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

Authors: Clement, Philipp; Danzinger, Herbert; Veledar, Omar; Konczol, Clemens; Macher, Georg; Eichberger, Arno;

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

Abstract

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.

Keywords

In cabin measurement, HMI, trust, comfort, driver state, ADAS/AD, multi-level approach, psychophysiology, heart-rate

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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6
Top 10%
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11
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