदलने के लिए स्वचाल

Machine translation (Meta M2M100); the English original follows.

Abstract

This paper explores the potential of Artificial Intelligence (AI) to enable end-to-end automotive design and software development for Software-Defined Vehicles (SDVs). Based on our contributions within the Central Car Server (CeCaS) and follow-up EU-funded projects, we present an AI-driven toolchain integrating Large Language Models (LLMs) with Model-Driven Engineering (MDE) to automate the transformation of natural-language requirements into system architectures, executable software, and validation artifacts. The approach emphasizes traceability, consistency, and compliance with safety-critical automotive development requirements. Validation is performed on a centralized vehicle computing platform supporting adaptive cruise control and emergency braking, tested in Hardware-in-the-Loop (HiL) and Software-in-the-Loop (SiL) environments. We discuss current capabilities, practical limitations, and future directions toward increasingly automated, reliable, and quality-assured automotive software development with minimal human intervention.

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Topics: Engineering, Software, Computer science, Automotive industry, Software development, Systems engineering

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