Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey

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, reconcilin...

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Autores: Pérez Cerrolaza, Jon, Abella, Jaume, Borg, Markus, Donzella, Carlo, Cerquides, Jesús, Cazorla, Francisco J., Englund, Cristofer, Tauber, Markus, Nikolakopoulos, George, Flores, José Luis
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/377985
Acceso en línea:http://hdl.handle.net/10261/377985
Access Level:acceso abierto
Palabra clave:Computing methodologies
Artificial intelligence
Machine learning
Computer systems organization
Dependable and fault-tolerant systems and networks
Robotics
Robotic autonomy
Hardware
Safety critical systems
Functional safety
Autonomous systems
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spelling Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a surveyPérez Cerrolaza, JonAbella, JaumeBorg, MarkusDonzella, CarloCerquides, JesúsCazorla, Francisco J.Englund, CristoferTauber, MarkusNikolakopoulos, GeorgeFlores, José LuisComputing methodologiesArtificial intelligenceMachine learningComputer systems organizationDependable and fault-tolerant systems and networksRoboticsRobotic autonomyHardwareSafety critical systemsFunctional safetyAutonomous systemsArtificial 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 reviewedAssociation for Computing MachineryPérez Cerrolaza, Jon [0000-0001-6389-648X]Abella, Jaume [0000-0001-7951-4028]Borg, Markus [0000-0001-7879-4371]Donzella, Carlo [0009-0002-5102-3205]Cerquides, Jesús [0000-0002-3752-644X]Cazorla, Francisco J. [0000-0002-3344-376X]Englund, Cristofer [0000-0002-1043-8773]Tauber, Markus [0000-0002-0003-2243]Nikolakopoulos, George [0000-0003-0126-1897]Flores, José Luis [0000-0002-5555-9712]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/377985reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1145/3626314Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3779852026-05-22T06:33:51Z
dc.title.none.fl_str_mv 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
spellingShingle Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
Pérez Cerrolaza, Jon
Computing methodologies
Artificial intelligence
Machine learning
Computer systems organization
Dependable and fault-tolerant systems and networks
Robotics
Robotic autonomy
Hardware
Safety critical systems
Functional safety
Autonomous systems
title_short Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
title_full Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
title_fullStr Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
title_full_unstemmed Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
title_sort Artificial Intelligence for safety-critical Systems in Industrial and transportation domains: a survey
dc.creator.none.fl_str_mv Pérez Cerrolaza, Jon
Abella, Jaume
Borg, Markus
Donzella, Carlo
Cerquides, Jesús
Cazorla, Francisco J.
Englund, Cristofer
Tauber, Markus
Nikolakopoulos, George
Flores, José Luis
author Pérez Cerrolaza, Jon
author_facet Pérez Cerrolaza, Jon
Abella, Jaume
Borg, Markus
Donzella, Carlo
Cerquides, Jesús
Cazorla, Francisco J.
Englund, Cristofer
Tauber, Markus
Nikolakopoulos, George
Flores, José Luis
author_role author
author2 Abella, Jaume
Borg, Markus
Donzella, Carlo
Cerquides, Jesús
Cazorla, Francisco J.
Englund, Cristofer
Tauber, Markus
Nikolakopoulos, George
Flores, José Luis
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Pérez Cerrolaza, Jon [0000-0001-6389-648X]
Abella, Jaume [0000-0001-7951-4028]
Borg, Markus [0000-0001-7879-4371]
Donzella, Carlo [0009-0002-5102-3205]
Cerquides, Jesús [0000-0002-3752-644X]
Cazorla, Francisco J. [0000-0002-3344-376X]
Englund, Cristofer [0000-0002-1043-8773]
Tauber, Markus [0000-0002-0003-2243]
Nikolakopoulos, George [0000-0003-0126-1897]
Flores, José Luis [0000-0002-5555-9712]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Computing methodologies
Artificial intelligence
Machine learning
Computer systems organization
Dependable and fault-tolerant systems and networks
Robotics
Robotic autonomy
Hardware
Safety critical systems
Functional safety
Autonomous systems
topic Computing methodologies
Artificial intelligence
Machine learning
Computer systems organization
Dependable and fault-tolerant systems and networks
Robotics
Robotic autonomy
Hardware
Safety critical systems
Functional safety
Autonomous systems
description 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.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/377985
url http://hdl.handle.net/10261/377985
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1145/3626314
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Association for Computing Machinery
publisher.none.fl_str_mv Association for Computing Machinery
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869404705698873344
score 15,811543

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