The rise of AI models across diverse domains includes promising advancements, but
also poses critical challenges. In particular, establishing trust in AI-based
systems for mission-critical applications is challenging for most domains. For
the automotive domain, embedded systems are operating in real-time and
undertaking mission-critical tasks. Ensuring dependability attributes,
especially safety, of these systems remains a predominant challenge.
This article focuses on the application of AI-based systems in safety-critical
contexts within automotive domains. Drawing from current standardization
methodologies and established patterns for safe application, this work offers a
reflective analysis, emphasizing overlaps and potential avenues to put AI-based
systems into practice within the automotive landscape. The core focus lies in
incorporating pattern concepts, fostering the safe integration of AI in
automotive systems, with requirements described in standardization and topics
discussed by AI working groups.
This article aims to provide a concept on leveraging AI-based systems while
addressing safety concerns within the automotive sector and current versions of
related standards. The proposed approach explores synergies and highlights
pathways for the utilization of AI-based systems within safety-critical
automotive applications.
