Correlation between subjective driver state measures and psychophysiological and vehicular data in simulated driving

Elisabeth Schmidt

Ralf Decke

Ralph Rasshofer

Abstract: Advanced driver assistance systems require better knowledge of the driver’s state. This would allow for adapting driving support functions, e.g. adaptive automation. To detect the emotional and cognitive state of the driver, it is necessary to know which signals contain accurate information about the state. In this paper the results of a driving simulator study, in which different emotional and cognitive states were induced in 46 subjects via traffic scenarios, are presented. In the study, psychophysiological and vehicular data was measured in addition to subjective state estimations of the subjects. A correlation analysis confirmed that physiological data can potentially predict subjective driver states.

This publication uses Eye Tracking and Facial Expression Analysis which is fully integrated into iMotions Lab

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