Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A SurveyJust Accepted

Jon Perez-Cerrolaza, Jaume Abella,Markus Borg, Carlo Donzella, Jesús Cerquides,Francisco J. Cazorla,Cristofer Englund,Markus Tauber,George Nikolakopoulos,Jose Luis Flores

ACM Computing Surveys(2022)

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摘要
Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-critical systems in which Machine Learning (ML) algorithms learn optimized and safe solutions. AI can also support and assist human safety engineers in developing safety-critical systems. However, reconciling both cutting-edge and state-of-the-art AI technology with safety engineering processes and safety standards is an open challenge that must be addressed before AI can be fully embraced in safety-critical systems. Many works already address this challenge, resulting in a vast and fragmented literature. Focusing on the industrial and transportation domains, this survey structures and analyzes challenges, techniques, and methods for developing AI-based safety-critical systems, from traditional functional safety systems to autonomous systems. AI trustworthiness spans several dimensions, such as engineering, ethics and legal, and this survey focuses on the safety engineering dimension.
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关键词
functional safety,autonomous systems
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