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Abstract: Few studies have examined the extent of driver sleepiness during a long distance morning trip. Sleepiness at this time may be high because of night work, waking early to commence work or travel, sleep disorders and the monotony of driving long distances. The objective of this study was to estimate the prevalence of chronic sleepiness (Epworth sleepiness score ≥10) and sleep restriction (≤5h) in a sample of 649 drivers. Participants driving between 08:00 and 10:00 on three highways in regional Australia participated in a telephone interview. Approximately 18% of drivers reported chronic sleepiness. The proportions of night workers (NW) and non-night workers (NNW) with chronic sleepiness were not significantly different but males reported a significantly greater proportion of chronic sleepiness than females. The NW group had a significantly greater proportion of drivers with ≤5h of sleep in the previous 24 and 48h, fewer nights of full sleep (≤4), acute sleepiness and longer weekly work hours. The NW group reported driving a significantly longer distance at Time 1 (Mean=140.29±72.17km, versus 117.55±89.74km) and an additional longer distance to complete the journey (Mean=89.33±95.23km, versus 64.77±94.07km). The high proportions of sleep restriction and acute sleepiness among the NW group, and the amount of chronic sleepiness in the NW and NNW groups reported during a long distance morning trip may be of concern for driver safety. [Copyright &y& Elsevier]

Abstract: A moving base driving simulator experiment was carried out in order to investigate the effects of milled rumble strips on driver fatigue. There were rumble strips both at the edge line and centre line. Four different physical designs of milled rumble strips (yielding noise values from 1.5 to 16dBA) and two placements on shoulder were used in the experiment. Sound and vibrations from real milled rumble strips were reproduced in the simulator. In total 35 regular shift workers drove during the morning hours after a full night shift. The main results showed an increase in sleepiness indicators (EEG alpha/theta activity, eye closure duration, standard deviation of lateral position, subjective sleepiness) from start to before hitting the rumble strip, an alerting effect in most parameters (not subjective sleepiness) after hitting the strip. The alertness enhancing effect was, however, short and the sleepiness signs returned 5min after the rumble strip hit. Essentially no effects were seen due to type of strip. It was concluded that various aspects of sleepiness are increased before hitting a rumble strip and that the effect is very short-lived. Type of strip, as used in the present study did not have any effect. [Copyright &y& Elsevier]

Abstract: Cox proportional hazard models were used to study relationships between the event that a driver is leaving the lane caused by sleepiness and different indicators of sleepiness. In order to elucidate different indicators’ performance, five different models developed by Cox proportional hazard on a data set from a simulator study were used. The models consisted of physiological indicators and indicators from driving data both as stand alone and in combination. The different models were compared on two different data sets by means of sensitivity and specificity and the models’ ability to predict lane departure was studied. In conclusion, a combination of blink indicators based on the ratio between blink amplitude and peak closing velocity of eyelid (A/PCV) (or blink amplitude and peak opening velocity of eyelid (A/POV)), standard deviation of lateral position and standard deviation of lateral acceleration relative road (ddy) was the most sensitive approach with sensitivity 0.80. This is also supported by the fact that driving data only shows the impairment of driving performance while blink data have a closer relation to sleepiness. Thus, an effective sleepiness warning system may be based on a combination of lane variability measures and variables related to eye movements (particularly slow eye closure) in order to have both high sensitivity (many correct warnings) and acceptable specificity (few false alarms). [Copyright &y& Elsevier]

Abstract: Young drivers are over-represented in nighttime traffic accidents and several studies have suggested that many accidents are associated with elevated sleepiness levels. It has been suggested that there may be a connection between lowered wake capacity and functional sensory motor skills on the one hand and sleep deprivation at the circadian low in young drivers on the other. Performance during a 45/min evening and night drive among young (n =10, age range 18–24 years) and elderly (n =10, age range 55–64 years) subjects was studied using a moving base driving simulator. EEG was measured continuously. Every 5min, subjects were rated on the Karolinska Sleepiness Scale (KSS). Saliva cortisol was assessed before and after each drive. The results showed that sleepiness increased across each drive and was higher among young drivers at night. Relative EEG power increased among older drivers for frequencies of 10–16Hz. The sigma 1 frequency band (12–14Hz) proved particularly sensitive to sustained driving, and was elevated among subjects in the elderly group. Cortisol levels before and after the evening and night drive showed higher mean levels for elderly subjects. The present study has demonstrated that young drivers were more sleepy while driving at night. The effects could represent a mobilization of effort and a reorganization of brain firing pattern among older subjects, possibly reflecting better ability and effort to resist sleepiness. [Copyright &y& Elsevier]

Airline pilots’ sleep and on-duty alertness are important focus areas in commercial aviation. Until now, studies pertaining to this topic have mainly focused on specific characteristics of flights and thus a comprehensive picture of the matter is not well established. In addition, research knowledge of what airline pilots actually do to maintain their alertness while being on duty is scarce. To address these gaps in research knowledge, we conducted a field study on a representative sample of the airline pilots of a medium-sized airline. The sample consisted of 90 pilots, of whom 30 flew long-haul (LH) routes, 30 short-haul (SH) routes, and 30 flew both. A total of 86 pilots completed the measurements that lasted for almost two months per pilot. The measurements resulted in a total of 965 flight duty periods (FDPs) including SH flights and 627 FDPs including LH flights. During the measurement periods, sleep was measured by a diary and actigraphs, on-duty alertness by the Karolinska Sleepiness Scale (KSS) in all flight phases, and on-duty alertness management strategies by the diary. Results showed that SH and LH FDPs covering the whole domicile night (00:00–06:00 at home base) were most consistently associated with reduced sleep-wake ratio and subjective alertness. Approximately every 3rd FDP falling into this category involved a reduced sleep-wake ratio (1:3 or lower) and every 2nd a reduced level of subjective alertness (KSS rating 8–9 in at least one flight phase). The corresponding frequencies for the SH and LH FDPs that partly covered the domicile night were every 10th and every 5th FDP and for the pure non-night FDPs every 30th and every 36th FDP, respectively. The results also showed that the pilots tended to increase the use of effective on-duty alertness management strategies (consuming alertness-promoting products and taking strategic naps) in connection with the FDPs that overlapped the domicile night. Finally, the results showed that the frequency of flights involving reduced subjective alertness depended on how alertness was assessed. If it was assessed solely in the flight phase just before starting the landing procedures (top of descent) the phenomenon was less frequent than if the preceding cruise phase was also taken into account. Our results suggest that FDPs covering the whole domicile night should be prioritised over the other FDPs in fatigue management, regardless of whether an FDP is a short-haul or a long-haul. In addition, the identification of fatigue in flight operations requires one to assess pilots’ alertness across all flight phases, not only at ToD. Due to limitations in our data, these conclusions can, however, be generalise to only LH FDPs during which pilots can be expected to be well acclimatised to the local time at their home base and SH night FDPs that include at least 3 h of flying in the cruise phase. [ABSTRACT FROM AUTHOR]

Abstract: Sleepiness has been identified as one of the most important factors contributing to road crashes. However, almost all work on the detailed changes in behavior and physiology leading up to sleep related crashes has been carried out in driving simulators. It is not clear, however, to what extent simulator results can be generalized to real driving. This study compared real driving with driving in a high fidelity, moving base, driving simulator with respect to driving performance, sleep related physiology (using electroencephalography and electrooculography) and subjective sleepiness during night and day driving for 10 participants. The real road was emulated in the simulator. The results show that the simulator was associated with higher levels of subjective and physiological sleepiness than real driving. However, both for real and simulated driving, the response to night driving appears to be rather similar for subjective sleepiness and sleep physiology. Lateral variability was more responsive to night driving in the simulator, while real driving at night involved a movement to the left in the lane and a reduction of speed, both of which effects were absent in the simulator. It was concluded that the relative validity of simulators is acceptable for many variables, but that in absolute terms simulators cause higher sleepiness levels than real driving. Thus, generalizations from simulators to real driving must be made with great caution. [Copyright &y& Elsevier]

Abstract: Sleepiness is related to factors such as the time of day, the time since awakening and the duration of prior sleep. The present study investigated whether actual road crashes could be predicted from a mathematical model based on these three factors (the Sleep/Wake Predictor—SWP). Data were derived from a population-based case-control study of serious injury crashes. Data on accident time (or control sampling time) and start and end of prior sleep were entered into the model (blind). The predicted sleepiness values were used in logistic regressions. The results showed a highly significant odds ratio (OR)=1.72 (confidence interval=1.41–2.09) for each incremental step of sleepiness on the output sleepiness scale (nine steps). There was also a significant interaction with blood alcohol level, showing high OR values for high sleepiness levels and alcohol levels above 50mg% (0.05g/dl). It was concluded that the model is a good predictor of road crashes beyond that of alcohol level, and that interaction between the two carries a very high risk. [Copyright &y& Elsevier]