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Articles

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

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Pages 778-792 | Received 07 Oct 2020, Accepted 24 Jan 2021, Published online: 16 Apr 2021
 

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 analyse 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 behaviour, 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 52 min. 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.

Practitioner summary: This study offers valuable insights for the design of driver monitoring systems. The use of individual risk factors such as conscientiousness, sensation seeking, and non-verbal IQ can increase microsleep prediction. These findings may improve monitoring systems based solely on physiological signals (e.g., blinking, heart rate) and vehicle data (e.g., steering wheel movements, acceleration, cornering).

Abbreviations: ADAC: Allgemeiner Deutscher Automobil Club; ANOVA: analysis of variance; AIC: Akaike information criteria; CI: confidence interval; GPS: global positioning system; IQ: intelligence quotient; IQR: inter quartile range; KSS: Karolinska sleepiness scale; NEO-PI-R: revised NEO personality inventory; OLS: ordinary least squares; PSQI: Pittsburgh sleep quality index; SPM: standard progressive matrices; SSS: sensation seeking scale; WHO: World Health Organization

Acknowledgment

This research was part of an undergraduate project at the local University and did not receive any specific grant from funding agencies in the public or not-for-profit sectors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data and analysis script are available upon request.

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