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Abstract
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OBJECTIVE
We studied how system descriptions of conditionally driving vehicles (SAE International, 2014) influenced drivers' knowledge/mental model, trust, and acceptance.
Background
The increasing proliferation of assisted and conditionally automated vehicles urge a proper understanding of knowledge about, acceptance, and trust in the system. Up to now there is a lack of studies for automated systems and system knowledge which will be served in this study.
Methods
We provided N = 120 participants with correct, incomplete, and incorrect descriptions about the conditionally automated vehicle. Thereafter, they watched five video clips with different situations where the driver has to resume control of the driving task or do nothing. Immediately before such a situation, the videos were frozen and knowledge questions were asked according to the SAGAT method (Endsley, 1995). Further, trust and acceptance before and after watching videos were measured.
Results
The knowledge questions differed in groups for level 2 (comprehension) and level 3 (projection) of situation awareness (SA). The difference is significant for the groups in level 2 situation awareness (comprehension) with correct vs. incorrect and incomplete vs. incorrect descriptions. The overall trust in their answer behavior was the highest for the group with the correct description followed by the group with the incomplete description. Furthermore, trust and acceptance did not differ between groups and even not between measurement time (before vs. after watching videos).
Conclusion
An incorrect preliminary system description leads to an incorrect mental model which in turn leads to incorrect comprehension and projection of traffic situations. This effect can be minimized over time, but is relevant to the safety of the driver.
Application
Accurate system descriptions might reduce the number and the gravity of most accidents with conditionally automated systems in driving. Moreover, repeated exposure will reduce the possibility of accidents.
Language: en |