## 3 Dataset and Experimental Setup
### Experimental Procedure  
We held two recordings for each participant. One recording took place in the morning, usually sometime from 8 a.m. to 11 a.m., and the second recording happened during the afternoon/evening, between 4 p.m. and 8 p.m. We asked all participants to schedule the morning recording as the first task in their daily routines so that they are as less drowsy as possible. On the contrary, participants were supposed to attend the afternoon recordings later in the day, usually before going home, and were specifically instructed not to nap throughout that day until the time of the recording. Our assumption is that in different times of the day we could capture variant levels of alertness and biological rhythms and that during late afternoon recordings subjects would tend to be more drowsy. This assumption is based on several past research findings that suggest that drowsy behaviors are mostly observed either during late night or during the late afternoon and that those are also the time-slots that most related driving accidents occur [5; 35; 36; 37; 38]. That is especially true for our specific target group (young adults) who were in their vast majority graduate and undergraduate students and participated in the afternoon recording after attending long hours of classes. Even though our analysis is representative of this age group, taking into account that age is a relevant factor regarding the degree in which drowsiness affects driving, we can not safely generalize our findings on elders at this point. The two recordings did not have to happen in the same day or in any specific order. Each recording lasted on average 45 min and consisted of three different sub-recordings; 'baseline', 'free-driving' and 'distractions'. During each session and for both distractions and free-driving sections, the drivers were free to drive anywhere in the virtual environment, which consisted of both city-like environments and highways with low traffic, no pedestrians and good weather conditions under day-light conditions. The 'baseline' recording consisted of two sub-parts: the 'base part' and the 'eye-tracking' part. In the 'base part' participants were asked to sit still, breath naturally and stare at the middle of the central monitor for 2.5 min. For the 'eye-tracking' part, subjects were shown a pre-recorded video with a target changing its position every few seconds. Participants were asked to follow the target with their gaze while acting naturally. This part lasted another 2.5 min. During the 'free-driving' recording, participants had to drive uninterrupted for approximately 15 min. Before the beginning of each 'free-driving' recording and after explaining the basic operation controls, we gave participants a chance to drive for a few minutes so they can familiarize themselves with the simulator. To minimize the biases introduced by  
Figure 1: The data collection setup. the relatively unfamiliar virtual-driving setup, for the purposes of this paper we used only 5 min long data segments, extracted from the last 7 min of the free-driving recording, when subjects were already used to the driving simulator. The last part was the 'distractions' recording. This recording consisted of four different sub-parts that simulated different types of common driving distractors. Bellow we describe the four different distractors that participants were exposed to during each recording session. 1. **Testing--Physical**. Participants were asked to type a small text message on their personal mobile device. The text was a predefined 8-word message and was dictated to the participant by the experiment supervisor on the fly. By using predefined texts we aimed to minimize the impact of cognitive effort that subjects had to put when texting and focus more on the physical disengagement from driving. Nonetheless, texting combines all three distraction classes defined by NHTSA and the CDC, which are Manual, Visual and Cognitive.