Reliability of simulator driving tool for evaluation of sleepiness,fatigue and driving performance

Study objective

To compare the impact of extended wakefulness (i.e., sleepiness) and prolonged driving (i.e., fatigue) at the wheel in simulated versus real-life driving conditions.

Design

Participants drove on an INRETS-MSIS SIM2 simulator in a research laboratory or an open French highway during 3 nocturnal driving sessions. A dose–response design of duration of nocturnal driving was used: a 2 h short driving session (3–5 AM), a 4 h intermediate driving session (1–5 AM) and an 8 h long driving session (9 PM–5 AM).

Participants

Two groups of healthy male drivers (20 for simulated driving and 14 drivers for real driving; mean age ± SD = 22.3 ± 1.6 years), free of sleep disorders.

Measurements

Number of inappropriate line crossings, self-rated fatigue and sleepiness were recorded in the last hour of driving sessions to control the effects of prior waking time and time of day.

Results

Compared to the daytime reference session, both simulated and real driving performance were affected by a short nocturnal driving session (P < .05 and P < .001, respectively). Extension of nocturnal driving duration affected simulated performance nonlinearly and more severely than that of real driving (P < .001).Compared to the daytime reference session, short nocturnal simulated and real driving sessions increased self-perceived fatigue and sleepiness. Real and simulated driving conditions had an identical impact on fatigue and sleepiness during extended periods of nocturnal driving.

Conclusions

In healthy subjects, the INRETS-MSIS SIM2 simulator appropriately measures driving impairment in terms of inappropriate line crossings related to extended wakefulness but has limitations to measure the impact of extended driving on drivers’ performance.     

The distribution of sleepiness,sleep and work hours during a long distance morning trip: A comparison between night- and non-night workers

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 (≤5 h) 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 ≤5 h of sleep in the previous 24 and 48 h, 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 ± 72.17 km, versus 117.55 ± 89.74 km) and an additional longer distance to complete the journey (Mean = 89.33 ± 95.23 km, versus 64.77 ± 94.07 km). 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.     

Sleepiness in professional drivers: effect of age and time of day

The effect of age and time of day on objective and subjective sleepiness in professional drivers was investigated during a simulated driving task. Thirty-six young and middle-aged professional males drivers, free from any sleep disorder, took part in two simulated driving sessions; one carried out in the afternoon (between 2 and 4 p.m.) the other in the evening (between 11 p.m. and 1 a.m.). Half of each age group drove in a low traffic condition while the second half drove in a heavy traffic condition. Throughout the driving task, subjects' electroencephalogram and Karolinska sleepiness scale (KSS) scores were recorded. Visual analog scales measuring alertness and sleepiness levels were also completed before and after the driving. After each session, subjects filled out the NASA-TLX questionnaire and were asked if they had felt sleepy during the driving. Young professional drivers presented a significant decrease in alertness (raise of the spectral power in the alpha band) in the low traffic condition and a strong propensity to sleep during the evening test in contrast to middle-aged professional drivers.     

Naturalistic field study of the restart break in US commercial motor vehicle drivers: Truck driving,sleep, and fatigue

Commercial motor vehicle (CMV) drivers in the US may start a new duty cycle after taking a 34-h restart break. A restart break provides an opportunity for sleep recuperation to help prevent the build-up of fatigue across duty cycles. However, the effectiveness of a restart break may depend on its timing, and on how many nighttime opportunities for sleep it contains. For daytime drivers, a 34-h restart break automatically includes two nighttime periods. For nighttime drivers, who are arguably at increased risk of fatigue, a 34-h restart break contains only one nighttime period. To what extent this is relevant for fatigue depends in part on whether nighttime drivers revert back to a nighttime-oriented sleep schedule during the restart break. We conducted a naturalistic field study with 106 CMV drivers working their normal schedules and performing their normal duties. These drivers were studied during two duty cycles and during the intervening restart break. They provided a total of 1260 days of data and drove a total of 414,937 miles during the study. Their duty logs were used to identify the periods when they were on duty and when they were driving and to determine their duty cycles and restart breaks. Sleep/wake patterns were measured continuously by means of wrist actigraphy. Fatigue was assessed three times per day by means of a brief psychomotor vigilance test (PVT-B) and a subjective sleepiness scale. Data from a truck-based lane tracking and data acquisition system were used to compute lane deviation (variability in lateral lane position). Statistical analyses focused on 24-h patterns of duty, driving, sleep, PVT-B performance, subjective sleepiness, and lane deviation. Duty cycles preceded by a restart break containing only one nighttime period (defined as 01:00–05:00) were compared with duty cycles preceded by a restart break containing more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers showed more nighttime-oriented duty and driving patterns and more daytime-oriented sleep patterns than during duty cycles preceded by a restart break with more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers also experienced more lapses of attention on the PVT-B and increased lane deviation at night, and they reported greater subjective sleepiness. Importantly, drivers exhibited a predominantly nighttime-oriented sleep schedule during the restart break, regardless of whether the restart break contained only one or more than one nighttime period. Consistent with findings in laboratory-based studies of the restart break, the results of this naturalistic field study indicate that having at least two nighttime periods in the restart break provides greater opportunity for sleep recuperation and helps to mitigate fatigue.     

Subjective and predicted sleepiness while driving in young adults

Sleepiness is a significant contributor to car crashes and sleepiness related crashes have higher mortality and morbidity than other crashes. Young adult drivers are at particular risk for sleepiness related car crashes. It has been suggested that this is because young adults are typically sleepier than older adults because of chronic sleep loss, and more often drive at times of increased risk of acute sleepiness. This prospective study aimed to determine the relationship between predicted and perceived sleepiness while driving in 47 young-adult drivers over a 4-week period. Sleepiness levels were predicted by a model incorporating known circadian and sleep factors influencing alertness, and compared to subjective ratings of sleepiness during 2518 driving episodes. Results suggested that young drivers frequently drive while at risk of crashing, at times of predicted sleepiness (>7% of episodes) and at times they felt themselves to be sleepy (>23% of episodes). A significant relationship was found between perceived and predicted estimates of sleepiness. However, the participants nonetheless drove at these times. The results of this study may help preventative programs to specifically target factors leading to increased sleepiness when driving (particularly time of day), and to focus interventions to stop young adults from driving when they feel sleepy.     

Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation

Drivers are not always aware that they are becoming impaired as a result of sleepiness. Using specific symptoms of sleepiness might assist with recognition of drowsiness related impairment and help drivers judge whether they are safe to drive a vehicle, however this has not been evaluated. In this study, 20 healthy volunteer professional drivers completed two randomized sessions in the laboratory – one under 24 h of acute sleep deprivation, and one with alcohol. The Psychomotor Vigilance Task (PVT) and a 30 min simulated driving task (AusEdTM) were performed every 3–4 h in the sleep deprivation session, and at a BAC of 0.00% and 0.05% in the alcohol session, while electroencephalography (EEG) and eye movements were recorded. After each test session, drivers completed the Karolinska Sleepiness Scale (KSS) and the Sleepiness Symptoms Questionnaire (SSQ), which includes eight specific sleepiness and driving performance symptoms. A second baseline session was completed on a separate day by the professional drivers and in an additional 20 non-professional drivers for test–retest reliability. There was moderate test–retest agreement on the SSQ (r = 0.59). Significant correlations were identified between individual sleepiness symptoms and the KSS score (r values 0.50–0.74, p < 0.01 for all symptoms). The frequency of all SSQ items increased during sleep deprivation (χ² values of 28.4–80.2, p < 0.01 for all symptoms) and symptoms were related to increased subjective sleepiness and performance deterioration. The symptoms “struggling to keep your eyes open”, “difficulty maintaining correct speed”, “reactions were slow” and “head dropping down” were most closely related to increased alpha and theta activity on EEG (r values 0.49–0.59, p < 0.001) and “nodding off to sleep” and “struggling to keep your eyes open” were related to slow eye movements (r values 0.67 and 0.64, p < 0.001). Symptoms related to visual disturbance and impaired driving performance were most accurate at detecting severely impaired driving performance (AUC on ROC curve of 0.86–0.91 for detecting change in lateral lane position greater than the change at a BAC of 0.05%). Individual sleepiness symptoms are related to impairment during acute sleep deprivation and might be able to assist drivers in recognizing their own sleepiness and ability to drive safely.     

Risk factors in highway traffic accidents: a case control study

The objective of this study was to identify risk factors related to the driver, the vehicle and the environment, that are associated with motor vehicles accidents on highways. A case and control design was used where the case was: the driver of a motor vehicle who was involved in an accident while traveling on the Mexico-Cuernavaca highway; and the control was: the driver or a motor vehicle who, traveling on the highway, completed the trip without being involved in a traffic accident. Risk factors associated with the occurrence of a traffic accident (P > 0.05) were: age under 25 years, frequent travel, traveling to work, alcohol consumption, driving during the daylight, on a week-day, under adverse weather conditions and in the Mexico Cuernavaca direction of road. Risks adjusted by logistic regression were: age under 25 years odds ratio (OR) 3.01, confidence interval (CI) (95%) 1.46-6.18; work as a travel reason OR 1.74, CI 1.06 2.86; alcohol intake OR 4.70, Cl 1.62 13.6; driving under adverse weather conditions OR 5.70, CI 3.66-8.85; traveling on a week-day OR 1.84, CI 1.14-2.94; during daylight hours OR 4.23, CI 2.36-7.58 and in the Mexico Cuernavaca direction of road OR 2.69, CI 1.67 4.32. The identification of factors associated with the risk of being involved in a highway traffic accident allows us to propose primary prevention measures for this important public health problem.     

Daytime driving simulation performance and sleepiness in obstructive sleep apnoea patients

BACKGROUND: Sleepiness related car accidents are common in obstructive sleep apnoea syndrome (OSAS) patients. The objective measurements of sleepiness used in clinical setting quantify the tendency to fall asleep in quiet situations that are completely different from driving. METHODS: We studied 30 OSAS patients with subjective (subjective sleepiness scales) and objective (multiple sleep latency test, MSLT) sleepiness measurements, associated with driving simulation test (DST), previously validated in young healthy subjects. The results of subjective and objective sleepiness tests were compared with simulated driving performance in order to evaluate the suitability of our DST for measuring alertness. RESULTS: Subjective and objective sleepiness measurements were significantly correlated with driving performance on the simulator. The most significant correlates of sleepiness were the measures of the primary vehicle control task on the simulator: lane position variability and crash data. The comparison of DST and MSLT results suggested our driving simulated approach could be used to evaluate daytime sleepiness in the clinical setting of OSAS patients. CONCLUSIONS: Our DST is a suitable objective tool to detect sleepiness in OSAS patients, and could be useful in the clinical setting of sleep medicine and research.     

Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves

Driving while sleepy is a serious contributor to automobile accidents. Previous research has shown that drowsy drivers produce systematic errors (variability) in vehicle behavior which are detectable using vehicle monitoring technology. The current study developed a new methodological approach using a vehicle heading difference metric to detect drowsy driving more effectively than other more commonly used methods. Twenty participants completed a driving scenario as well as several measures of fatigue in five testing sessions across a night of sleep deprivation. Each simulated highway driving session lasted 20 min, and was analyzed for lateral lane position variability and vehicle heading difference variability with two statistical methods. Fatigue measures monitored reaction time, attention, and oculomotor movement. The results showed that examining lane heading difference using the absolute value of the raw data detected driving variability better across the night than other statistical models. The results from the fatigue measures indicated an increase in reaction time and response lapses, as well as a decrease in oculomotor reactivity across the night. These results suggest that in fatigued drivers the statistical model using the absolute value of lane heading could be an improved metric for drowsy driving detection that could accurately detect detriments in driving ability at lower levels of fatigue.     

The role of driver sleepiness in car crashes: a systematic review of epidemiological studies

To assess the available evidence for a causal role of driver sleepiness in car crashes or car crash injury, and to quantify the effect, a systematic review of the international literature was conducted. The review included all studies with a fatigue-related exposure measure, a crash or crash injury outcome measure and a comparison group, regardless of publication status, language or date of the study. Eighteen cross-sectional studies and one case-control study fulfilled the inclusion criteria. The fatigue-related exposures investigated in these studies were sleep disorders (n = 14), shift work (n = 2), sleep deprivation/fragmentation (n = 1), and excessive daytime sleepiness (n = 2). Only one study used an injury outcome measure. Studies were limited in their ability to establish a causal relationship by their design, by biases, and in many cases, by small sample sizes. The better quality cross-sectional studies were suggestive of a positive relationship between fatigue and crash risk, but could not provide reliable estimates of the strength of the association. The case-control study provided moderately strong evidence for an association between sleep apnoea and risk of driver injury, with an adjusted odds ratio of 7.2 (95% confidence interval 2.4-21.8). We conclude that the direct epidemiological evidence for a causal role of fatigue in car crashes is weak, but suggestive of an effect. To estimate the burden of injury due to fatigue-related crashes in the population, information is required from well-designed observational epidemiological studies about the prevalence of fatigue in the car driving population and the size of the risk this confers.     

Effects of an afternoon nap on nighttime alertness and performance in long-haul drivers

The effects of an afternoon nap on alertness and psychomotor performance were assessed during a simulated night shift. After a night of partial sleep restriction, eight professional long-haul drivers either slept (nap condition) or engaged in sedentary activities (no-nap condition) from 14:00 to 17:00 h. Alertness and performance testing sessions were conducted at 12:00 (pre-nap baseline), 24:00, 02:30, 05:00 and 07:30 h, and followed 2-h runs in a driving simulator. In the nap condition, the subjects showed lower subjective sleepiness and fatigue, as measured by visual analog scales, and faster reaction times and less variability on psychomotor performance tasks. Electrophysiological indices of arousal during the driving runs also reflected the beneficial effects of the afternoon nap, with lower spectral activity in the theta (4–7.75 Hz), alpha (8–11.75 Hz) and fast theta-slow alpha (6–9.75 Hz) frequency bands of the electroencephalogram, indicating higher arousal levels. Thus, a 3-h napping opportunity ending at 17:00 h improved significantly several indices of alertness and performance measured 7–14 h later.     

Short and long sleep duration and risk of drowsy driving and the role of subjective sleep insufficiency

Experimental sleep restriction increases sleepiness and impairs driving performance. However, it is unclear whether short sleep duration in the general population is associated with drowsy driving. The goal of the present study was to evaluate whether individuals in the general population who obtained sleep of 6 h or less are more likely to report drowsy driving, and evaluate the role of perceived sleep sufficiency. Data exploring whether subgroups of short sleepers (those who report the most or least unmet sleep need) show different risk profiles for drowsy driving are limited. From the 2009 Behavioral Risk Factor Surveillance System (N = 31,522), we obtained the following self-reported data: (1) sleep duration (≤5, 6, 7, 8, 9, or ≥10 h/night); (2) number of days/week of perceived insufficient sleep; (3) among drivers, yes/no response to: “During the past 30 days, have you ever nodded off or fallen asleep, even just for a brief moment, while driving?” (4) demographics, physical/mental health. Using 7 h/night as reference, logistic regression analyses evaluated whether self-reported sleep duration was associated with drowsy driving. Overall, 3.6% reported drowsy driving. Self-identified short-sleepers reported drowsy driving more often, and long sleepers, less often. Among those who perceived sleep as always insufficient, drowsy driving was reported more often when sleep duration was ≤5 h, 6 h, or ≥10 h. Among those who perceived sleep as always sufficient, drowsy driving was reported more often among ≤5 h and 6 h sleepers. Overall, drowsy driving was common, particularly in self-identified short-sleepers as a whole, as well as subgroups based on sleep insufficiency.     

Behavioral adaptation of young and older drivers to an intersection crossing advisory system

An advanced driver assistance system (ADAS) provided information about the right of way regulation and safety to cross an upcoming intersection. Effects were studied in a longer-term study involving 18 healthy older drivers between the ages of 65 and 82 years and 18 healthy young drivers between the ages of 20 and 25 years. Participants repeatedly drove 25 km city routes in eight sessions on separate days over a period of two months in a driving simulator. In each age group, participants were randomly assigned to the control (no ADAS) and treatment (ADAS) group. The control group completed the whole experiment without the ADAS. The treatment group drove two sessions without (sessions 1 and 7) and six times with ADAS. Results indicate effects of ADAS on driving safety for young and older drivers, as intersection time and percentage of stops decreased, speed and critical intersection crossings increased, the number of crashes was lower for treatment groups than for control groups. The implications of results are discussed in terms of behavioral adaptation and safety.     

Are drivers aware of sleepiness and increasing crash risk while driving?

Drivers are advised to take breaks when they feel too tired to drive, but there is question over whether they are able to detect increasing fatigue and sleepiness sufficiently to decide when to take a break. The aim of this study was to investigate the extent to which drivers have access to cognitive information about their current state of sleepiness, likelihood of falling asleep, and the implications for driving performance and the likelihood of crashing. Ninety drivers were recruited to do a 2 h drive in a driving simulator. They were divided into three groups: one made ratings of their sleepiness, likelihood of falling asleep and likelihood of crashing over the next few minutes at prompts occurring at 200 s intervals throughout the drive, the second rated sleepiness and likelihood of falling asleep at prompts but pressed a button on the steering wheel at any time if they felt they were near to crashing and the third made no ratings and only used a button-press if they felt a crash was likely. Fatigue and sleepiness was encouraged by monotonous driving conditions, an imposed shorter than usual sleep on the night before and by afternoon testing. Drivers who reported that they were possibly, likely or very likely to fall asleep in the next few minutes, were more than four times more likely to crash subsequently. Those who rated themselves as sleepy or likely to fall asleep had a more than 9-fold increase in the hazards of a centerline crossing compared to those who rated themselves as alert. The research shows clearly that drivers can detect changes in their levels of sleepiness sufficiently to make a safe decision to stop driving due to sleepiness. Therefore, road safety policy needs to move from reminding drivers of the signs of sleepiness and focus on encouraging drivers to respond to obvious indicators of fatigue and sleepiness and consequent increased crash risk.     

Sleepiness,sleep, and use of sleepiness countermeasures in shift-working long-haul truck drivers

Driver sleepiness is a prevalent phenomenon among professional drivers working unconventional and irregular hours. For compromising occupational and traffic safety, sleepiness has become one of the major conundrums of road transportation. To further elucidate the phenomenon, an on-road study canvassing the under-explored relationship between working hours and sleepiness, sleep, and use of sleepiness countermeasures during and outside statutory rest breaks was conducted. Testing the association between the outcomes and working hours, generalized estimating equations models were fitted on a data collected from 54 long-haul truck drivers (mean 38.1 ± 10.5 years, one female) volunteering in the 2-week study. Unobtrusive data-collection methods applied under naturalistic working and shift conditions included the Karolinska Sleepiness Scale (KSS) measuring sleepiness, a combination of actigraphy and sleep-log measuring sleep, and self-report questionnaire items incorporated into the sleep-log measuring the use of sleepiness countermeasures during and outside statutory rest breaks. Drivers’ working hours were categorized into first and consecutive night, morning and day/evening shifts based on shift timing. The results reveal severe sleepiness (KSS ≥ 7) was most prevalent on the first night (37.8%) and least on the morning (10.0%) shifts. Drivers slept reasonably well prior to duty hours, with main sleep being longest prior to the first night (total sleep time 7:21) and shortest prior to the morning (total sleep time 5:43) shifts. The proportion of shifts whereby drivers reported using at least one sleepiness countermeasure outside statutory rest breaks was approximately 22% units greater for the night than the non-night shifts. Compared to the day/evening shifts, the odds of severe sleepiness were greater only on the first night shifts (OR 6.4–9.1 with 95% confidence intervals, depending on the statistical model), the odds of insufficient daily sleep were higher especially prior to the consecutive night shifts (OR 3.5 with 95% confidence intervals), and the odds of using efficient sleepiness countermeasures outside statutory rest breaks were greater on the first as well as consecutive night shifts (OR 4.0–4.6 with 95% confidence intervals). No statistically significant association was found between shift type and use of efficient sleepiness countermeasures during statutory rest breaks. In all, the findings demonstrate marked differences in the occurrence of severe sleepiness at the wheel, sleep preceding duty hours, and the use of sleepiness countermeasures between different shift types. In addition, although drivers slept reasonably well in connection with different shift types, the findings imply there is still room for improvement in alertness management among this group of employees.     

Road accidents caused by drivers falling asleep

About 29600 Norwegian accident-involved drivers received a questionnaire about the last accident reported to their insurance company. About 9200 drivers (31%) returned the questionnaire. The questionnaire contained questions about sleep or fatigue as contributing factors to the accident. In addition, the drivers reported whether or not they had fallen asleep some time whilst driving. and what the consequences had been. Sleep or drowsiness was a contributing factor in 3.9% of all accidents, as reported by drivers who were at fault for the accident. This factor was strongly over-represented in night-time accidents (18.6%), in running-off-the-road accidents (8.3%), accidents after driving more than 150 km on one trip (8.1%), and personal injury accidents (7.3%). A logistic regression analysis showed that the following additional factors made significant and independent contributions to increasing the odds of sleep involvement in an accident: dry road, high speed limit, driving one's own car, not driving the car daily, high education, and few years of driving experience. More male than female drivers were involved in sleep-related accidents, but this seems largely to be explained by males driving relatively more than females on roads with high speed limits. A total of 10% of male drivers and 4% of females reported to have fallen asleep while driving during the last 12 months. A total of 4% of these events resulted in an accident. The most frequent consequence of falling asleep--amounting to more than 40% of the reported incidents--was crossing of the right edge-line before awaking, whereas crossing of the centreline was reported by 16%. Drivers' lack of awareness of important precursors of falling asleep--like highway hypnosis, driving without awareness, and similar phenomena--as well as a reluctance to discontinue driving despite feeling tired are pointed out as likely contributors to sleep-related accidents. More knowledge about the drivers' experiences immediately preceding such accidents may give a better background for implementing effective driver warning systems and other countermeasures.     

Monotony of road environment and driver fatigue: a simulator study

Studies have shown that drowsiness and hypovigilance frequently occur during highway driving and that they may have serious implications in terms of accident causation. This paper focuses on the task induced factors that are involved in the development of these phenomena. A driving simulator study was conducted in order to evaluate the impact of the monotony of roadside visual stimulation using a steering wheel movement (SWM) analysis procedure. Fifty-six male subjects each drove during two different 40-min periods. In one case, roadside visual stimuli were essentially repetitive and monotonous, while in the other one, the environment contained disparate visual elements aiming to disrupt monotony without changing road geometry. Subject's driving performance was compared across these conditions in order to determine whether disruptions of monotony can have a positive effect and help alleviate driver fatigue. Results reveal an early time-on-task effect on driving performance for both driving periods and more frequent large SWM when driving in the more monotonous road environment, which implies greater fatigue and vigilance decrements. Implications in terms of environmental countermeasures for driver fatigue are discussed.     

Self-reported injuries among seafarers. Questionnaire validity and results from an international study

International surveys of occupational injuries among seafarers have so far been missing. It was the aim to test the method of self-report of injuries and length of time at risk during the latest duty period and second to study the injury incidence rate among seafarers by use of the method. A pilot study was conducted (n = 1068) in Finland, Denmark, the Philippines, Croatia and Spain using self-completed questionnaires with questions about the person, the ship, the duration of latest duty period and injuries. The duration of the self-reporting duty period was in the Danish part compared with information from the crew register of the Maritime Authority. For seafarers from merchant ships in the Danish sub-study there was acceptable correspondence between the information from the seafarers and the Maritime Authority, but not when referring to ferries and non-specified types of ship. Unadjusted and adjusted injury incidence rates-ratios (IRRs) based on number of injuries per number of work hours were calculated. Adjusted IRRs for ordinary seamen/officers: IRR = 2.43 (95% CI: 1.25-4.72); for age < 35/35+ years: IRR = 1.97 (1.02-3.81); length of tour: 117 days or longer compared with < 117 days: IRR = 0.46 (95% CI: 0.22-0.95); 57-70 working hours per week compared with < 57 h: IRR = 1.26 (0.48-3.29), 71+h compared with < 57 h: IRR = 2.12 (0.84-5.36). Non-significant IRRs >1.00 were found for ships under 10,000 GT compared with larger ships and for own flagged ships compared with ships under flag of convenience. In conclusion, more than 70 h of work per week was related to a higher rate of injuries for seafarers on merchant ships, but the result was not statistically significant. Self-report of the duration of the latest tour of duty is useful for seafarers from merchant ships with short-term employments, but not for ferries and other, non-specified types of ship with other or permanent employment.     

The alerting effect of hitting a rumble strip—A simulator study with sleepy drivers

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 16 dBA) 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 5 min 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.