Towards better microsleep predictions in fatigued drivers: Exploring benefits of personality traits and IQ

Abstract

Fatigued driving is one of the main contributors to road traffic accidents. Poor sleep quality and lack of sleep negatively affect driving performance, and extreme states of fatigue can cause microsleep (i.e. short episodes of sleep with complete loss of awareness). Driver monitoring systems analyze biosignals (e.g. gaze, blinking, heart rate) and vehicle data (e.g. steering wheel movements, lane holding, acceleration) to detect states of fatigue and prevent accidents. We argue that inter-individual differences in personality, sensation seeking behavior, and intelligence could improve microsleep prediction, in addition to sleepiness. We tested 144 male participants in a supervised driving track after 27 hours of sleep deprivation. More than 74% of drivers experienced microsleep, after an average driving time of 51:31min. Overall, prediction models for microsleep vulnerability and driving time before microsleep were significantly improved by conscientiousness, sensation seeking and non-verbal IQ, in addition to situational sleepiness, as individual risk factors.

Guillermo Hidalgo Gadea

PhD Student in Psychology

My research interests include embodied cognition, animal behavior and machine learning.