Applying neural network analysis on heart rate variability data to assess driver fatigue

Driver fatigue is a major cause of road accidents and has implications for road safety. This review discusses the concepts of fatigue and provides a summary on psychophysiological associations with driver fatigue. A variety of psychophysiological parameters have been used in previous research as indicators of fatigue, with electroencephalography perhaps being the most promising. Most research found changes in theta and delta activity to be strongly linked to transition to fatigue. Therefore, monitoring electroencephalography during driver fatigue may be a promising variable for use in fatigue countermeasure devices. The review also identified anxiety and mood states as factors that may possibly affect driver fatigue. Furthermore, personality and temperament may also influence fatigue. Given the above, understanding the psychology of fatigue may lead to better fatigue management. The findings from this review are discussed in the light of directions for future studies and for the development of fatigue countermeasures.

To assess the incidence, time of day, and driver morbidity associated with vehicle accidents where the most likely cause was the driver falling asleep at the wheel. Two surveys were undertaken, in southwest England and the midlands, by using police databases or on the spot interviews. Drivers involved in 679 sleep related vehicle accidents. Of all vehicle accidents to which the police were summoned, sleep related vehicle accidents comprised 16% on major roads in southwest England, and over 20% on midland motorways. During the 24 hour period there were three major peaks: at around 0200, 0600, and 1600. About half these drivers were men under 30 years; few such accidents involved women. Sleep related vehicle accidents are largely dependent on the time of day and account for a considerable proportion of vehicle accidents, especially those on motorways and other monotonous roads. As there are no norms for the United Kingdom on road use by age and sex for time of day with which to compare these data, we cannot determine what the hourly exposure v risk factors are for these subgroups. The findings are in close agreement with those from other countries.