Treffer: Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A Survey

Title:
Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A Survey
Contributors:
Barcelona Supercomputing Center
Publisher Information:
ACM Computing Surveys
Publication Year:
2024
Collection:
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge
Document Type:
Fachzeitschrift article in journal/newspaper
File Description:
application/pdf
Language:
English
DOI:
10.1145/3626314
Rights:
http://creativecommons.org/licenses/by/4.0/ ; Open Access ; Attribution 4.0 International
Accession Number:
edsbas.A682443
Database:
BASE

Weitere Informationen

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. ; Peer Reviewed ; Postprint (published version)