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

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.

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Publication Details

Journal
IEEE Transactions on Intelligent Vehicles
Published
2024-11-15
DOI
https://doi.org/10.1109/tiv.2024.3496797
Citations
7
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
2.43
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article

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

Knut Graichen, Klaus Dietmayer, Michael Buchholz, Lars Ullrich
7 citations
IEEE Transactions on Intelligent Vehicles
Adversarial Robustness in Machine Learning
2.43
article

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

Knut Graichen, Klaus Dietmayer, Michael Buchholz, Lars Ullrich
article en
7 citations

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.

IEEE Transactions on Intelligent VehiclesVol. 10(10)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Universität Ulm (DE)
Openalex Percentile: Top 9%
Adversarial Robustness in Machine Learning
2.43
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AI Safety Assurance for Automated Vehicles: A Survey on Research, Standardization, Regulation — Knut Graichen, Klaus Dietmayer, et al. · IEEE Transactions on Intelligent Vehicles (2024) | TGRS Research Map | TGRS