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OBJECTIVE The feasibility of measuring drivers' automation trust via gaze behavior during highly automated driving was assessed with eye tracking and validated with self-reported automation trust in a driving simulator study. BACKGROUND Earlier research from other domains indicates that drivers' automation trust might be inferred from gaze behavior, such(More)
In the near future, highly automated driving will almost certainly be available in commercial vehicles. Concerning the human-machine interface in such cars, two main issues have to be addressed. First, the detrimental effects of automation have to be avoided. Second, cars should provide an interface that allows the driver to utilize the time while driving(More)
During the last years, intensive research has been conducted to make high degrees of automation available in cars. However, driver assistance systems today still need the driver to monitor the system. This will most probably change in near future, as highly automated driving becomes available. With the driver out of the control loop, this driving mode has(More)
OBJECTIVE The objective for this study was to investigate the effects of prior familiarization with takeover requests (TORs) during conditional automated driving on drivers' initial takeover performance and automation trust. BACKGROUND System-initiated TORs are one of the biggest concerns for conditional automated driving and have been studied extensively(More)
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