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

Author:

Perez-Cerrolaza Jon1,Abella Jaume2,Borg Markus3,Donzella Carlo4,Cerquides Jesús5,Cazorla Francisco J.6,Englund Cristofer3,Tauber Markus7,Nikolakopoulos George8,Flores Jose Luis9

Affiliation:

1. Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Spain

2. Barcelona Supercomputing Center (BSC), Spain

3. RISE Research Institutes of Sweden AB, Sweden

4. Exida, Italy

5. Artificial Intelligence Research Institute (IIIA-CSIC), Spain

6. BSC and Maspatechnologies S.L., Spain

7. Research Studios Austria, Austria

8. Luleå University of Technology, Sweden

9. Ikerlan Technology Research Centre, BRTA, Spain

Abstract

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.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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