Christian Braunagel

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This paper presents a novel approach to automated recognition of the driver's activity, which is a crucial factor for determining the take-over readiness in conditionally autonomous driving scenarios. Therefore, an architecture based on head-and eye-tracking data is introduced in this study and several features are analyzed. The proposed approach is(More)
This paper reports a study that investigated driver behavior between manual and conditionally automated driving and behavioral progress in a long conditionally automated phase. The goal was to evaluate a novel framework of an assistant system for driver state monitoring during conditionally automated driving. The framework was based on the analysis of the(More)
Algorithms for eye movement classification are separated into threshold-based and probabilistic methods. While the parameters of static threshold-based algorithms usually need to be chosen for the particular task (task-individual), the probabilistic methods were introduced to meet the challenge of adjusting automatically to multiple individuals with(More)
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