Machine learning advancements for vehicle safety systems Review of technical foundations and applications
This report summarizes the integration of Machine Learning (ML) in modern vehicle safety applications. Advances in ML have transformed vehicle safety, shifting from traditional rule-based systems to data-driven, adaptive technologies. These applications include advanced driver assistance, predictive maintenance, real-time traffic management, and autonomous driving. ML encompasses a broad spectrum of methodologies and offers flexibility for various implementations. However, ML introduces challenges like the “black box” problem, ethical concerns, and issues related to privacy and cybersecurity, highlighting the need for further research and regulatory frameworks.
Publisert
Eier
Norges forskningsråd (NFR)
Utfører
Transportøkonomisk institutt (TØI)
Forfattere
Anders Kielland, Anna Piterskaya og Christian Weber
Språk
Engelsk