Buch, Englisch, 198 Seiten, Format (B × H): 155 mm x 235 mm
Hardware, Software, Design Methodologies, Workshop Proceedings
Buch, Englisch, 198 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-032-34892-0
Verlag: Springer Nature Switzerland AG
This book presents a practical roadmap for developing dependable, scalable, and evolvable software-defined vehicles by combining AI-driven engineering, data-centric architectures, and continuous verification. It enables faster deployment of reliable Level 4 autonomous functions while reducing development and validation effort through compliance-by-design methodologies.
Its novel contribution is the integration of Generative AI, digital twins, heterogeneous redundancy, and uncertainty-aware inference to bridge probabilistic AI with functional safety requirements. The book covers the entire Software-Defined Vehicle lifecycle, including hardware-software co-design, perception, V2X localization, adaptive vehicle systems, and verification. Intended for automotive engineers, researchers, and graduate students, it serves as both a reference and a practical guide for automating development workflows and implementing scalable assurance for next-generation intelligent vehicles.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Vehicle data architecture approach – A game changer towards software-centric development in automotive.- Checkpoint-based Integration of Early Exits for Automotive ML Tasks in Centralized Platforms.- On Benchmarking Systolic-Array-based Accelerators for Automotive Applications.
