Leveraging Answer Set Programming for Continuous Monitoring, Fault Detection, and Explanation of Automated and Autonomous Driving Systems

KLKlampfl, LorenzWFWotawa, Franz

Graz University of Technology · Fraunhofer Institute for Cognitive Systems

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Abstract

Recent advancements in automated and autonomous driving systems have facilitated their integration into modern vehicles, enabling them to accurately perceive their surroundings and support or even fully undertake complex driving tasks. Given the complexity and unpredictable nature of driving environments and traffic situations, ensuring the correct behavior of such systems is essential to prevent hazardous situations, increase user acceptance, and avoid human harm. However, the increased complexity of these systems and the extensive search space of possible scenarios introduce significant challenges to testing and real-time fault management. Hence, besides rigorous testing during the development phase, there…

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440
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11.49
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100%
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Authors

2
  • KL
    Klampfl, LorenzCorresponding

    Graz University of Technology, Fraunhofer Institute for Cognitive Systems

  • WF
    Wotawa, Franz

    Graz University of Technology, Fraunhofer Institute for Cognitive Systems

Topics & keywords

Keywords
  • Scalability
  • Standardization
  • RSS
  • Computer science
  • Field (mathematics)
  • Automotive industry
  • Vehicle safety
  • Risk analysis (engineering)
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