Effect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers

Otmani, Sarah; Pébayle, Thierry; Rogé, Joceline; Muzet, Alain

doi:10.1016/j.physbeh.2005.02.021

Cited by 225 publications

(161 citation statements)

References 49 publications

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“…The intersubject correlation between EEG and performance changes on a sustained attention task is not consistent or large, especially in well-rested subjects (Belyavin and Wright, 1987;Boddy, 1971;Cajochen et al, 1999;Kornfeld and Beatty, 1977;Otmani et al, 2005;Townsend and Johnson, 1979;Williams et al, 1962). The two measures that more often correlate with worse performance are increasing theta and decreasing beta.…”

Section: Eeg-performance Relationshipmentioning

confidence: 93%

Vigilance, alertness, or sustained attention: physiological basis and measurement

Oken

Salinsky

Elsas

2006

Clinical Neurophysiology

678

463

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Vigilance is a term with varied definitions but the most common usage is sustained attention or tonic alertness. This usage of vigilance implies both the degree of arousal on the sleep-wake axis and the level of cognitive performance. There are many interacting neural and neurotransmitter systems that affect vigilance. Most studies of vigilance have relied on states where the sleep-wake state is altered, e.g. drowsiness, sleep-deprivation, and CNS-active drugs, but there are factors ranging from psychophysics to motivation that may impact vigilance. While EEG is the most commonly studied physiologic measure of vigilance, various measures of eye movement and of autonomic nervous system activity have also been used. This review paper discusses the underlying neural basis of vigilance and its assessment using physiologic tools. Since, assessment of vigilance requires assessment of cognitive function this aspect is also discussed.

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Section: Eeg-performance Relationshipmentioning

confidence: 93%

Vigilance, alertness, or sustained attention: physiological basis and measurement

Oken

Salinsky

Elsas

2006

Clinical Neurophysiology

678

463

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“…A relative band ratio of (α θ)/ β was calculated to assess fatigue levels. In addition, 10-min epochs were used as per techiqued described by (Otmani et al, 2005).…”

Section: Electroencephalographic (Eeg) Measuresmentioning

confidence: 99%

“…Subjective feeling of fatigue which combined with negative effects on performance due to time spent on cognitively demanding tasks (Meletis and Barker, 2004) can somehow affect the driving performance due to sleepiness, monotonous driving environment condition and the length of driving period as previous studies proved (Otmani et al, 2005;Papadelis et al, 2007;Zaharah and Law, 2004). A study pointed out that 37.7 percent of commercial bus drivers in Malaysia had encountered fatigue during driving where the long driving duration and awkward working hours had synergistic effect in inducing the onset of fatigue .…”

Section: Introductionmentioning

confidence: 98%

“…For instance, Dobbie (2002) determined that prolonged driving without rest can increase the fatigue level and deteriorate the driving performance. Long duration of driving, inadequate sleep and other cumulative factors caused the sleep deprived drivers to make higher number of right edge-line crossings and other errors (Otmani et al, 2005;Philip et al, 2003). Apart from fatigue factors, studies have also shown that working duration and sleep deprivation, as a result of disruption of an individual's routine sleep cycle (Philip et al, 2003;Philip, 2005;Tippayanate, 2006), clearly contributed to the deterioration of driving performance.…”

Section: Introductionmentioning

confidence: 99%

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Driving Fatigue and Performance among Occupational Drivers in Simulated Prolonged Driving

Seen¹,

Tamrin

Goh

2010

GJHS

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Introduction: Motor vehicle accident is a major problem in Malaysia. The statistics shows an increasing number of accidents (year 1997 to 2007). Fatigue and drowsiness among the drivers has been identified as one of the main reasons behind fatal crashes and injuries especially driving in long and monotonous motorway. This study aims to determine the driver's driving performance and physiological change of EEG in association with external factors such as driving condition and environmental background factors in a prolonged simulation study. Result: The study showed that time-on-task effect had significantly deteriorated drivers' alertness and impaired driving performance in an extended driving period, when certain driving condition and environmental factors considered. Conclusion: This study shows that prolong driving had significantly induced drivers' fatigue level exclusively with monotonous environment. Extended driving period deteriorated drivers' performance, revealing that time-on-task effect could possibly put drivers on a higher risk to be involved in traffic accident.

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“…A common approach when studying driver sleepiness is to use sleep deprived drivers [18][19][20]. Usually, the drivers are in an alert condition during daytime and in a sleep deprived condition during night-time.…”

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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Effect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers

Cited by 225 publications

References 49 publications

Vigilance, alertness, or sustained attention: physiological basis and measurement

Vigilance, alertness, or sustained attention: physiological basis and measurement

Driving Fatigue and Performance among Occupational Drivers in Simulated Prolonged Driving

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

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