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      Autonomous Vehicles: Disengagements, Accidents and Reaction Times

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      PLoS ONE
      Public Library of Science

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          Abstract

          Autonomous vehicles are being viewed with scepticism in their ability to improve safety and the driving experience. A critical issue with automated driving at this stage of its development is that it is not yet reliable and safe. When automated driving fails, or is limited, the autonomous mode disengages and the drivers are expected to resume manual driving. For this transition to occur safely, it is imperative that drivers react in an appropriate and timely manner. Recent data released from the California trials provide compelling insights into the current factors influencing disengagements of autonomous mode. Here we show that the number of accidents observed has a significantly high correlation with the autonomous miles travelled. The reaction times to take control of the vehicle in the event of a disengagement was found to have a stable distribution across different companies at 0.83 seconds on average. However, there were differences observed in reaction times based on the type of disengagements, type of roadway and autonomous miles travelled. Lack of trust caused by the exposure to automated disengagements was found to increase the likelihood to take control of the vehicle manually. Further, with increased vehicle miles travelled the reaction times were found to increase, which suggests an increased level of trust with more vehicle miles travelled. We believe that this research would provide insurers, planners, traffic management officials and engineers fundamental insights into trust and reaction times that would help them design and engineer their systems.

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          Author and article information

          Contributors
          Role: Editor
          Journal
          PLoS One
          PLoS ONE
          plos
          plosone
          PLoS ONE
          Public Library of Science (San Francisco, CA USA )
          1932-6203
          20 December 2016
          2016
          : 11
          : 12
          : e0168054
          Affiliations
          [001]Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, UNSW Australia, Sydney New South Wales, Australia
          Beihang University, CHINA
          Author notes

          Competing Interests: The authors have declared that no competing interests exist.

          • Conceptualization: VVD SC.

          • Data curation: VVD SC.

          • Formal analysis: VVD SC.

          • Funding acquisition: VVD.

          • Methodology: VVD.

          • Supervision: VVD.

          • Writing – original draft: VVD SC DJN.

          • Writing – review & editing: VVD SC DJN.

          Article
          PONE-D-16-34293
          10.1371/journal.pone.0168054
          5173339
          27997566
          4dfc62a3-d285-4f19-866b-798c45632009
          © 2016 Dixit et al

          This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

          History
          : 26 August 2016
          : 25 November 2016
          Page count
          Figures: 6, Tables: 3, Pages: 14
          Funding
          The author(s) received no specific funding for this work.
          Categories
          Research Article
          Biology and Life Sciences
          Neuroscience
          Cognitive Science
          Cognitive Neuroscience
          Reaction Time
          Biology and Life Sciences
          Neuroscience
          Cognitive Neuroscience
          Reaction Time
          Engineering and Technology
          Civil Engineering
          Transportation Infrastructure
          Roads
          Engineering and Technology
          Transportation
          Transportation Infrastructure
          Roads
          Engineering and Technology
          Control Engineering
          Automation
          Physical Sciences
          Physics
          Classical Mechanics
          Damage Mechanics
          Physical Sciences
          Mathematics
          Probability Theory
          Probability Density
          Engineering and Technology
          Civil Engineering
          Transportation Infrastructure
          Engineering and Technology
          Transportation
          Transportation Infrastructure
          People and places
          Geographical locations
          North America
          United States
          California
          Biology and Life Sciences
          Physiology
          Sensory Physiology
          Somatosensory System
          Pain Sensation
          Medicine and Health Sciences
          Physiology
          Sensory Physiology
          Somatosensory System
          Pain Sensation
          Biology and Life Sciences
          Neuroscience
          Sensory Systems
          Somatosensory System
          Pain Sensation
          Custom metadata
          The data were obtained from the California Department of Motor Vehicles (DMV). The data are publicly available from the DMV website: https://www.dmv.ca.gov/portal/dmv/detail/vr/autonomous/testing.

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          Uncategorized

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