Cognitive analysis of the drivers sleepiness in different road simulated scenarios

Driver drowsiness is a major contributor to road traffic crashes, yet most laboratory research relies on artificially induced sleep deprivation, revealing little about how alertness naturally fluctuates during ordinary driving. This thesis investigates driver sleepiness under normal, non-sleep-deprived conditions, comparing two simulated driving scenarios differing in traffic density: with-traffic (three-lane highway, light-to-moderate traffic, 130 km/h) and without-traffic (same route and speed limit, no surrounding vehicles). Twenty-five participants completed both scenarios in a fixed order on the VI-grade COMPACT simulator, wearing Tobii Pro Glasses 3 as the primary instrument; a Mindtooth EEG headset was also worn as a secondary system, though EEG data are not analyzed here. Four core Tobii metrics were examined — fixation duration, pupil diameter, saccade rate, and saccadic velocity alongside gaze allocation across nine lane-based Areas of Interest and a single-item subjective sleepiness rating (1–10) before and after the session. Three of the four physiological metrics moved as expected under increasing sleepiness without traffic: fixation duration was longer (934 vs. 816 ms), pupil diameter smaller (3.17 vs. 3.27 mm), and saccade rate lower (43.9 vs. 53.0 per minute). Saccadic velocity showed no meaningful difference. Gaze shifted away from the left lane (34.8% to 22.4% of fixation duration) toward the middle and right lanes, consistently at the individual level. Self-reported sleepiness also rose modestly over the session (3.84 to 4.52 on a 10-point scale). All comparisons are descriptive and visual rather than statistically tested, and the fixed scenario order confounds differences with time-on-task; both are stated as scope decisions. Results are broadly consistent with low-traffic, monotonous driving being associated with reduced arousal even over a short session, with implications for road design and future in-vehicle drowsiness-detection systems.