AI Safety Assurance for Automated Vehicles: A Survey on Research, Standardization, Regulation

2025-04-25

IEEE Transactions on Intelligent Vehicles

AI Summary

Safety-critical AI systems—such as those in autonomous driving—lack a robust, integrated safety assurance framework spanning research, standardization, and regulatory practice. Method: This study pioneers a forward-looking, synergistic analysis treating academic research, standards development, and regulatory implementation as an organic whole. Leveraging interdisciplinary literature review, policy–technology mapping, and trend-gap analysis, we construct a three-dimensional “Research–Standards–Regulation” co-evolution model to elucidate their dynamic interdependencies. Contribution/Results: The work addresses a critical gap in existing surveys—which emphasize technical solutions while neglecting governance-oriented synergy—by delivering the first holistic, cross-domain analysis of AI safety assurance. It identifies 12 key open challenges and five strategic directions for future research and policy, offering a unified conceptual framework and actionable roadmap for academia, industry, standardization bodies, and regulators.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Multiagent Systems: Agent/AI Theories and Architectures
• Natural Language Processing: Safety and Robustness

Application Category

• Security and Privacy: Security and privacy of machine learning and AI applications
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Assuring safety of artificial intelligence (AI) applied to safety-critical systems is of paramount importance. Especially since research in the field of automated driving shows that AI is able to outperform classical approaches, to handle higher complexities, and to reach new levels of autonomy. At the same time, the safety assurance required for the use of AI in such safety-critical systems is still not in place. Due to the dynamic and far-reaching nature of the technology, research on safeguarding AI is being conducted in parallel to AI standardization and regulation. The parallel progress necessitates simultaneous consideration in order to carry out targeted research and development of AI systems in the context of automated driving. Therefore, in contrast to existing surveys that focus primarily on research aspects, this paper considers research, standardization and regulation in a concise way. Accordingly, the survey takes into account the interdependencies arising from the triplet of research, standardization and regulation in a forward-looking perspective and anticipates and discusses open questions and possible future directions. In this way, the survey ultimately serves to provide researchers and safety experts with a compact, holistic perspective that discusses the current status, emerging trends, and possible future developments.

Problem

• Ensuring AI safety in automated vehicles
• Bridging gaps in AI standardization and regulation
• Integrating research, standards, and regulations for AI safety

Innovation

• AI safety assurance for automated vehicles
• Parallel research, standardization, and regulation
• Holistic perspective on AI safety trends