Fatigued and drowsy driving: A survey of attitudes, opinions and behaviors

Vanlaar, Ward; Simpson, H M; Mayhew, D R; Robertson, Robyn

doi:10.1016/j.jsr.2007.12.007

Cited by 139 publications

(69 citation statements)

References 15 publications

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“…It is still seen as one of the most important causes. However, research has shown other factors that are equally important (Vanlaar, et al 2007). In the first place, fatigue is a lack of sleep.…”

Section: Causes Of Fatiguementioning

confidence: 99%

“…Working time is, after all, one of the basic economic inputs to production and transport. Consequently, the safety argument too often has been brushed aside in the face of a commercial logic that requires flexible and on time transportation of goods and passengers, in many cases spanning the 24-hour cycle (Vanlaar et al, 2007). The customer, the consumer and new modes of production require this -and in some respects, the working conditions of many drivers have become harsher and more demanding over the last 30 years.…”

Section: Introductionmentioning

confidence: 99%

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Efficacy of Drivers’ Fatigue on Road Accident in Selected Southwestern States of Nigeria

Aworemi¹,

adegoke

Oyedokun³

et al. 2010

IBR

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The study examines the causes and effects of driver's fatigue on road crashes in south-western Nigeria. The study was carried out in the administrative seats of Oyo and Ogun states of Nigeria with the aid of structured questionnaires which were administered on 325 respondents in the study area using simple random sampling approach. The collected data were analysed using multiple regression model.The study revealed that, duration of driving, stress, sleep deficit, alcohol contributed significantly to the causes of driver's fatigue both at 5% and 10% significant levels.It was concluded that, the safest option is for driver to avoid driving when sleepy on when they are ill or taking medication. And that it is pertinent on them to plan their journeys in such a way that it will include regular rest, break of at least 15 minutes at every two hours.

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Section: Causes Of Fatiguementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficacy of Drivers’ Fatigue on Road Accident in Selected Southwestern States of Nigeria

Aworemi¹,

adegoke

Oyedokun³

et al. 2010

IBR

View full text Add to dashboard Cite

show abstract

“…Not surprisingly, a link was found between various physical and psychological fatigue factors and the likelihood of road traffic crashes among drivers. There is already evidence suggesting that the problem of fatigued and drowsy driving is an important contributor to road traffic crashes (Vanlaar, Simpson, Mayhew & Robertson, 2008;Radun & Radun, 2009). In a Canadian study using a representative sample of 750 Ontario drivers, more than half of the respondents admitted occasionally driving while fatigued or drowsy, with two in 10 admitting that they had fallen asleep or nodded off while driving during the previous year (Vanlaar et al, 2008).…”

Section: Supporting the Un Decade Of Action For Road Safety 2011-2020mentioning

confidence: 99%

Supporting the UN Decade of Action for Road Safety 2011–2020

Forjuoh¹

2010

International Journal of Injury Control and Safety Promotion

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“…Fatigue symptoms include increased feelings of tiredness and reduced alertness that results in decreased reaction time to respond to changes in conditions and to perform a task. Fatigue is known to lead to driving related traffic accidents, injuries and fatalities [1]. As a result, there is a need for an automatic detection and monitoring of driver related fatigue.…”

Section: Introductionmentioning

confidence: 99%

Enhancing accuracy of mental fatigue classification using advanced computational intelligence in an electroencephalography system

Chai

Tran

Craig

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-A system using electroencephalography (EEG) signals could enhance the detection of mental fatigue while driving a vehicle. This paper examines the classification between fatigue and alert states using an autoregressive (AR) model-based power spectral density (PSD) as the features extraction method and fuzzy particle swarm optimization with cross mutated of artificial neural network (FPSOCM-ANN) as the classification method. Using 32-EEG channels, results indicated an improved overall specificity from 76.99% to 82.02%, an improved sensitivity from 74.92 to 78.99% and an improved accuracy from 75.95% to 80.51% when compared to previous studies. The classification using fewer EEG channels, with eleven frontal sites resulted in 77.52% for specificity, 73.78% for sensitivity and 75.65% accuracy being achieved. For ergonomic reasons, the configuration with fewer EEG channels will enhance capacity to monitor fatigue as there is less set-up time required.

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Fatigued and drowsy driving: A survey of attitudes, opinions and behaviors

Cited by 139 publications

References 15 publications

Efficacy of Drivers’ Fatigue on Road Accident in Selected Southwestern States of Nigeria

Efficacy of Drivers’ Fatigue on Road Accident in Selected Southwestern States of Nigeria

Supporting the UN Decade of Action for Road Safety 2011–2020

Enhancing accuracy of mental fatigue classification using advanced computational intelligence in an electroencephalography system

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