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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
  • Forskningsöversikt (refereegranskat)
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

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