articleIEEE Intelligent Transportation Systems MagazineJan 1, 2017Closed access

Autonomous Vehicle Safety: An Interdisciplinary Challenge

Carnegie Mellon University · Edge Case Research (United States)

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Abstract

Ensuring the safety of fully autonomous vehicles requires a multi-disciplinary approach across all the levels of functional hierarchy, from hardware fault tolerance, to resilient machine learning, to cooperating with humans driving conventional vehicles, to validating systems for operation in highly unstructured environments, to appropriate regulatory approaches. Significant open technical challenges include validating inductive learning in the face of novel environmental inputs and achieving the very high levels of dependability required for full-scale fleet deployment. However, the biggest challenge may be in creating an end-to-end design and deployment process that integrates the safety concerns of a myriad…

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650
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Authors

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Topics & keywords

Keywords
  • Software deployment
  • Dependability
  • Systems engineering
  • Process (computing)
  • Computer science
  • Fault tolerance
  • Risk analysis (engineering)
  • Engineering
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