Driver risk factors for sleep-related crashes

Stutts, J C; Wilkins, Jean; Osberg, J. Scott; Vaughn, Bradley V.

doi:10.1016/s0001-4575(02)00007-6

Cited by 275 publications

(187 citation statements)

References 23 publications

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“…The model used seems also reliable when looking at the other factors. It provides statistical significant RCI risks associated with mobile phone, driving while drowsy, riding a two-wheeled vehicle and VKT in accordance with known results (Aarts and van Schagen 2006;Laberge-Nadeau et al 2003;Stutts et al 2003). …”

Section: Discussionsupporting

confidence: 84%

Road crash involvement and professional status: A prospective study using the French Gazel cohort

Lenguerrand¹,

Martin²,

Chiron³

et al. 2008

Accident Analysis & Prevention

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ObjectivesTo assess the influence of professional status differences on the risk of road crash involvement-RCI-(irrespective of crash severity) and to examine the underlying mechanisms by evaluating the role of users' exposure to road risk (ERR) in these differences. MethodsA total of 15 237 current and retired staff selected from the French GAZEL cohort were studied. A proportional hazard model for recurrent events was used to calculate the relative risks of RCI associated with professional status. The associations between RCI and professional status were investigated by adjusting for ERR (kilometres travelled and risk behaviour on the road).

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Section: Discussionsupporting

confidence: 84%

Road crash involvement and professional status: A prospective study using the French Gazel cohort

Lenguerrand¹,

Martin²,

Chiron³

et al. 2008

Accident Analysis & Prevention

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“…In particular an increased risk has been reported when driving during the night or early morning hours [2][3][4], for young [5,6] and for professional [7][8][9] drivers, shift workers driving home after a night shift [10,11], and for people with untreated sleep disorders [7][8][9]12]. In general, driving when sleepy impairs driving performance causing deteriorated lateral (for example keeping the position in the lane) and longitudinal control (for example keeping the speed in a stable state) of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

The severity of driver fatigue in terms of line crossing: a pilot study comparing day- and night time driving in simulator

Anund

Fors

Ahlström

2017

Eur. Transp. Res. Rev.

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Introduction The overall aim of this study is to compare daytime driving with night-time driving looking at line crossings during self-reported sleepiness and long blinks. The hypothesis is that high levels of self-reported sleepiness (KSS 9) and long blink duration (>0.15 s) will be less associated with critical events during the day-time compared to night-time. Method The study is based on data from a driving simulator experiment with 16 participants driving 150 km on a typical Swedish motorway scenario twice: once during daytime and once during night time. In total data from 6 segments of 4 km each equally distributed along the drive was averaged and included in the analysis. A Mixed Model Anova was used to test the effects on KSS, Blink Duration and Line Crossings with factors for Session (Day/Night) and Road segment (1-6), and participant as random. In addition, a logistic regression was used to identify when there is a risk for line crossings. Finally, the proportion of line crossings in relation to high KSS values and long blink durations was tested with Fisher's exact test. Results The results show no differences in the percentage of Line Crossings to the left during high levels of Karolinska Sleepiness Scale during daytime (33%) compare to night-time (40%). However, there was a significant difference between day and night time line crossings while the driver had long duration blinks (4% during daytime and 35% during night-time). Despite these results the most promising predictor of line crossings in each segment of 4 km/h was KSS with an Odds Ratio of 5.4 with a reference value at Karolinska Sleepiness Scale level 5. Conclusion In conclusion, the results do not support the hypothesis that high levels of KSS will result in more frequent line crossings at night time compared to day time. However, the result supports the hypothesis that long blink durations are associated with more line crossings when they appear during night time than during daytime.

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“…Activities involving manual and visual distraction (see Strayer et al, 2013) such as eating, interacting with the radio, texting and using a handheld cell phone represent the most common sources of distraction for drivers (Stutts et al, 2003). Since these activities often require drivers to take their hands off the steering wheel and their eyes off the road, car-manufacturers and policy-makers have recently focused their attention on voice-based technologies as a way to tackle distraction and its consequences on road safety.…”

Section: Objectivesmentioning

confidence: 99%