Sökning: id:"swepub:oai:DiVA.org:lnu-100985" >
Software Verificati...
Software Verification and Validation of Safe Autonomous Cars : A Systematic Literature Review
-
- Rajabli, Nijat (författare)
- Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Linnaeus University, Sweden
-
- Flammini, Francesco, Senior Lecturer, 1978- (författare)
- Mälardalens högskola,Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Mälardalen University, Sweden,Innovation och produktrealisering,Linnaeus University, Sweden
-
- Nardone, Roberto (författare)
- Mediterranean Univ Reggio Calabria, Italy,University of Reggio, Calabria, Italy
-
visa fler...
-
- Vittorini, Valeria (författare)
- Univ Napoli Federico II, Italy,University of Napoli Federico II, 80125 Naples, Italy
-
visa färre...
-
(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
-
Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 9, s. 4797-4819
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://lnu.diva-por... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
https://urn.kb.se/re...
-
visa färre...
Abstract
Ämnesord
Stäng
- Autonomous, or self-driving, cars are emerging as the solution to several problems primarily caused by humans on roads, such as accidents and traffic congestion. However, those benefits come with great challenges in the verification and validation (V&V) for safety assessment. In fact, due to the possibly unpredictable nature of Artificial Intelligence (AI), its use in autonomous cars creates concerns that need to be addressed using appropriate V&V processes that can address trustworthy AI and safe autonomy. In this study, the relevant research literature in recent years has been systematically reviewed and classified in order to investigate the state-of-the-art in the software V&V of autonomous cars. By appropriate criteria, a subset of primary studies has been selected for more in-depth analysis. The first part of the review addresses certification issues against reference standards, challenges in assessing machine learning, as well as general V&V methodologies. The second part investigates more specific approaches, including simulation environments and mutation testing, corner cases and adversarial examples, fault injection, software safety cages, techniques for cyber-physical systems, and formal methods. Relevant approaches and related tools have been discussed and compared in order to highlight open issues and opportunities.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)
Nyckelord
- Advanced driver assistance systems
- automotive engineering
- autonomous vehicles
- cyber-physical systems
- formal verification
- intelligent vehicles
- machine learning
- system testing
- system validation
- vehicle safety
- Data- och informationsvetenskap
- Computer and Information Sciences Computer Science
Publikations- och innehållstyp
- ref (ämneskategori)
- for (ämneskategori)
Hitta via bibliotek
Till lärosätets databas