: Drowsy driving is a major issue in road safety. In this paper, we propose a description of an experimental data collection to develop a drowsiness detection model. The objective of this data collection was mainly to gather physiological data of individuals in simulated driving situations. We designed a realistically annoying scenario to induce fatigue while staying close to real driving conditions. The experiment was run on an augmented reality platform called CAVE. The need for contextualization came early in the design of the experiment. Therefore, in addition to physiological data, we added much more data sources, from driving habits to driving behaviour in addition to self-assessment of fatigue levels and the gold standard (EEG). As a result, this experience helped us create a data set of physiological data completed by elements of context and driving behaviour. Thus allowing us to perform a very rich analysis of these physiological data.

Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving

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Physiological Data Recording in VR Simulator for Sleepiness Detection During Driving