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Measuring trust in automated driving using a multi-level approach to human factors

Clement, Philipp; Danzinger, Herbert; Veledar, Omar; Koenczoel, Clemens; Macher, Georg; Eichberger, Arno

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Clement, Philipp</dc:creator>
  <dc:creator>Danzinger, Herbert</dc:creator>
  <dc:creator>Veledar, Omar</dc:creator>
  <dc:creator>Koenczoel, Clemens</dc:creator>
  <dc:creator>Macher, Georg</dc:creator>
  <dc:creator>Eichberger, Arno</dc:creator>
  <dc:description>As the driving is shifting towards automation, the maximization of related benefits would profit from improved user acceptance of the new technology. Studies suggest a strong connection between acceptance and trust in technical solutions. We investigate the improvement of user trust to driving automation through demonstrations that carried on a sophisticated driving simulator. The study correlates subjective data with objective psycho-physiological measurements. The multi-factorial and multivariate analysis of variance investigates the influence of learning effects and pre-experience with ADAS on trust. Results show improvement in trust through user interaction with a human-machine interface of the demonstrated AD system, hence illustrating the relevance of human-centered development processes. The conclusion is supported by the observation of driver cardiac signals.</dc:description>
  <dc:relation>info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Research and Innovation action/871385/</dc:relation>
  <dc:subject>In cabin measurement, HMI, trust, comfort, driver state, ADAS/AD, multi-level approach, psychophysiology, heart-rate</dc:subject>
  <dc:title>Measuring trust in automated driving using a multi-level approach to human factors</dc:title>
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