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Factors associated with falling asleep at the wheel among long-distance truck drivers
Abstract
Data on the prevalence and hypothesized predictors of falling asleep while driving were gathered through face-to-face interviews with 593 long-distance truck drivers randomly selected at public and private rest areas and routine roadside truck safety inspections. Hypothesized predictor variables related to drivers' typical work and rest patterns, extent of daytime and night-time drowsiness, symptoms of sleep disorder, measures of driving exposure, and demographic characteristics. A sizeable proportion of long-distance truck drivers reported falling asleep at the wheel of the truck: 47.1% of the survey respondents had ever fallen asleep at the wheel of a truck, and 25.4% had fallen asleep at the wheel in the past year. Factor analysis reduced the large set of predictors to six underlying, independent factors: greater daytime sleepiness; more arduous schedules, with more hours of work and fewer hours off-duty; older, more experienced drivers; shorter, poorer sleep on road; symptoms of sleep disorder; and greater tendency to night-time drowsy driving. Based on multivariate logistic regression, all six factors were predictive of self-reported falling asleep at the wheel. Falling asleep was also associated with not having been alerted by driving over shoulder rumble strips. The results suggest that countermeasures that limit drivers' work hours and enable drivers to get adequate rest and that identify drivers with sleep disorders are appropriate methods to reduce sleepiness-related driving by truck drivers.
... These estimates by the IPEA involved the following aspects: loss of productivity (42.0% of the cost); dam age to property (vehicles, city equipment, traffic signs, and property belonging to a third party, amounting to 30.0% of the cost); medical/hospital expenses (rescue, medical treatment and rehabilitation, amounting to 15.9% of the cost); and other costs (legal, traffic jams, social security, removal of the vehicles, other means of transportation, police assistance, traffic officers, and impact on the family, accounting for 11.30% of the cost). While studies on truck driver fatigue or sleepiness date back to the 1930s, much remains unknown about the extent, causes, and effects of sleepiness-related driving in commercial drivers [2]. Fatigue and sleepiness are considered a high problem, not only because it affects drivers' wellbeing but also because it negatively affects performance and safety [3,4]. ...
... Fatigue and sleepiness are considered a high problem, not only because it affects drivers' wellbeing but also because it negatively affects performance and safety [3,4]. Fatigue and sleepiness can occur due to various endogenous and exogenous factors, such as sleep disorders (sleep apnea) [5], poor physical and mental health, advancing age [4], physical workload, nutritional status, alcohol and illicit drug habits or inadequate habits (e.g., poorer sleep quality, high levels of driving exposure; work schedule with long, irregular hours at the wheel during times that conflict with natural circadian rhythms, monotony, permanent night shifts and overtime) [2,[4][5][6][7][8]. A comparative study among short haul light and long distance heavy truck drivers identified important contributors to driver fatigue. ...
... However, Soccolich et al. [15] have demonstrated that an increased waking time, associated with working hours behind the wheel and extra daily activities contribute to the increased risk of errors, incidents and accidents at the wheel. Indeed, a study including 593 truck drivers identified six factors that could explain the drowsiness at the wheel: excessive daytime sleepiness, long working hours, insufficient sleep duration, longer driving experience, age and sleep disorders [2]. Sleep disorders are currently considered a public health issue due to several well-known negative effects on the general population's health and wellbeing. ...
Abstract
Objective: We investigated the relationships among parameters related
to accident involvement, sleep patterns and health habits of shift-working
Brazilian truck drivers.
Methods: In this cross-sectional study, 205 Brazilian truck drivers were
invited and accepted to complete our survey based on the validated
structured “UNIFESP Sleep Questionnaire”. A multiple correspondence
analysis was used to assess the clustering of evaluated potential categorical
variables with involvement in automobile accidents, aiming to examine
associations between these variables.
Results: Our results generated two distinct truck drivers’ profiles. For
the first profile, we observed that drivers who reported involvement in
accidents appeared similar to those who reported drug usage, driving
more than 14 to 19 hours without rest, excessive sleepiness, falling asleep
while driving and sleep complaints. Conversely, the second profile showed
that subjects who were not involved in accidents were similar to subjects
who reported no sleep complaints or excessive sleepiness, did not falling
asleep while driving and did not use drugs. We have also observed that the
variable contributing the most to these two profiles was overnight travel,
followed by falling asleep while driving and sleep complaints. Our data also
demonstrated that exposure to accidents was 4 times higher for drivers
who habitually drive during the night. We have also observed a protective
effect in terms of accident involvement for drivers who usually work fewer
than 12 hours per day.
Conclusion: Our results highlighted how adequate sleep habits, as well as,
the consequences related to sleep disturbances, are associated with drug
consumption and accident involvement by truck drivers.
Keywords: Accidents; Fatigue; Overnight travel; Drivers; Drugs; Falling
asleep
... No differences in crash outcomes have been found between older and middle-aged drivers (Newnam et al. 2018), while others have posited older drivers are safer on the road (Newnam et al. 2020). However, older, longtime drivers are at a higher risk of falling asleep at the wheel (McCartt et al. 2000), and some have found they pose a higher crash and injury severity risk (for single-vehicle crashes; Chen and Chen 2011). Of note, older drivers tend not to report to their carriers any decline in abilities for fear the information could impact their driving future (Newnam et al. 2020). ...
... For example, truck drivers often experience long work hours, severe time pressures, and incompatible expectations on the road (Kemp, Kopp, and Kemp 2013b;Lemke et al. 2016b;Morrow and Crum 2004). These issues can cause driver noncompliance with regulations (McCartt et al. 2000), and stress, which can lead to physical and mental fatigue (Kemp, Kopp, andKemp 2013a, 2013b). Driver fatigue contributes to a higher frequency of safety events (i.e., hard braking, close calls, Of course, rest and sleep have a major impact on driver fatigue and subsequent safety-related events (Morrow and Crum 2004). ...
... Sleep quantity and quality also contribute to driver fatigue, as a lack of both have shown to reduce safety performance and raise crash risk (Chen et al. 2016;Lemke et al. 2016b). Poor sleep on the road can cause drivers to fall asleep at the wheel, which has clear implications for safety (McCartt et al. 2000). For example, during driver restart periods, drivers with only one nighttime period in their restart break experienced greater nighttime fatigue while driving (Sparrow et al. 2016 ...
Abstract This article presents results of a systematic review of the US motor-carrier safety literature in transportation, logistics, and safety journals. The discipline has seen growth in research over the decades, and growth of the field rapidly increased in the last decade. We organize the literature into a systems framework and summarize the research across industry system levels to include government, regulators, carriers, and drivers. We then apply a goal-framing approach to reveal some of the dynamic interactions between system levels and the environment, as entities work to minimize risk to life and property during freight operations while striking a balance between the industry's welfare and societal welfare. This article provides recommendations for future research to fill gaps in the current body of knowledge and to aid government officials, regulators and law enforcement officials, carrier managers, and drivers in addressing industry challenges and maintaining safe roads in 2020 and beyond.
... 7 Fatigue is a common contributing factor in single vehicle and fatal-to-the-driver large truck crashes. 8 In Washington State, 60% of truck driver fatalities are vehicle-related, and half of those fatalities were caused by single vehicle accidents where drivers lost control of their truck-a type of crash where fatigue is a likely factor. [9][10][11] In 1995 the National Transportation Safety Board evaluated 182 fatal-to-the-driver large truck crashes, and found that fatigue was the principle cause of the crash in 31% of cases. ...
... For analysis, LabVIEW programs (Version 2016; National Instruments, Austin, TX) were used to align acceleration data with GPS data and combine them into one file for each team. Once the files were created, a LabVIEW program was used to apply weighting as described in ISO 2631-1 (1997) to the raw, unweighted acceleration data, and additional LabVIEW programs were used to calculate the predominant, Z-axis average weighted vibration exposures that were normalized to 8 hours, termed ''A (8).'' Additionally, power spectral density (PSD) analyses were conducted to further examine the truck mattress and truck floor vibrations in the frequency domain. ...
... Figure 2 shows that the low frequency peaks in the floor PSDs were centered around 2 Hz and similar between the two companies. However, there were differences between companies in the higher frequency floor PSD peaks, which were centered around 14 Hz for Company 1, and 9 Hz for Company 2. As shown in Fig. 3, the PSDs for the mattresses were company dependent with Company 1 having higher PSDs compared to Company 2. With Company 1, the mattress in condition A had more higher frequency vibration energy (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) Hz) compared to the mattress in condition B; whereas, with Company 2, the mattress in condition A had more lower frequency vibration energy (1-4 Hz) than the mattress in condition B. ...
Objective:
To test the feasibility, acceptability, and potential effectiveness of engineering and behavioral interventions to improve the sleep, health, and well-being of team truck drivers (dyads) who sleep in moving semi-trucks.
Methods:
Drivers (n = 16) evaluated (A) an innerspring mattress and (B) a novel therapeutic mattress. A subsample (n = 8) then (C) switched to an active suspension driver's seat and completed a behavioral sleep-health program. Primary outcomes were sleep duration, sleep quality, and fatigue. Behavioral program targets included physical activity and sleep hygiene.
Results:
Self-reported sleep and fatigue improved with mattress A, and improved further with mattress B which altered vibration exposures and was kept by all drivers. Condition C improved additional targets, and produced larger effect sizes for most outcomes.
Conclusions:
Results support these interventions as promising for advancing team truck drivers' sleep, health, and well-being.
... This is the main issue behind the drivers' dissatisfaction with the profession; even though they are facing health-related problems they continue to serve in the occupation. The effect of skillset on driving behavior has been studied in the literature (22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36), as well as the reasons for dissatisfaction with the profession (37)(38)(39)(40). Many studies have attempted to identify truck drivers' views on the contributing factors for accidents, and found issues such as stress (5, 8, 10-13, 24, 38, 41), sleep disorder (6,10,13,17,23,30,(41)(42)(43)(44), fatigue (6,10,13,14,25,27,29,(45)(46)(47), anxiety (17,18), over speeding (8,12,22,39), rash driving (22,39), low income, depression (4-6, 10, 15, 22, 35, 38, 43, 48), and driving for an extended period (5-8, 13, 15, 18, 24, 25, 28, 42, 46). ...
... Apart from these factors, personal factors such as age (23,40,41,46,49), education level (16,24,31,37,49,50), experience (1,3,8,11,34), and physical health condition of the drivers (6,10,13,23,47) were also studied. Previous studies have demonstrated that drowsiness has an adverse effect on safe driving (1,(45)(46)(47), but during accident investigation drivers never reveal that they fell asleep while driving (17,28). The effect of economic factors such as income, wages, incentives, and savings on fuel on driving behavior were also studied; it was found that economic factors have two types of effects on driving behavior. ...
... The effect of economic factors such as income, wages, incentives, and savings on fuel on driving behavior were also studied; it was found that economic factors have two types of effects on driving behavior. Some studies found that the incentives based on performance such as savings on fuel and overtime allowance motivate drivers to drive for long hours (15,25,28) to gain the benefit; on the other hand, economic benefits such as paid-by-trip ensure the minimum wages for the drivers cause less fatigue and stress (14,45,50). External factors such as poor road conditions (1,2,13,50), extreme weather conditions, and cattle on the road also have a negative effect on the attention of the driver by distracting attention and causing sudden braking or turnings. ...
India ranks first in the global fatalities rate related to traffic accidents. India’s trucking industry is highly unorganized compared with that in developed countries, as a result of which drivers do not get professional recognition in society. Low income, job
insecurity, high-fatigue conditions, and continuous exposure to external environmental conditions cause job dissatisfaction, and the majority of traffic accidents in India are caused by driver negligence. This study aims to systematically examine the
underlying factors that cause drivers’ unsafe behavior from the following four assessment levels: personal, professional, organizational, and external factors. A purposeful sampling-based survey method was employed to collect the data. The findings
of this study were compared with the opinions of the experts and results from previous studies in the literature. The study results found that the contribution of professional and organizational factors to unsafe behavior is greatest compared with external and personal factors. The study concludes with recommendations for reducing drivers’ risk through planned driving schedules, ensuring social security through welfare schemes, and improving driving performance through proper training programs for preventing and minimizing damage caused by accidents, and recommends policy-based measures to trucking companies and regulatory bodies for minimizing accident occurrence.
... Turning to other fatigue inducing factors, inappropriate rest breaks, prolonged driving time, payment type, and tight delivery schedules were shown to have significant impact on fatigue driving (Chen and Xie, 2014;Mahajan et al., 2019a,b;Chen and Xie, 2014) investigated the impacts of off-duty prior to a trip and short rest breaks using Cox proportional hazards model and Anderson-Gill model. The study results showed that increasing total rest break duration consistently resulted in reduction of fatigue related crashes (Mccartt et al., 2000). reviewed the factors associated with falling asleep behind the wheel among truck drivers using Multivariate logistic regression model. ...
... It is also found that Parking difficulties (F4), Tiredness due to prolonged queuing (F5), Verbal criticism from dispatchers (F2), Discomfort due to increase in vehicle heat during driving (F6), Motivation towards incentives (F3), Marital status (S2), and Ownership of vehicle (W1), as the least predictors of fatigue with MDG ranging between 1 and 3 in the present sample. In essence, the contributory factors of truck driver fatigue herein obtained from the variable importance plot was found to be in coherence with a number of previous studies from different regions (Mccartt et al., 2000;Mahajan et al., 2019a,b). ...
Introduction: Long-haul Truck drivers (LHTDs) have long working hours, insufficient rest, and poor health conditions and often experience fatigue that substantially may lead to crashes and injuries. Despite its potential harmfulness, we have little understanding on non-linear hidden patterns of influential factors on fatigue driving, especially in developing nations like India. Objectives: This paper aimed to predict fatigue driving among LHTDs using four tree-based machine learning techniques including Decision tree (DT), Random Forest (RF), Adaptive boosting (AdaBoost), and Extreme gradient boosting (XGBoost) to analyze the non-linear hidden pattern of most influential variables contributing to fatigue driving among Indian LHTDS. Methods: Using a cross-sectional study design, a face-to-face interview was conducted among LHTDs using carefully designed questionnaire in Salem, Tamil Nadu, India. A total of 756 responses were obtained from LHTDs based on four aspects including socioeconomic characteristics , work and vehicle characteristics, health-related lifestyle characteristics, and fatigue-inducing characteristics using a convenience sampling technique. Four tree-based machine learning algorithms namely DT, RF, Adaboost, and Xgboost were employed to predict fatigue driving. The influence of predictors on fatigue driving for the most suitable model was determined through variable importance plot and their causality effect on probability of fatigue were examined using Partial dependency plot (PDP). All the analysis were carried out using IBM SPSS statistics Version 27.0 and R programming language version 4.2.1. Results: From the analysis, it was found that RF model outperformed other investigated classifiers (Accuracy = 81.2%, F1 score = 58.82%, AUROC = 0.854). Furthermore, variable importance plot of befitting RF classifier showed that type of commodity carried, pressured delivery of goods, countermeasure mostly followed, and education level of the LHTD as some of most influential predictors causing fatigue. Conclusion: These findings provide insights to state and highway transportation officials and In-dian trucking industries for framing effective strategies to promote safety and well-being among LHTDs.
... In this study, 36 55% of the drivers are found to travel the same mileage before a WWD crash ( Figure 1). Also, in 37 the Vermont study, neither they divided drivers into local-nonlocal groups nor found any driver 38 group-specific crash-related factors. 39 The definition of local and non-local drivers is unclear. ...
... For 34 this group, the study team recommends a low-cost countermeasure package over the expensive 35 ITS-based technologies. Michigan and Connecticut DOTs have two accomplished "low-cost 36 countermeasures package" projects that can help prevent non-local drivers from going the wrong 37 way in rural areas (Table 4) (4,45). 38 39 However, ITS sensor and camera-based installation cost ranges from $50,000 to $150,000 (46). ...
Extensive research has been conducted on Wrong-Way Driving (WWD) prone crash locations, crash contributing factors and safety countermeasures. Still, the number of WWD crashes remains nearly constant over the past years, necessitating further investigation from different perspectives. Past studies identified various crash contributing factors that directly contributed to WWD crash frequency and severity. Prime factors include driver characteristics, environmental and temporal characteristics, and interchange layouts. However, the impact of locality and nonlocality on WWD crash propensity is seldom investigated. Therefore, this study explores the major WWD crash contributing factors related to local and non-local drivers. A total of 1,048 WWD fatal crashes from 2015 to 2017 were collected from the Fatality Analysis Report System (FARS) database. Drivers’ locality and non-locality were defined using the distance traveled from home to crash location using the Geographic Information System. Descriptive statistics and a multinomial logit model were developed to analyze the significant contributing factors specific to driver groups. The results demonstrated that factors such as rural settings, unprotected median types, and dark but not lighted conditions significantly contributed to WWD fatal crashes when the driver was non-local. In contrast, local drivers are more prone to be involved in WWD crashes in urban areas and while driving under the influence of alcohol or drugs. Based on the results, different safety countermeasures related to WWD crashes were recommended targeting local and non-local drivers.
... According to the data of the National Council of Road Safety of the Ministry of Transport and Communications (MTC), there were 88,168 traffic accidents in the non-urban road network (roads) during 2017. 7 Worldwide, there are frequent reports of accidents in interprovincial bus transportation as a result of drowsiness or weariness that they experience during their work shift, which are brought about by their bad driving habits and work breaks [9][10][11][12] . Excessive drowsiness during driving decreases the attention span of drivers, advantages errors in driving maneuvers, reduces responsiveness and affects reaction time to an unforeseen event [13][14][15] . ...
... Excessive drowsiness during driving decreases the attention span of drivers, advantages errors in driving maneuvers, reduces responsiveness and affects reaction time to an unforeseen event [13][14][15] . Various conditions have been associated with drowsiness while driving vehicles such as level of education, years of experience as a driver, sleep deficit the previous night, overweight and obesity 8,9,11,12,16 . ...
Objective: To determine the factors associated with excessive daytime sleepiness (EDS) in informal interprovincial transport drivers of the Lima-Huancayo central highway (Peru) from January to March 2018.
Methods: Cross-sectional study. The drivers were weighed and measured, then individual, sociodemographic, and occupational data were obtained which were recorded in a data collection form, then the Epworth Sleepiness Scale (ESS) was applied to the drivers. The prevalence and EDS-associated factors in drivers were obtained from this data. The multivariate analysis of the possible associated factors for EDS was performed with binary logistic regression, obtaining the adjusted odds ratio (AOR).
Results: 162 drivers participated in the study. The average age was 42.0 ± 10.2 years (Range of 21-62 years), all the participants were male. 55. 6% had a technical degree, 42.0% were married and 55.6% had two to three children. The mean time of experience as a driver was 17.0 ± 6.8 years, 54.9% were overweight, and 32.1% were obese. 27.8% of drivers had EDS, the multivariate analysis found that the EDS-associated factors of the drivers were obesity (AOR=3.8, 95% CI: 1.422- 10.233), having 10 or more years of experience as a driver (AOR=3.1, 95% CI: 1.342-7.189) and overweight (AOR=2.9 CI 95%: 1.216-7.096).
Conclusion: There is a high prevalence of EDS in informal drivers of interprovincial transport of the central high-altitude highway studied. Obesity was the main factor associated with EDS, along with being overweight and having 10 or more years of experience as a driver.
... Transportation drivers have been found to have more sleep disruptions, especially for those who are working the night shift and extended working hours (14). Most studies have examined the link between poor sleep, sleepiness, and fatigue among drivers (5,15). Another study conducted among commercial truck and bus drivers in Thailand (16) showed a strong relationship between drowsiness and accidents. ...
... A past study reported sleep-related accidents during this period (22). A study of fatigue among drivers has linked time of the day and fatigue as the most consistent factor (5,14). Past researchers have identified nighttime driving among professional drivers resulted in reduced performance and alertness. This supported the fact that sleeping frequently occurs in nocturnal driving. ...
Fatigue is an inevitable problem in the workplace due to many factors. Transportation workers are susceptible to falling asleep at the wheel, feeling tired and drowsiness, prolonged mental and physical exertion, sleep deprivation, which will later result in fatigue. The objective of this paper is to provide a comprehensive review of driver fatigue, documenting potential relationships between demographics and work factors with prevalence of risk factors among transportation drivers. Related literature search was done using PubMed, SCOPUS, and ScienceDirect to review some articles related to factors influencing fatigue among transportation workers which was published between years 2000 to 2021. The most significant risk factors were poor quality and quantity of sleep, prolonged driving in a day and work-related factors. Therefore, further research should be directed towards assessing and implementing a standardized measurement of work fatigue. This could help the industry in precisely managing and measuring fatigue and sleepiness.
... Several empirical studies report the prevalence of fatigue and fatigue-related accidents in the trucking industry. For instance, Häkkänen & Summala [18] report that around a fifth of long-distance truck drivers in their survey had dozed off at least twice while driving, while in McCartt et al. [28] almost half of the surveyed truck drivers reported having fallen asleep at the wheel. Moreover, in Boufous & Williamson's study [5], fatigue levels were reported in 28% of fatalities, while Akerstedt [2] claimed fatigue was behind between 15 to 20% of accidents. ...
... In long-haul road freight, fatigue is caused by, amongst others factors, inadequate rest and prolonged and irregular working hours [1,2,5,6,28]. Current European legislation, specifically 'Regulation (EC) A business model for automated road freight in geo-fenced highway areas: impact and implications 3 No 561/2006' [35] mandates that workdays should not exceed nine (exceptionally ten) hours of driving, besides frequent breaks and rest periods. ...
We describe and quantitatively assess an L4-ready business model for long-haul road freight. In short, this model relies on a driverless geo-fenced (but wide) highway area, supervised by a control center. Complementing self-driving, manual driving would become more local. This approach would also require an infrastructure of pick up/drop-off locations near main transport hubs. We show this model would allow to reap the economic and societal benefits of CAD while avoiding potential negative effects. More specifically, it can lead to higher safety, productivity and traffic efficiency while also reducing labour shortages, improving work conditions and yielding a quicker market adoption of AVs.
... [3][4][5][6][7][8][9][10][11][12][13] OSA is particularly salient for commercial drivers, since untreated moderate-severe disease is associated with greater risk of falling asleep at the wheel and vehicular crashes, 14 greater medical care costs, 15 and adverse health consequences. [14][15][16][17][18][19][20][21] Vehicular crashes, in particular, are an immediate danger to drivers with untreated or undiagnosed OSA; accidents from falling asleep at the wheel have a fatality rate similar to that of alcohol-related crashes. 22 Studies have shown an association between likelihood of OSA and increased rate of crashes in commercial vehicle drivers 23,24 , and a systematic review and meta-analysis showed increased rate of crashes in individuals with OSA 25 . ...
Background
: Obstructive sleep apnea (OSA) is common in commercial drivers, and associated with increased risk of crashes if untreated, making diagnosis and effective treatment crucial in this population.
Study Design and Methods
: This is a retrospective summary of a clinical program based on telemedicine and remote treatment monitoring developed with a national trucking company to screen new hires in the U.S. for OSA and implement PAP management. New hires were informed of the program and consented as part of their employment. Drivers who did not comply with the evaluation or with PAP after diagnosis were removed from driving commercial vehicles by the company or did not pursue further employment.
Results
: A total of 975 drivers were enrolled. Among screened drivers, 35.5% were cleared without a sleep study, 15.0% were cleared following a sleep study (AHI<5 events·h ⁻¹ ), 22.1% had mild OSA (AHI 5–15), and 27.4% had moderate-severe OSA (AHI≥15). Those with moderate-severe OSA were more obese (36.2±6.3 kg·m ⁻² ) and had more comorbidities. Of 269 drivers starting CPAP, 160 (59.5%) maintained participation in a care management program, 80 (29.7%) resigned or were terminated, 23 (8.6%) were cleared to discontinue PAP, and 6 (2.2%) were complex cases requiring transfer of care. Illustrating effectiveness, those that maintained participation had excellent PAP adherence (5.27±1.61 h/night; 88.5±12.9% days used; 79.7±17.7% days used ≥4 h).
Interpretation
: Remote assessment of OSA and PAP management in commercial drivers is feasible and effective. This approach has wide-ranging applications, particularly in populations and areas with a lack of sleep medicine providers.
... reports having fallen asleep behind the wheel within the previous 12 months ( McCartt et al., 2000;Vitols & Voss, 2021). ...
All new vehicle types within the European Union must now be equipped with a driver drowsiness and attention warning system starting from 2022. The specific requirements for the test procedure necessary for type approval are defined in the Annex of EU Regulation C/2021/2639. The objectives of this study were to: (i) investigate how sleepiness develops in professional truck drivers under real‐road driving conditions; and (ii) assess the feasibility of a test procedure for validating driver drowsiness and attention warning systems according to the EU regulation. Twenty‐four professional truck drivers participated in the test. They drove for 180 km on a dual‐lane motorway, first during daytime after a normal night's sleep and then at nighttime after being awake since early morning. The results showed higher sleepiness levels during nighttime driving compared with daytime, with a faster increase in sleepiness with distance driven, especially during the night. Psychomotor vigilance task results corroborated these findings. From a driver drowsiness and attention warning testing perspective, the study design with sleep‐deprived drivers at night was successful in inducing the targeted sleepiness level of a Karolinska Sleepiness Scale score of ≥ 8. Many drivers who reported a Karolinska Sleepiness Scale ≥ 8 during the drives also acknowledged feeling sleepy in the post‐drive questionnaire. Reaching high levels of sleepiness on real roads during daytime is more problematic, not the least from legal and ethical perspectives as higher traffic densities during the daytime lead to increased risks.
... Concerning the factors leading to truck/large truck accidents and/or risky behavior, most research on the dangers associated with their operations covers factors that include age [45,46], job experience [47,48], sleep quality [49,50], driving mileage [51,52] and the time of day [53,54]. There is a lack of literature, especially for heavy goods vehicle drivers, on the influence of nationality on violations of drivers' working rules or on the type of goods transported. ...
To achieve the elimination of the negative impacts of transport on road safety, the European Union is taking various measures resulting from its commitment to improve road safety. The main objective of this paper is to assess the impact of social legislation on road transport safety using real research and to identify the factors influencing the violation of the legislation depending on the type of transport carried out in domestic or international road freight transport. Answers from the respondents are used in the segmentation of truck drivers based on input data describing the factors influencing the violation of traffic rules. Two-step cluster analysis is a suitable method for the segmentation of truck drivers based on input data. These data are obtained through a questionnaire from a total of 472 Czech and Slovak truck drivers. The results show that the optimal number of types of truck drivers with different characteristics is four. All of the clusters are described and compared. The majority of truck drivers do not violate social legislation for several reasons, such as traffic accidents (almost 67%), complications in meeting the loading or unloading deadline (less than 88%), poorly planned transport routes (more than 90%) and driving home (almost 80%).
... For McCartt et al. (2000), drowsiness is an important factor for accidents, although there is generally little physical or other evidence that a driver crashed due to sleepiness or falling asleep, which is consistent with what was stated by Chu (2014b), who indicates that accidents that occurred at night significantly increased the probability of serious injuries; however, accidents at night, before midnight, cause less serious injuries than those that occur between midnight and dawn, which can be associated with the appearance of great drowsiness. On this same point, Nik Mahdi et al. (2014) indicate that night driving is an additional risk factor, especially during the early morning hours, associated with fatigue and poor visibility. ...
... OSAS patient who used more than three such strategies had worse ESS (17 +/-Introduction Driving is a complex task that involves many aspects such as perception, response time, physical ability and is an essential part of an individual's life. Studies have shown that driving either on a motorway or on an urban road can be fatiguing even for an alert driver [1][2][3] . ...
Introduction
Sleepiness while driving is potentially fatal, and it is recommended that a driver who starts to feel tired should stop and have a rest. However, some may use various counter measures to try to stay alert. We devised a questionnaire that assessed various potential coping strategies that might be used against fatigue and compared them between OSAS patients and controls and with sleepiness in general (Epworth Sleepiness Scale; ESS), specifically while driving (Driving Sleepiness Scale; DSS) and driving incidents.
Method
119 untreated OSAS patients (Males; 82%, BMI; 37±8, ESS; 14±5, DSS: 3±2, ODI; 39±15) and 105 controls (Males; 70%, BMI; 28±6, ESS; 4±3, DSS; 7± 6) matched for age and driving experience were recruited. All completed a questionnaire, relating to their experience over the last one year, which included sleepiness in general, sleepiness specifically while driving, ten questions about various coping strategies they might adopt in order to avoid sleepiness and their history of incidents while driving. As compared to controls, nearly a third of OSAS patients (29.4%) used more than three coping strategies “frequently”. OSAS patient who used more than three such strategies had worse ESS (17±4 v/s 12±5, p=<0.0001); were more likely to feel sleepy while driving (10±8 v/s 5±7, p= 0.0002) and had more reported accidents (22.85% v/s 2.38%, p= 0.0002) as compared to OSAS patients who used less than three strategies. There was no difference in patient demographics, severity of OSAS, driving experience or episodes of nodding at the wheel and reported near miss events.
Conclusions
Untreated OSAS patients frequently use certain strategies which could be surrogate markers of sleepiness. Enquiring about such strategies in clinical practice may aid the clinician in identifying the patients who are at risk of driving incidents and to advise appropriately.
... Not all drivers fully rested before leaving the route (40% of drivers slept only 4-5 hours). Sleep disturbance is directly related to the risk of a traffic accident [31][32]. Many drivers (40%) constantly felt tired at work. ...
Mountain roads in Kyrgyzstan are characterized a large difference in altitude above sea level. Above 2,000 meters above sea level, drivers develop symptoms of altitude sickness. The aim of the study is to study the effect of atmospheric pressure on the body of a vehicle driver in mountainous conditions. The Bishkek-Naryn-Torugart international highway was chosen as an object. Control point No. 1 is located on the Torugart pass near the border with China (altitude is 3752 meters above sea level). Checkpoint No. 2 is located near the village of At-Bashy (altitude above sea level is 2046 meters). Control point No. 3 is located near the village of Kemin (altitude 1120 meters above sea level). The results of the study showed that blood pressure indicators change along the considered route depending on the height above sea level. For example, pressure indicators of 140-159 / 90-99 were observed in 24% of drivers at point No. 1, 19% at point No. 2 and only 5% at point No. 3. Blood pressure 160-179 / 100-109 (moderate hypertension) was observed in 7% of drivers in point 1 and in 5% of drivers in point 2. The main reason for the increase in pressure was a violation of the mode of work and rest of drivers. As a result, standards for the work of drivers of international road transport in high altitude conditions were developed and measures were proposed for the mandatory organization of rest places for drivers on the Bishkek-Naryn-Torugart road.
... In the context of commercial vehicles, accidents stemming from driver drowsiness or inattentiveness are notably amplified, accounting for approximately 39% of such incidents (Sung et al., 2005). This issue is particularly widespread within the trucking sector, where a substantial 47.1% of truck drivers in the United States have acknowledged experiencing drowsiness at some point in their professional trajectory, with 25.4% revealing such occurrences within their first year of operation (McCartt et al., 2000). Correspondingly, data from Canada indicates that a considerable number (exceeding 60) of fatal accidents involving heavy motor vehicles each month are due to drivers either dozing off or succumbing to fatigue (Du et al., 2018). ...
Driver drowsiness is a factor in at least 20% of serious motor vehicle accidents. Although research has shown that
Whole-Body Vibration (WBV) can induce drowsiness in drivers, it is unknown whether particular frequencies are
more problematic. The present study systematically investigated the influence of WBV frequency on driver
drowsiness. Fifteen participants each undertook six 1-h sessions of simulated driving while being subjected to
WBV of either 0 Hz (no vibration), 1–4 Hz, 4–8 Hz, 8–16 Hz, 16–32 Hz or 32–64 Hz. Subjective sleepiness, as
measured by the Karolinska Sleepiness Scale (KSS), confirmed that drivers felt drowsier when exposed to the two
lowest frequency ranges (1–4 Hz and 4–8 Hz). Reaction time, which measures attention and alertness, was
significantly impaired by the two lowest frequency ranges. Objective driving performance measures (Standard
Deviation of Lane Position (SDLP), Standard Deviation of (SD) Steering Angle, Time in Unsafe Zone) also showed
significant degradation due to exposure to the two lowest frequency ranges. Exposure to 1–4 Hz or 4–8 Hz vibration
caused attention to become significantly impaired within 15–20 min and driving performance to be
significantly impaired by 30–35 min. The other frequency ranges had little or no effect. These findings point to a
need to develop equivalent vibration-induced drowsiness contours that can be adopted as transportation safety
standards.
... On the first barrier, commercial vehicles and public transport contribute to substantial road traffic morbidity and mortality in Ghana and other LMICs [4]. Among commercial truck drivers, work-related factors (e.g., demanding job requirements, long-haul distances) and behavioral factors (e.g., fatigue, speeding, alcohol/drug use) have been shown to increase the risk of crashes globally [21][22][23][24][25][26][27][28][29][30]. Prior studies in Ghana have found that crashes with commercial vehicles (e.g., heavy-load vehicles, public buses, taxis) are particularly common [31]. ...
Background:
Implementation of evidence-based approaches to reduce the substantial health, social, and financial burdens of road traffic injuries and deaths in Ghana and other low-and-middle-income countries (LMICs) is vitally important. Consensus from national stakeholders can provide insight into what evidence to generate and which interventions to prioritize for road safety. The main objective of this study was to elicit expert views on the barriers to reaching international and national road safety targets, the gaps in national-level research, implementation, and evaluation, and the future action priorities.
Materials and methods:
We used an iterative three-round modified Delphi process to generate consensus among Ghanaian road safety stakeholders. We defined consensus as 70% or more stakeholders selecting a specific response in the survey. We defined partial consensus (termed "majority") as 50% or more stakeholders selecting a particular response.
Results:
Twenty-three stakeholders from different sectors participated. Experts generated consensus on barriers to road safety goals, including the poor regulation of commercial and public transport vehicles and limited use of technology to monitor and enforce traffic behaviors and laws. Stakeholders agreed that the impact of increasing motorcycle (2- and 3-wheel) use on road traffic injury burden is poorly understood and that it is a priority to evaluate road-user risk factors such as speed, helmet use, driving skills, and distracted driving. One emerging area was the impact of unattended/disabled vehicles along roadways. There was consensus on the need for additional research, implementation, and evaluation efforts of several interventions, including focused treatment of hazardous spots, driver training, road safety education as part of academic curricula, promotion of community involvement in first aid, development of strategically positioned trauma centers, and towing of disabled vehicles.
Conclusion:
This modified Delphi process with stakeholders from Ghana generated consensus on road safety research, implementation, and evaluation priorities.
... Fatigue is defined as a "physical or mental state of a lack of energy and concentration where sleepiness, tiredness, drowsiness, and lethargy are often used interchangeably" [13,14]. Fatigue in the road transport industry is also described as "falling asleep at the wheel" [15]. In the study of Williamsons et al. [16], they described fatigue as "a biological drive for recuperative rest", indicating that this rest depends on the nature of the fatigue. ...
Background:
Fatigued driving is one of the leading factors contributing to road crashes in the trucking industry. The nature of trucking, prolonged working time, and irregular sleep patterns can negatively impact drivers' health and wellbeing. However, there is limited research in Australia investigating the impact of demographic, occupational, or lifestyle factors on fatigue among truck drivers.
Objective:
This cross-sectional study examines the role of demographic, occupational, lifestyle, and other health risk factors associated with fatigue among Australian truck drivers.
Method:
This study was part of a larger study that used a short online survey with a follow-up telephone survey to capture in-depth information on a wide range of determinants related to truck drivers' physical and mental health outcomes. Fatigue was measured by three questions, including the frequency of fatigue, fatigue management training, and strategies used to combat fatigue. Multivariate regression analysis was used to determine the specific impact of demographics, occupational factors, lifestyle factors, and other health risk factors on fatigue.
Results:
In total, 332 drivers completed both the online and telephone surveys; 97% were male, representing drivers from broad age groups and professional experience. The odds of being in the high-risk fatigue group were nearly three times higher in drivers who worked 40-60 h compared to those who worked < 40 h. Poor sleep increased the odds of high-risk fatigue by seventimes (95% CI: 2.26-21.67, p = 0.001). Drivers who reported experiencing loneliness also had double the odds of being at high risk of fatigued driving.
Conclusions:
The increased risk of fatigue in truck drivers is associated with prolonged working hours, poor sleep, and social aspects such as loneliness. Further interventions seeking to reduce driver fatigue should consider the impact of work schedules, the availability of quality sleeping spaces, and the level of social connections.
... On the first barrier, commercial vehicles and public transport contribute to substantial road traffic morbidity and mortality in Ghana and other LMICs (4). Among commercial truck drivers, workrelated factors (e.g., demanding job requirements, long-haul distances) and behavioral factors (e.g., fatigue, speeding, alcohol/drug use) have been shown to increase the risk of crashes globally (21)(22)(23)(24)(25)(26)(27)(28)(29)(30). Prior studies in Ghana have found that crashes with commercial vehicles (e.g., heavy-load vehicles, public buses, taxis) are particularly common (31). ...
... As for commercial truck drivers, when driving on the job, they spend significant time behind the wheel and they are expected to maintain contact with dispatchers (Ng et al., 1995), and when they become bored due to a long drive, using a mobile phone becomes more and more tempting (Iseland et al., 2018). On the other hand, truck drivers' DE has also been significantly and positively associated with the frequency of their various risky driving behaviors, such as overloading (Alkhoori & Maghelal, 2021) and fatigued driving (McCartt et al., 2000). Therefore, the following hypotheses were proposed: H6. ...
Commercial truck drivers are particularly exposed to the risks associated with distracted driving, especially with mobile phone use while driving (MPWD), due to their higher driving exposure (DE) (e.g., high driving frequency, long driving hours and distance). However, despite being identified as one of the major causes in truck crashes, truck drivers’ MPWD behavior has received little attention. In the current work, the theory of planned behavior (TPB), extended with DE, was applied to explore the determinants of MPWD among commercial truck drivers in China and examine the correlations between drivers’ DE and psychological factors. We conducted an Internet survey and collected 420 valid questionnaires, which measured truck drivers’ 5 standard TPB variables, DE and demographics. Structural equation modelling was used to analyze the data from the survey. The results showed strong support for the application of the proposed TPB model in explaining truck drivers’ MPWD behavior. Specifically, truck drivers’ behavioral intention (BI) had the greatest direct positive effect on MPWD behavior, while perceived behavioral control (PBC) had no direct positive effect. Moreover, PBC, attitude (ATT) and DE were significantly and positively associated with BI, while subjective norm was insignificant. As expected, DE has significant positive effects on truck drivers’ psychological factors underlying MPWD behavior, especially on ATT and PBC, indicating that truck drivers with higher DE tend to have more positive attitudes toward MPWD and feel more confident about performing this risky behavior. These results may have notable practical implications in providing theoretical support for management and intervention of commercial truck drivers.
... Fatigue and stress are blamed for some of these accidents [26,28]. Although several studies have examined the connection between a driver's work schedule and their performance behind the wheel in different sectors [29,30,31,32], there is a paucity of research on how safety culture can mitigate this unfavourable relationship between the work schedule and driving performance. Otherwise, previous studies in the oil and gas transportation sector addressed many important factors, such as exhaustion-related psychological risk factors [33], psychological well-being, perceived stress [34,35], and fatigue assessment by the psychomotor vigilance test [36]. ...
The adverse effects of work schedule on driving performance are relatively common. Therefore, it is necessary to fully understand an organisation’s safety culture to improve driver performance in order to avoid road crashes. This study aims to investigate the moderating role of safety culture in the relationship between driver work schedules and driving performance. The study developed a conceptual framework based on the literature review of existing studies, which is supported by situation awareness theory that explains the model’s relationships and supports the study’s hypotheses. Three hundred four questionnaires were collected from oil and gas truck drivers then Structural equation modelling (SEM) was applied to test the study hypotheses. Derived from the findings, the outer loading for all items was above the threshold of 0.70 unless two items were deleted. The latent exogenous variables of safety culture and work schedule explained 59.1% of driving performance. Besides, work schedule and safety culture significantly impact driving performance. In addition, the results show that safety culture moderates the unfavourable work schedule impact on driving performance with an effect size of 23%. Therefore, this study showed strong evidence that safety culture acts as a critical moderator in reducing the negative impact of work schedule on driving performance in the energy transportation sector. Drivers with high safety culture can manage and reduce the effect of work schedule disorder on driving performance through their safety attitude and patterns compared to those drivers with low safety culture. Consequently, the improvement in driving performance will be noticed among drivers with a high awareness of safety culture.
... A seguir, são discutidos os três principais fatores identificados (sono, trabalho e saúde) que podem influenciar a manifestação da fadiga, onde se tenta resumir de forma concisa a literatura relevante sobre cada tema. (LEMKE et al., 2021;LIU et al., 2009;MCCARTT et al., 2000;MIZUNO et al., 2020;SHAMS et al., 2020;Umar;Bashir, 2020 1997;FILOMENO et al., 2019;GARBARINO et al., 2018;GIROTTO et al., 2016;SHAMS et al., 2020;WISE et al., 2020). ...
Os acidentes de trânsito vêm sendo tratados como um problema de saúde pública, uma vez que sobrecarregam o sistema de saúde dos países, trazendo um alto custo social devido as principais vítimas serem jovens economicamente ativos. Especialmente os motoristas de caminhão, que geralmente dirigem por longos períodos e em turnos irregulares, têm um risco relativamente alto de se envolverem em acidentes durante sua jornada de trabalho. No Brasil, entre 2007 e 2018, morreram 38.040 pessoas vítimas de acidentes em que pelo menos um caminhão esteve envolvido. Estima-se que a fadiga esteja envolvida entre 20% e 50% dos acidentes graves no mundo. A fadiga pode aumentar a frequência, a amplitude ou a variabilidade dos erros que o condutor pode cometer ao volante. Dessa forma, o principal objetivo do estudo é sintetizar as evidências relacionadas aos aspectos causadores da fadiga nos motoristas de caminhão. Para a realização da revisão sistemática se utilizou as diretrizes do PRISMA, conjunto de tópicos a serem descritos pelos autores durante o desenvolvimento da pesquisa. Foram definidos critérios de elegibilidade dos estudos, como palavras-chaves, tipo de documento, fonte, idioma e período de abrangência. A revisão trabalhou com 56 artigos selecionados e identificou três fatores que podem influenciar a manifestação da fadiga, sendo eles o sono, o trabalho e a saúde. Além do potencial impacto na segurança dos motoristas, o sono insuficiente é um fator de risco causador de uma ampla gama de problemas de saúde. As condições de trabalho e os stress relacionados a profissão não só têm o potencial de impactar negativamente ao agravar a saúde dos caminhoneiros, mas também coloca em risco a segurança de terceiros nas estradas. O maior risco de acidente relacionado à fadiga neste setor foi atribuído a características bem conhecidas da profissão, como as longas jornadas de trabalho e o trabalho noturno com turnos irregulares, fatores estes que limitam as oportunidades de descanso dos motoristas. Palavras-chave: Segurança; Saúde; Fadiga; Transporte Rodoviário; Motorista de Caminhão.
... The fishbone diagram ( Fig. 1) summarises the myriad of drowsiness-inducing factors that have been reported by earlier studies (Craig, Tran, Wijesuriya, & Boord, 2006;Gnardellis, Tzamalouka, Papadakaki, & Chliaoutakis, 2008;Lyznicki et al., 1998;McCartt et al., 2000;Soares et al., 2020) and we have organised these factors under the categories of environmental, physical, psychophysiological, fatigue, sleep quantity and quality and vehicle vibration. Environmental factors include a monotonous road surface, traffic flow and unchanging road conditions, and time of the day (Farahmand & Boroujerdian, 2018;Larue, Rakotonirainy, & Pettitt, 2011). ...
Introduction: Whole-body vibration has direct impacts on driver vigilance by increasing physical and cognitive stress on the driver, which leads to drowsiness, fatigue and road traffic accidents. Although sleep deprivation, sleep apnoea and alcohol consumption can also lead to driver drowsiness, exposure to steady vibration is the factor most readily controlled by changes to vehicle design, yet it has received comparatively less attention. Methods: This review investigated interrelationships between the various components of whole-body vibration and the physiological and cognitive parameters that lead to driver drowsiness, as well as the effects of vibration parameters (frequency, amplitude, waveform and duration). Vibrations transmitted to the driver body from the vehicle floor and/or seat have been considered for this review, whereas hand-arm vibration, shocks, acute or transient vibration were excluded from consideration. Results: Drowsiness is affected by interactions between the frequency, amplitude, waveform and duration of the vibration. Under optimal conditions, whole-body vibration can induce significant drowsiness within 30 min. Low frequency whole-body vibrations, particularly vibrations of 4–10 Hz, are most effective at inducing drowsiness. This review notes some limitations of current studies and suggests directions for future research. Conclusions: This review demonstrated a strong causal link exists between whole-body vibration and driver drowsiness. Since driver drowsiness has been established to be a significant contributor to motor vehicle accidents, research is needed to identify ways to minimise the components of whole-body vibration that contribute to drowsiness, as well as devising more effective ways to counteract drowsiness.
Practical Applications: By raising awareness of the vibrational factors that contribute to drowsiness, manufacturers will be prompted to design vehicles that reduce the influence of these factors.
... The disassociation in the findings of the PVT and the driving simulator suggests that the PVT is less likely to be a reliable predictor of operationally relevant performance. Considering that simulated driving is not the same as real driving as during real drives, sleep related accidents occur only after 1 h of driving (McCartt et al. 2000;Sagberg 1999) but on a driving simulator, sleepiness and performance decrements start to emerge much earlier (George 2000), these findings demonstrate the importance of implementing tasks directly relevant to the operation in future studies examining temporal changes in alertness and performance in the field. Considering that only drive violations demonstrated a similar pattern to performance on the PVT, this suggests that drive violations, also defined as events involving deliberate contraventions of safe driving practices (Parker et al. 1995), is more sensitive to sleep loss than the other measures of drive performance examined in the current study. ...
This study examined the impact of first and second night shift work on sleep and performance in mining haul truck drivers. Sleep-wake patterns were monitored using wrist actigraphy. The Karolinska Sleepiness Scale (KSS), Psychomotor Vigilance Test (PVT) and a truck simulator were administered at the start and end of the first (N1) or second (N2) night shift (19:00-07:00 h). Participants were categorised into those who demonstrated a decline in performance (increase of one or more PVT lapses [reaction time >500 msec] from the start to the end of shift) or those who did not demonstrate a decline in performance (no increase in lapses) from the start to the end of shift. Total sleep time (TST) was longer in the 24 h prior to N1 (9.05 ± 1.49 h) compared to N2 (5.38 ± 1.32 h). PVT lapses and the slowest 10% of reaction times were similar at the start and end of N1, while greater impairments on these outcomes were observed at the end of N2 compared to the end of N1 (p < .05). In contrast, subjective sleepiness was equally impaired at the end of both night shifts. PVT performance (lapses and slowest 10% of reaction times) and drive violations demonstrated a similar direction of change on N1 and N2. Participants who demonstrated a decline in performance showed reduced TST in the 48 h prior to shifts compared to those who demonstrated no decline in performance across the shift. Likely due to short sleep prior, the end of N2 was associated with pronounced performance impairments on the PVT and drive violations compared to the start of the shift. The findings suggest that drive violations may be more sensitive to sleep loss compared to the other driving measures examined in this study. This study also emphasizes the need for adequate recovery sleep between night shifts.
... France has one of the highest km/driver ratios due in part to the shortage of drivers, which is expected to increase by 20% over a 10-year period as the profession has less appeal to younger individuals. The shortage of drivers and high turnover rates may indirectly affect the health of workers because of increased pressures to meet delivery timetables and less time for leisure activity 16,17 . ...
Introduction
This study examines the health status of long-haul truck drivers
(LHTDs) and more specifically smoking and obesity, in France.
Methods
A total of 373 French and other LHTDs were randomly interviewed at
six highway rest stops. Variables recorded were self-reported sociodemographic
characteristics (age, gender, marital status, and nationality), behavioral variables
(consumption of sodas, daily exercise, smoking status), weight and height. Body
mass index (BMI) was also calculated. Statistical analysis was conducted using
chi-squared analysis and multiple logistic ordinal regression models (MLR) were
developed.
Results
The mean age was 43.4 and the largest proportion (41.2%) of respondents
were aged 40–50 years. Most respondents were French (70.3%), married (73.8%)
and did not report having an active exercise routine (66.0%). Almost two-thirds
of the drivers consumed daily 1–2 sodas (34.2%) or 3–4 sodas (33.2%). Based
on the BMI, respondents were divided into normal (34.3%), overweight (39.8%),
obese (19.5%) or morbidly obese (9.4%) categories. The mean BMI was 27.9 kg/m 2 and 51.1% of LHTDs were current or active smokers. MLR analysis revealed
that French LHTDs were more likely (OR=3.04; 95% CI: 1.62–5.69) to have a
normal BMI compared to other drivers. Smokers were significantly more likely
than non-smokers (OR=2.12; 95% CI: 1.26–3.58) to have an above normal BMI.
Conclusions
These results confirm that French and other LHTDs are at high risk of
non-communicable diseases. They also highlight the need to address the health
risks associated with smoking and obesity among LHTDs using multifaceted
strategies.
... Jung et al. (2017) specifically found that the provision of supplemental rest areas in the South Korean freeway system has led to about 14% reduction in drowsy driving crashes. Due to the potential of fatal and severe injuries, there have been particular interests in drowsy driving among long-distance truck drivers (e.g., McCartt et al. 2000;Howard et al. 2004;Rau 2005;de Pinho et al. 2006;Eskandarian et al. 2008). ...
Driver perception-reaction time and ability to sustain attention decrease as drivers become drowsy. The consequences of drowsy driving crashes are often worse on interstate highways due to the relatively high travel speeds typical on such facilities. To address the problem of driver fatigue, rest areas are often located along interstates and other long-distance highways to serve as public facilities at which motorists can take a break from driving. This paper explores the relationship between a range of crash factors and the injury severity outcomes of drowsy driving crashes on interstates in Alabama. The crash outcomes were examined in relation to interstate rest area locations. Findings from the study establish that severe injury crashes were more likely to be recorded on interstates that did not have any public rest areas. In addition, drowsy driving crashes that occurred more than 16.1 km (10 mi) away from a public rest area and those that occurred after a driver passed a rest area were more likely to record severe injuries. Other factors that were found to be associated with drowsy driving crash outcomes include unlit roadway conditions, driver gender and age, seatbelt use, location attributes of the crash site, and some temporal factors. Drowsy driving crashes involving out-of-state drivers were also found to have higher chances of recording severe injuries. Increased driver education and public campaigns are recommended as strategies to reduce drowsy driving-related crashes. While drivers should be encouraged to utilize rest areas, state officials should ensure adequate security and sanitation as well as provide amenities to make rest areas more attractive to motorists.
... Huang et al. (2013) report that truck drivers face multiple pressures such as delivering goods on time, limited rest time, traffic regulation including speed limits, maintaining their vehicles, and adverse weather conditions. McCartt et al. (2000) surveyed 593 truck drivers in the US and found occupational factors such as adverse work schedules, long working hours, and night-time driving to be a predictor of falling asleep behind the wheel. Past studies report that truck drivers perceive that physical and mental stress is induced by unsupportive workplace environments, financial pressures, worry about their families whilst away from home, and inadequate road infrastructure (Karimi Moonaghi et al., 2015;Ranjbar et al., 2016;Shattell et al., 2010). ...
Background
Heavy goods vehicle drivers are an influential driving population in Nepal, with over 90% of goods in the country are transported by road. Due to the time spent on the road, drivers have long periods of exposure to the risk of crash involvement. The study explores the perceptions and experiences of heavy goods vehicle drivers and representatives from their professional association regarding road danger.
Methods
We conducted semi-structured interviews with fifteen heavy goods vehicle drivers regularly driving on the East-West highway of Makwanpur District, Nepal. A focus group was conducted with eleven members from a major transportation entrepreneur's association in Nepal. The focus group and interviews were audio-recorded, transcribed, translated, and analyzed using thematic analysis.
Results
Four themes were developed- assumptions of blame; perceptions of safety culture in the trucking industry; influence of road infrastructure; and behaviours of road users. The road and traffic environment, enforcement, and the safety culture in the heavy vehicle industry not only influenced the attitudes of the road users towards traffic safety but also legitimized and encouraged behaviours that affect safety. General and industry-related road safety improvements suggested by participants included: making provision for heavy good vehicles parking areas, separating the highway with a median strip, improving crash investigation capacity, conducting road safety awareness and training programs, strictly enforcing the speed limit and laws about driving under the influence of alcohol/drugs, and formulating strategies to create a safe, supportive working environment in the heavy vehicle industry.
Conclusion
Heavy goods vehicle drivers and members of the professional association can provide rich information regarding the barriers and facilitators of road risk in Nepal. Their perceptions and opinions can contribute to devising interventions at individual, societal, organizational, and governmental levels, and inform efforts to develop a positive safety culture within the heavy vehicle transport industry.
... Many studies point to possible causes of drowsiness or at-risk groups of drivers [7]. The causes of drowsiness are generally known today; this also applies to risk groups of drivers such as night shift workers, truck drivers [8] and so on [9,10]. The less serious consequences of drowsiness end up as material damage to vehicles or public property. ...
Driver fatigue can be manifested by various highly dangerous direct and indirect symptoms, for example, inattention or lack of concentration. The aim of the study was to compare the behavior of young drivers, older drivers and professional drivers, particularly in situations where they feel fatigued. In the online questionnaire, drivers answered various questions which analysed their responsibility of driving a car during fatigue, the optimum temperature in the car, or experience with microsleep. The sample of drivers consisted of 507 women and 951 men in Slovakia. Young drivers are more responsible when driving during fatigue, while professional drivers take risks, break the law, and drive tired more often. A total of 25% of all drivers experience fatigue more than once a week. Adverse results were found in connection with driving and fatigue, where more than 42% of respondents stated that their duties require them to drive even when they are tired. A total of 27% of drivers have had microsleep while driving. The survey showed that drivers are aware that thermoneutral temperature in a car interior can improve driving performance and a lower temperature can positively affect a person’s attention. The regulation of the temperature in the car was helpful for 75% of all drivers when they felt tired, and more than 97% of the drivers lowered the temperature in the interior of the vehicle in order to achieve a better concentration. In addition to standard statistical methods, a neural network was used for the evaluation of the questionnaire, which sought for individual connections and subsequent explanations for the hypotheses. The applied neural network was able to determine parameters such as the age of the driver and the annual raid as the riskiest and closely associated with the occurrence of microsleep between drivers.
... Regarding the effects of work on driving, we found very few articles, and most refer to professional drivers [28]. However, the relationship between working hours, fatigue, and the risk of traffic accidents is clear [29]. There are many workers who are not professional drivers but use their vehicles to travel to work. ...
A large percentage of traffic accidents are due to human errors. Driving behavior and driving stress influence the probability of making these mistakes. Both are influenced by multiple factors, among which might be elements such as age, gender, sleeping hours, or working hours. The objective of this paper is to study, in a real scenario and without forcing the driver’s state, the relationship between driving behavior, driving stress, and these elements. Furthermore, we aim to provide guidelines to improve driving assistants. In this study, we used 1050 driving samples obtained from 35 volunteers. The driving samples correspond to regular commutes from home to the workplace. ANOVA and ANCOVA tests were carried out to check if there are significant differences in the four factors analyzed. Although the results show that driving behavior and driving stress are affected by gender, age, and sleeping hours, the most critical variable is working hours. Drivers with long working days suffer significantly more driving stress compared to other drivers, with the corresponding effect on their driving style. These drivers were the worst at maintaining the safety distance.
... Research conducted in India also showed that truck drivers with unsuitable working conditions and under economic pressures have to drive for longer hours to earn more income, and as such they have more crashes [16]. McCartt et al. study in New York revealed that working conditions of truck drivers represent one of the main predictive factors for crashes [18]. Also, La et al. in Vietnam as well as Lim and Chia in Singapore found that working conditions of drivers such as working hours and their level of income influence the number and severity of crashes [19,20]. ...
Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this purpose, 780 Iranian truck drivers were interviewed by validated questionnaires including insomnia severity index (ISI), attention related driving errors scale (ARDES), and driving anger expression (DAX). To confirm the validity of these questionnaires, confirmatory factor analysis (CFA) was used. Next, structural equation modeling (SEM) was employed for investigating the relationships between these latent variables and truck drivers' demographic characteristics, working conditions and their crash involvement. SEM results indicated that as the severity of insomnia among drivers increased, they committed more inattention-related errors, and also expressed more anger during driving. Generally, the results of this study indicated that with increase in the extent of experience and safety knowledge of drivers and improvement in their working conditions and their sleep status, it is possible to reduce inattention-related error and expression of anger during driving among heavy vehicle drivers.
... Obese truckers have a twofold higher accident-involvement rate compared with their non-obese counterparts (Roberts & York, 2000). In a road safety survey, 25% of truckers reported falling asleep at the wheel in the past year and 47% reported the same at some time in their careers (McCartt, Rohrbaugh, Hammer, & Fuller, 2000). Finally, sleep debt resulting from semi-chronic, partial sleep restriction has additional metabolic and endocranial repercussions, leading to increased risks for obesity, pre-diabetic states, and impaired immune functions (Ayas et al., 2003;Buxton, Spiegel, & van Cauter, 2002). ...
A critical review was conducted of social, psychological, and health science literature on the array of health risks and morbidities of truckers. Multilevel worksite-induced strains (e.g., long work hours and fatigue, shift work and sleep deprivation, postural fatigue and exposure to noise and vibration, sedentary lifestyle and unhealthy diet, exposure to diesel exhaust fumes, and other occupational stressors) were categorized into six primary morbidities for truckers: (1) psychological and psychiatric disorders; (2) detriments resulting from disrupted biological cycles; (3) musculoskeletal disorders; (4) cancer and respiratory morbidities; (5) cardiovascular disease; and (6) risk-laden substance use and sexual practices. Elevated morbidity risks suggest the need for the design and implementation of systematic epidemiological research and environmental interventions in the transport sector.
Study Objectives
The effectiveness of advanced emergency braking systems (AEBS) in preventing drowsy driving-related truck collisions remains unclear. We aimed to evaluate the damage-mitigation effect of AEBS on drowsy driving-related collisions involving large trucks using collision rate and damage amount.
Methods
Data collected by a Japanese transportation company from 1,699 collisions involving 31,107 large trucks over 7 years were analyzed post-hoc. The collision rate (number of trucks with collisions/total number of trucks) and damage amount (total amount of property damage and personal injury) were compared based on whether the collisions were caused by drowsy or non-drowsy driving and whether the trucks were equipped with AEBS or not.
Results
For all and non-drowsy driving-related collisions, the collision rate for the 12,887 trucks with AEBS (1.62 and 1.20 collisions/truck/7 years, respectively) was significantly lower than that for the 18,220 trucks without AEBS (1.94 and 1.56 collisions/truck/7 years, respectively) (p=0.04 and p=0.008, respectively). However, for drowsy driving-related collisions, the collision rate did not significantly differ between trucks with and without AEBS. The damage amount in neither type of collision (drowsy vs. non-drowsy) significantly differed between trucks with and without AEBS.
Conclusions
Regarding the collision rate of large trucks, AEBS was effective in non-drowsy driving-related collisions, but not in collisions involving drowsy driving. The damage amount was not mitigated for trucks with and without AEBS regardless of the collision type. The limited effect of AEBS for damage-mitigation suggests the need for combined use with other safety-support systems that intervene in driving operations.
This study assessed daytime sleepiness in young adults, including individuals with idiopathic hypersomnia (IH) and narcolepsy (NA), using subjective and objective measures. The participants included adults (N = 42): 13 with IH, 10 with NA, and 19 with healthy controls (HC). We excluded HC participants with a score of ≥11 on the Japanese version of the Epworth Sleepiness Scale. Participants underwent nocturnal polysomnography in a sleep laboratory, followed by administration of the Japanese version of the Karolinska Sleepiness Scale (KSS-J) before each session of the Multiple Sleep Latency Test (MSLT) the next day. We divided HC participants into two groups based on their mean sleep latency on the MSLT: low sleep propensity (low SP; ≥8 min) and high sleep propensity (high SP; <8 min). The high SP group demonstrated a discrepancy between subjective and objective sleepiness. The correlation between KSS-J scores and sleep latency in each nap trial was low and varied by the group. A significant proportion of HC individuals in the high SP group exhibited shorter sleep latency similar to those with IH or NA despite not experiencing subjective sleepiness. We concluded that some healthy individuals show objective signs of sleepiness comparable to those with hypersomnia or narcolepsy, even without reporting subjective sleepiness, underscoring the significance of using subjective and objective measures to assess daytime sleepiness.
The extant transport literature suggests that truck driver fatigue is a leading contributor in truck crashes. Various factors are known to affect a truck driver's ability to comply with work and rest requirements, including long working hours, irregular work schedules, sleep deprivation and driving at night. In Australia, while control measures restrict the number of hours of work a truck driver may undertake without rest, they travel vast distances and work with a high level of autonomy. This makes it difficult for transport companies to monitor and manage truck drivers' work and rest compliance; thereby relying on them to self-manage driver fatigue at designated rest-stops. However, there is little Australian research examining rest-stop behaviour of truck drivers in relation to driver fatigue compliance. To better understand how truck drivers manage driver fatigue, an exploratory participant observation study of truck drivers (N = 378) was un-dertaken at two Australian truck rest stops in rural New South Wales. The findings indicate that while most truck drivers comply with rest requirements regarding driver fatigue, load type, driver changeovers, access to parking, and time spent on work-related activities at the rest areas affects the time truck drivers spend at rest, and these factors are likely to increase the risk of truck drivers not complying with driver fatigue regulation. They are also likely to increase the number of truck drivers involved in fatigue related crashes.
Drowsiness while driving negatively impacts road safety, especially in truck drivers. The present study investigated the feasibility and alerting effects of a daylight-supplementing in-truck lighting system (DS) providing short-wavelength enriched light before, during, and after driving. In a within-participants design, eight truck drivers drove a fully-loaded truck under wintry Scandinavian conditions (low daylight levels) with a DS or placebo system for five days. Subjective and objective measures of alertness were recorded several times daily, and evening melatonin levels were recorded three times per study condition. DS significantly increased daytime light exposure without causing negative side effects while driving. In addition, no negative carry-over effects were observed on evening melatonin and sleepiness levels or on nighttime sleep quality. Moreover, objective alertness (i.e., psychomotor vigilance) before and after driving was significantly improved by bright light exposure. This effect was accompanied by improved subjective alertness in the morning. This field study demonstrated that DS was able to increase daytime light exposure in low-daylight conditions and to improve alertness in truck drivers before and after driving (e.g., during driving rest periods). Further studies are warranted to investigate the effects of daylight-supplementing in-cabin lighting on driving performance and road safety measures.
Background:
Slow eye movements (SEMs), which occurs during eye-closed periods with high time coverage rate during simulated driving process, indicate drivers' sleep onset.
New method:
For the multi-scale characteristics of slow eye movement waveforms, we propose a multi-scale one-dimensional convolutional neural network (MS-1D-CNN) for classification. The MS-1D-CNN performs multiple down-sampling processing branches on the original signal and uses the local convolutional layer to extract the features for each branch.
Results:
We evaluate the classification performance of this model on ten subjects' standard train-test datasets and continuous test datasets by means of subject-subject evaluation and leave-one-subject-out cross validation, respectively. For the standard train-test datasets, the overall average classification accuracies are about 99.1% and 98.6%, in subject-subject evaluation and leave-one-subject-out cross validation, respectively. For the continuous test datasets, the overall average values of accuracy, precision, recall and F1-score are 99.3%, 98.9%, 99.5% and 99.1% in subject-subject evaluation, are 99.2%, 98.8%, 99.3% and 99.0% in leave-one-subject-out cross validation.
Comparison with existing method:
Results of the standard train-test datasets show that the overall average classification accuracy of the MS-1D-CNN is quite higher than the baseline method based on hand-designed features by 3.5% and 3.5%, in subject-subject evaluation and leave-one-subject-out cross validation, respectively.
Conclusions:
These results suggest that multi-scale transformation in the MS-1D-CNN model can enhance the representation ability of features, thereby improving classification accuracy. Experimental results verify the good performance of the MS-1D-CNN model, even in leave-one-subject-out cross validation, thus promoting the application of SEMs detection technology for driver sleepiness detection.
High-speed train (HST) is a fast, reliable, and environmental-friendly transportation means for medium to long-distance travel. HST drivers need to continuously keep alert for a few hours, detect potential hazards in time and make quick reactions, and strictly follow standard operating procedures. The objectives of this study were to identify the key factors that are related to HST drivers' operation performance, to propose a validated prediction model, and to provide practical management suggestions to improve performance. Six focus groups with 22 HST drivers and 18 frontline managers and a questionnaire survey with 243 HST drivers were conducted to collect qualitative and quantitative data concerning the potential influencing factors. A prediction model with seven key predictors was then developed and validated to distinguish high and low-performance HST drivers. Accordingly, management guidelines were proposed based for HST frontline managers to improve their drivers' operation performance by optimizing the three scheduling factors, such as adjusting sleep duration, intermittent rest duration, and HST-type switching frequency; and managing the four non-scheduling factors, such as periodically checking HST drivers’ health condition, frustration, and fatigue, and providing corresponding interventions.
Ensuring motor carriers comply with safety rules is critical to the efficient workings of supply chains and the safety of the motoring public. However, little is understood regarding how carriers respond to changes in the likelihood of inspection (a.k.a., "crackdowns") undertaken by the Department of Transportation. Drawing on the regulatory compliance and criminology literatures, we extend the rational cheater explanation that undergirds carrier safety research by incorporating principles from attention-based theory to devise new theoretical predictions regarding how carriers respond to announced versus unannounced inspection crackdowns. To test our theory, we rely on exogenous variation in the probability of inspection from the DOT's use of announced and unannounced inspection "blitzes." We test predictions using a longitudinal dataset of nearly 10 million truck inspections from 2012 to 2016. We find firms with lower costs of compliance and higher costs of avoiding inspections improve compliance prior to and during announced blitzes. Small firms with lower costs of avoidance tend to avoid announced blitzes. Unannounced blitzes result in no changes in compliance or avoidance, providing evidence that awareness is driving our results.
Kazalarda yaşamlarını kaybedenlerin yarıdan fazlası yolcu otobüsü veya nakliye araçlarının sürücüleri ya da yolcularıdır. Profesyonel sürücülerin yaşamlarını yitirdikleri kazaların oranı diğer Güney Avrupa ülkelerinde çok daha düşüktür. Trafik kaza analizleri, insan faktörünün, kazaların %90’ında ana ya da yardımcı faktör olduğunu göstermiştir. Hayati yetilerin bazıları yaşın artmasıyla birlikte gerilemekte ve ilk belirtiler genellikle 55 yaşı başlarında ortaya çıkmaktadır. Farklı nörolojik durumlar ve görsel işlev bozuklukları araç kullanma becerisinde hatırı sayılır düşüşlere, kaza riskinde ise artışlara yol açabilmektedir. Çünkü, nöropsikolojik ve görsel işlevlerdeki gerileme yavaş yavaş ve belli durumlarda olmakta, sürücünün kendisi bile durumunun farkında olmamakta ve araç kullanma becerilerindeki bozulmalar genelde çok geç fark edilmektedir. Literatüre göre, yaşlı sürücüler, diğer sürücü gruplarından daha sık ölümlü kazalar ve özellikle kavşak kazaları yapmaktadır. Sıradan (amatör) sürücülerin aksine, profesyonel yaşlı sürücüler, birkaç görevin eş zamanlı yapılmasının gerektiği zorlu ve karmaşık durumlardan kaçınamazlar. Dolayısıyla, profesyonel yaşlı sürücülerin bilişsel ve görsel yetilerinin uygun beceri testleriyle düzenli olarak değerlendirilmesi hayatidir. Bu çalışmada, 120 (50yaş üzeri) Türk ve yaklaşık 100 Fin profesyonel yaşlı sürücünün araç kullanımına uygunluğu klinikte değerlendirilmiştir. Değerlendirme, görüş testlerini, nöropsikolojik testleri, sağlık taramasını, psikolojik envanterleri ve araç kullanmayla ilgili envanter ve testleri içermektedir.
Sleepiness is a common human factor among truck drivers resulting from sleep loss or time of day and causing impairment in vigilance, attention, and driving performance. While driver sleepiness may be associated with increased risk on the road, sleepy drivers may drive more cautiously as a result of risk-compensating behaviour. This endogeneity has been overlooked in the previous driver behaviour studies and may provide new insight into the effects of sleepiness on driving performance. In addition, the Karolinska Sleepiness Scale (KSS) has been widely used to quantify sleepiness. However, the KSS is a subjective self-reported measure and is reliant on honest reporting and understanding of the scale. An alternative way of quantifying sleepiness is using drivers’ heart rate and correlating it with their sleepiness. While recent advances in data collection technologies have made it possible to collect heart rate data in real-time and in an unobtrusive way, their application in measuring sleepiness particularly among truck drivers has been unexplored.
This study aims to address these gaps and contribute to analytic methods in road safety research by collecting truck drivers’ heart rate data in real-time, measuring sleepiness from those data, and using it in an instrumental variable modelling framework to investigate its effect on driving performance. To this end, a driving simulator experiment was conducted in Belgium and heart rate data were collected for 35 truck drivers via sensors installed on the steering wheel of the simulator. Additional demographic data were collected using a questionnaire before the experiment. An instrumental variable model consisting of a discrete binary logit and a continuous generalized linear model with grouped random parameters and heterogeneity in their means was then developed to study the effects of driver sleepiness on headway. Results indicate that age, years of holding driver licence, road type, type of truck transport, and weekly distance travelled are significantly associated with sleepiness among the participants of this study. Sleepy driving is associated with reduced headway for 30.5% of the drivers and increased headway for the other 69.5%, and night-time shift is associated with such varied effects. These findings indicate that there may be group- or context-specific risk patterns which cannot be explicitly addressed by hours of service regulations and therefore, transport operators, driver trainers and fleet managers should identify and handle such context-specific high risk patterns in order to ensure safe operations.
Slow eye movements (SEMs) indicate sleep onset period but are rarely studied in the field of driver fatigue detection. Through visual observation and statistical analysis we find that SEMs occur during eye-closed periods and have a high overall coverage rate during driving, which makes it feasible to utilize detecting SEMs to recognize drivers’ sleep onset period. To detect SEMs, we adopt a bimodal Long Short-Term Memory (LSTM) network to deal with temporal information and multimodal information in physiological signals. To extend the distinguishing information, we define a novel horizontal sum (HSUM) signal, which is sum of signals from two horizontal electrooculogram (EOG) channels. Electroencephalogram (EEG)-related features are extracted from the HSUM signal in contrast to those from the traditional O2 signal. EOG features are extracted from the horizontal EOG (HEOG) signals. The results demonstrate that features from multimodal signals (HSUM and HEOG signals, or O2 and HEOG signals) achieve better classification results than features from the single HEOG signal. And the EEG-related features extracted from self-defined HSUM signals achieve comparable results to those from traditional O2 signals, thus avoiding using extra O2 channel. The proposed method of detecting SEMs using the bimodal LSTM to classify features from HSUM and HEOG signals achieves the average F-score of 76.5%, which is higher than the classic support vector machine by 7.5%. This method of detecting SEMs using only two channels helps to build a user acceptable and feasible system for recognizing drivers’ sleep onset period.
The advance of automated driving allows the users to engage in non-driving related activities such as sleeping. However, until full automation is reached, the user may have to interact with the vehicle, for example, in planned take-overs, which requires the user to be awake and conscious. To evaluate auditory and visual awakening concepts (alarm, fading in 5, and fading in 20s), we conducted a between-subject (N=45) Virtual Reality study, in which participants dozed/slept for 15min, were then awoken, and then had to complete an ordering, a stroop, and a counting task. We only found a significant difference in the perceived sleep duration, which was highest in the alarm condition.
Insufficient sleep is a prominent problem in modern society with several negative effects and risks. One of the most serious consequences is traffic accidents caused by drowsy driving. Current solutions are focused on detecting drowsiness, where individuals need to reach a certain drowsiness level to receive an alarm, which may be too late to react. In this context, it is relevant to develop a wearable system that integrates the prediction of drowsiness and its prevention. By predicting the drowsy state, the driver can be warned in advance while still alert. To minimize further incidents, the reason why a state of drowsiness occurs must be identified, caused by a sleep disorder or sleep deprivation. The contribution of this work is to review the main scientific and commercial solutions, and perform automatic sleep staging based on heart rate variability. Results show that, although promising, this approach requires a larger dataset to consider a user-dependent scenario.
Driving is a complicated process that demands coordination between a range of neurocognitive functions, including attention, visuo-perception, and appropriate judgment, as well as sensory and motor responses. Therefore, several factors may reduce the driving performance of an individual, such as sleepiness, distraction, overspeeding, alcohol consumption, and sedative drugs, all of which increase the hazard of motor vehicle accidents. Among them, drowsy driving is a major cause of traffic accidents, leading to more serious injuries as compared to other causes of major traffic accidents. Although sleep disorders have been highly associated among drowsy drivers, they are often untreated and unrecognized as a disease. In particular, obstructive sleep apnea and narcolepsy are some sleep disorders that are highly related to traffic accidents. Insomnia, which can cause inadequate sleep duration and promote sedative effects from sleeping pills, may also cause traffic accidents. These conditions are especially applicable to commercial bus or truck drivers, nocturnal workers, and shift workers, who are highly vulnerable to drowsy driving. Therefore, assertive screening and management of sleep disorders are necessary in general private drivers and relevant occupational drivers.
Safety assessment among sleep-deprived drivers is a challenging research area with only a few sleep-related studies investigating safety performance during car-following. Therefore, this study aimed to measure the effects of partial sleep deprivation on driver safety during car-following. Fifty healthy male drivers with no prior history of any sleep-related disorders, drove the driving simulator in three conditions of varying sleep duration: a baseline (no sleep deprivation), test session (TS1) after one night of PSD (sleep ≤4.5 h/night) and TS2 after two consecutive nights of PSD. The reduced sleep in PSD sessions was monitored using an Actiwatch. Karolinska Sleepiness Scale was used to indicate loss of alertness among drivers. Each drive included a car-following task to measure longitudinal safety indicators based on speed and headway management: normalized time exposed to critical gap (TECG’), safety critical time headway and speed variability with respect to leading vehicle’s speed (SPV). Crash potential index (CPI) was also determined from deceleration rate of drivers during car-following and was found correlated with other indicators. Therefore, to determine the aggregate influence of PSD on safety during car-following, CPI was modelled in terms of TECG, SPV, THW and other covariates. All safety metrics were modelled using generalized mixed effects regression models. The results showed that compared to the baseline drive, critical time headway decreased by 0.65 and 1.08 times whereas speed variability increased by 1.34 and 1.28 times during the TS1 and TS2, respectively, both indicating higher crash risk. However, decrease in TECG’ by 64 % and 56 % during TS1 and TS2, respectively indicate compensatory measures to avoid risks due to sleep loss. A fractional regression model of crash potential revealed that low time-headway and higher speed variability and high time exposed to critical gap (TECG’) significantly contribute to higher CPI values indicating higher safety risk. Other covariates such as sleep duration, professional driving experience and history of traffic violations were also associated with safety indicators and CPI, however no significant effects of age were noticed in the study. The study findings present the safety indicators sensitive to rear-end crashes specifically under PSD conditions, which can be used in designing collisions avoidance systems and strategies to improve overall traffic safety.
Background:
There are over 12,000 professional truck drivers in the Canadian Maritime provinces, with the majority being in New Brunswick and Nova Scotia. Previous studies have focused on the health of Canadian and American truck drivers but the occupational health status of truck drivers in the Maritime Provinces remains undocumented.
Objective:
The objective of this cross-sectional study was to provide a general, occupational health and demographic characteristics description of professional truck drivers in the Maritimes.
Methods:
One-hundred and four male truck drivers from the Canadian Maritime Provinces volunteered for this study. Nine occupational health indicators were measured (seven were self-reported via questionnaire and two were physical measurements). Participants self-reported their age, years of truck driving experience and education.
Results:
Only one-quarter of the current sample had no health conditions. In contrast, more than half were obese, one third had back problems, and one-sixth had a high risk of developing cardiovascular disease (CVD). The group comparison analysis showed that the group without health condition were younger and more educated than the group with multiple health conditions. For this study, age and low rate of education were associated with an increased number of health conditions.
Conclusions:
Similar to health profiles of other populations of North American truck drivers, this study suggests that the majority of truck drivers in the Canadian Maritime Provinces have at least one poor indicator of occupational health.
The study is to assess road infrastructural damage occasioned by heavy vehicles and their associated costs. The researchers used a systematic pavement damage estimation procedure that synthesised several existing methodologies, including the Highway Economic Requirements System (HERS) and American Association of State Highway and Transportation Officials (AASHTO) methods. The highway section of Lokoja-Abuja, Ilorin-Jebba and Abakiliki-Ogoja via Mbok roads were surveyed, and data were collected through the axle-load survey, automatic traffic count and from secondary sources. The rate of gross vehicle weight violation, ranging from 20% to 94% of the axle load distribution were seen across the studied network. The heaviest overload of 94% of the 6-axle vehicles plying at the Lokoja-Abuja road could explain this intense damaging effect on the road pavement. Upon aggregation, the benchmark average annual maintenance costs per kilometre in Nigeria stands at ₦143,182,853.55, while average per-km yearly maintenance costs attributed to HGV traffic is ₦101,385,881.57. Thus, the unit damage cost per ESAL-km computed at ₦5.65, ₦5.70 and ₦0.74 for Lokoja-Abuja, Ilorin-Jebba, and Abakiliki-Ogoja roads, respectively. Hence, the benchmark per-equivalent single axle loads unit cost for the Nigerian roads is ₦4.03. This figure represents the damaging benchmark cost of overload per equivalent single axle loads (ESAL) on the Nigerian road. It hence becomes the basis for control of excessive axle-load violations on the Nigerian roads.
A literature review, a nationwide survey of commercial truck and bus driver work patterns, an analysis of accident data, and three extensive field experiments were conducted to establish evidence concerning driver fatigue.
The recent increase in the incidence of shiftwork has been accompanied by a change in the type of task typically performed by the shiftworker. The technological advances which have produced both these effects have meant that the shiftworker is more likely to be engaged in cognitive, mentally taxing tasks than the predominantly perceptual-motor ones typical of earlier times. Contemporary research on time of day effects in performance efficiency has indicated that these task changes may be crucially important in determining on-shift performance, and hence the choice of the individual and shift system that is most suitable. Evidence is reviewed on task demands, the effects of different shift systems, and the role of individual differences. A descriptive model is proposed in which on-shift performance is seen to be dependent on the type of task, type of shift system, and type of person, with the three factors interacting via the worker's various circadian rhythms.
A hospital-based survey on shift work, sleep, and accidents was carried out among 635 Massachusetts nurses. In comparison to nurses who worked only day/evening shifts, rotators had more sleep/wake cycle disruption and nodded off more at work. Rotators had twice the odds of nodding off while driving to or from work and twice the odds of a reported accident or error related to sleepiness. Application of circadian principles to the design of hospital work schedules may result in improved health and safety for nurses and patients.
The development and use of a new scale, the Epworth sleepiness scale (ESS), is described. This is a simple, self-administered questionnaire which is shown to provide a measurement of the subject's general level of daytime sleepiness. One hundred and eighty adults answered the ESS, including 30 normal men and women as controls and 150 patients with a range of sleep disorders. They rated the chances that they would doze off or fall asleep when in eight different situations commonly encountered in daily life. Total ESS scores significantly distinguished normal subjects from patients in various diagnostic groups including obstructive sleep apnea syndrome, narcolepsy and idiopathic hypersomnia. ESS scores were significantly correlated with sleep latency measured during the multiple sleep latency test and during overnight polysomnography. In patients with obstructive sleep apnea syndrome ESS scores were significantly correlated with the respiratory disturbance index and the minimum SaO2 recorded overnight. ESS scores of patients who simply snored did not differ from controls.
Following the 1986 annual meeting of the Association of Professional Sleep Societies (Columbus, Ohio, U.S.A., June 15–22, 1986), a committee of scientists was formed to review recent reports and related information on the role of human sleep and brain clocks (time-of-day variation in physiology and alertness) in the occurrence of medical and human error catastrophes. This is a report of the committee's findings and recommendations.
This study assesses a possible independent effect of sleep-related breathing disorders on traffic accidents in long-haul commercial truck drivers. The study design included integrated analysis of recordings of sleep-related breathing disorders, self-reported automotive and company-recorded automotive accidents. A cross-sectional population of 90 commercial long-haul truck drivers 20-64 years of age was studied. Main outcome measures included presence or absence, as well as severity, of sleep-disordered breathing and frequency of automotive accidents. Truck drivers identified with sleep-disordered breathing had a two-fold higher accident rate per mile than drivers without sleep-disordered breathing. Accident frequency was not dependent on the severity of the sleep-related breathing disorder. Obese drivers with a body mass > or = 30 kg/m2 also presented a two-fold higher accident rate than nonobese drivers. We conclude that a complaint of excessive daytime sleepiness is related to a significantly higher automotive accident rate in long-haul commercial truck drivers. Sleep-disordered breathing with hypoxemia and obesity are risk factors for automotive accidents.
Fatigue and sleep deprivation are important safety issues for long-haul truck drivers.
We conducted round-the-clock electrophysiologic and performance monitoring of four groups of 20 male truck drivers who were carrying revenue-producing loads. We compared four driving schedules, two in the United States (five 10-hour trips of day driving beginning about the same time each day or of night driving beginning about 2 hours earlier each day) and two in Canada (four 13-hour trips of late-night-to-morning driving beginning at about the same time each evening or of afternoon-to-night driving beginning 1 hour later each day).
Drivers averaged 5.18 hours in bed per. day and 4.78 hours of electrophysiologically verified sleep per day over the five-day study (range, 3.83 hours of sleep for those on the steady 13-hour night schedule to 5.38 hours of sleep for those on the steady 10-hour day schedule). These values compared with a mean (+/-SD) self-reported ideal amount of sleep of 7.1+/-1 hours a day. For 35 drivers (44 percent), naps augmented the sleep obtained by an average of 0.45+/-0.31 hour. No crashes or other vehicle mishaps occurred. Two drivers had undiagnosed sleep apnea, as detected by polysomnography. Two other drivers had one episode each of stage 1 sleep while driving, as detected by electroencephalography. Forty-five drivers (56 percent) had at least 1 six-minute interval of drowsiness while driving, as judged by analysis of video recordings of their faces; 1067 of the 1989 six-minute segments (54 percent) showing drowsy drivers involved just eight drivers.
Long-haul truck drivers in this study obtained less sleep than is required for alertness on the job. The greatest vulnerability to sleep or sleep-like states is in the late night and early morning.
Objective. - To assess the contribution of driver sleepiness to highway crashes and review recent recommendations to change federal hours-of-service regulations for commercial motor vehicle drivers. Data Sources. - Information was derived from a search on the MEDLINE, Transportation Research Information Service (TRIS), and Bibliographic Electronic Databases of Sleep (BEDS) databases from 1975 through 1997 and from manual review of the reference lists in relevant journal articles, government publications, conference proceedings, and textbooks. Data Synthesis. - Driver sleepiness is a causative factor in 1% to 3% of all US motor vehicle crashes. Surveys of the prevalence of sleepy behavior in drivers suggest that sleepiness may be a more common cause of highway crashes than is reflected in these estimates. About 96% of sleep-related crashes involve passenger vehicle drivers and 3% involve drivers of large trucks. Risk factors include youth, shift work, alcohol and other drug use, over-the-counter and prescription medications, and sleep disorders. Conclusions. - Increased awareness of the relationship between sleepiness and motor vehicle crashes will promote the health and safety of drivers and highway users. Physicians can contribute by encouraging good sleep habits, recognizing and treating sleep-related problems, and counseling patients about the risks of driving while sleepy. To protect public health and safety, the American Medical Association recommends continued research on devices and technologies to detect signs of sleepiness and prevent the deterioration of driver alertness and performance. Educational programs about the risks of falling asleep while driving are needed for physicians, the public, and commercial truck drivers.
6 Ss worked a full day, mainly on vigilance and calculation tests, for 2 successive days in each of 6 successive wk. On the preceding nights they were allowed 0, 1, 2, 3, 5, or 7.5 hr. sleep varying according to the week of testing. Less than 5 hr. sleep on a single night impaired vigilance; less than 3 hr. impaired calculation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Compared accident rates for 46 patients with mild–severe sleep apnea (SA) with rates for all licensed drivers in Virginia, using records for 1981–1985. Accident rates increased with the severity of SA, and rates for the severe SA group were significantly greater than rates for all drivers. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Sleep and daytime sleepiness were evaluated in 10 young adult subjects to determine whether restricting nocturnal step by a constant amount produces cumulative impairment. Subjects were studied for 12 consecutive days, including 3 baseline days with a 10-hr time in bed, 7 days with sleep restricted to 5 hrs, and 2 recovery days. In 5 subjects, recovery included a 10-hr time in bed; in the remaining subject, recovery induced a 5-hr time in bed with a 1-hr daytime nap. Sleepiness was measured using two self-rating scales and the multiple sleep latency test. During sleep restriction, nocturnal stage 2 and REM sleep were reduced and slow wave sleep was unaffected. Stanford Sleepiness Scales showed an immediate increase in daytime sleepiness that reached a plateau after 4 days. An analog sleepiness rating scale showed increased sleepiness after 2 restricted nights and leveled off after the fourth restricted night. The multiple sleep latency tests showed no effect of sleep restriction until the second day, followed by a progressive increase in sleepiness that persisted through the seventh sleep restriction day. During the recovery period, daytime sleepiness returned to basal values on all three measures following one full night of sleep; with a daytime nap, no further cumulative effects of sleep restriction were seen.
Fatigue and long driving hours have been implicated as risk factors in truck crashes. Under federal regulations, commercial drivers are permitted to drive no more than 10 hours before having an 8-hour break and cannot work more than 70 hours over an 8-day period. Several studies have suggested that violations of these rules are common. A survey of long haul tractor-trailer drivers was conducted to estimate what proportion of drivers report that they regularly violate the hours-of-service rules and to identify the drivers most likely to commit hours-of-service violations. During December 1990 through April 1991, a total of 1,249 drivers were interviewed at truck safety inspection stations, truck stops, and agricultural inspection stations in Connecticut, Florida, Oklahoma, and Oregon. In each state, interviews were conducted during varying periods of the day over the course of seven days at inspection stations. Overall, 89 percent of eligible drivers asked for interviews participated in the survey. According to self-reports, almost three-fourths of the respondents violate hours-of-service rules. About two-thirds of the drivers reported that they routinely drive or work more than the weekly maximum. A primary impetus for violating rules appears to be economic factors, including tight delivery schedules and low payment rates. Many other driver, job, and vehicle characteristics were significantly associated with being an hours-of-service violator. The high prevalence of hours-of-service violations among tractor-trailer drivers is a problem in need of urgent attention. Potential measures to reduce the prevalence of rules violations include more enforcement directed toward carriers, wider use of electronic recorders, and increasing the number of rest areas.
Three experiments which utilized an ultrashort sleep-waking cycle were conducted to investigate the 24 h structure of sleepiness after 1 night of sleep deprivation under 2 experimental conditions: instructing subjects to attempt to fall asleep or instructing subjects to attempt to resist sleep. Six subjects participated in experiment 1. At 19.00 h they started a 13 min waking-7 min sleep attempt, or 13 min waking-7 min resisting sleep, until 19.00 h on the next day. Eight subjects were tested in a similar way in experiment 2, which started at 07.00 h after a night of sleep deprivation and lasted for 24 h. Eight subjects were similarly tested in experiment 3 which started at 11.00 h after a night of sleep deprivation and lasted for 36 h until 23.00 h on the next day. The results showed that in spite of the significant between-group differences in total sleep, the temporal structure of sleepiness was very similar in the 3 experiments. In each there was a bimodal distribution of sleepiness: a major nocturnal sleepiness crest and a secondary mid-afternoon sleepiness peak. These were separated by a 'forbidden zone' for sleep centred at around 20.00-22.00 h. The onset of the nocturnal sleep period (the sleep gate) was found to be a discrete event occurring as an 'all or none' phenomenon. Its timing was stable over a 2 week period, and independent of the specific experimental demands; there were no significant differences between the AS and RS conditions with respect to total sleep time or any of the sleep stages. These results, which demonstrate structured variations in sleepiness across the nycthemeron are discussed in the light of the recent modelling of sleep along homeostatic principles.
Sleep-related motor vehicle accidents are a serious safety hazard both for the driver who falls asleep and for others on the road. Sleep disorders may be significant contributing factor in some of these accidents. We reviewed data on sleep-related accidents from 70 control subjects and 424 adults with four categories of sleep disorders: sleep apnea, narcolepsy, other disorders of excessive sleepiness, and sleep disorders without excessive sleepiness. The proportion of individuals with sleep-related accidents was 1.5-4 times greater in the hypersomnolent patient groups than in the control group. In patients with hypersomnia, the incidence of sleep-related accidents per year of excessive sleepiness was 3-7%. Although the proportion of patients with sleep-related accidents was highest in narcoleptics, apneics were involved in more sleep-related accidents because of their greater number. Apneics and nacroleptics accounted for 71% of all sleep-related accidents. The proportion of severe apneics who had sleep-related accidents was almost twice that of patients with mild or moderate apnea. Mean sleep latency by Multiple Sleep Latency Test did not differ significantly in patients with accidents and those without. Patients with a wide variety of sleep disorders appear to be at increased risk for sleep-related accidents. The severity and duration of hypersomnia are probably not the only factors that contribute to that risk. These findings have implications for the management of patients with sleep disorders.
Although patients with obstructive sleep apnea often report falling asleep while driving, the frequency of auto accidents involving these patients has not been rigorously studied. Therefore, we compared the driving records of 29 patients with obstructive sleep apnea with those of 35 subjects without sleep apnea. The patients with sleep apnea had a sevenfold greater rate of automobile accidents than did the subjects without apnea (p less than 0.01). The percentage of persons with one or more accidents was also greater in the patients with apnea than in the control subjects without apnea (31% versus 6%, p less than 0.01). The percentage of persons having one or more accidents in which they were at fault was also greater in the patients with apnea than in the control subjects (24% versus 3%, p less than 0.02). The automobile accident rate of the patients with sleep apnea was 2.6 times the accident rate of all licensed drivers in the state of Virginia (p less than 0.02). In addition, 24% of patients with sleep apnea reported falling asleep at least once per week while driving. We conclude that patients with obstructive sleep apnea have a significantly higher frequency of auto accidents than do subjects without apnea. Impaired drivers with sleep apnea may cause many preventable auto accidents.
Federal regulation allows truck drivers to use sleeper berths to accumulate eight hours of off-duty rest in two separate periods. Because sleep disruption may cause fatigue and deterioration of performance, a study was conducted to evaluate the association between sleeper-berth use in two periods and tractor-trailer driver fatality. Using Bureau of Motor Carrier Safety Reports, crashes that resulted in tractor-trailer driver fatality were compared with property damage crashes. After adjusting for confounding variables by logistic regression, tractor-trailer driver fatality was found to be significantly associated with sleeper-berth use in two shifts (odds ratio = 3.05). Statistically significant but weaker associations were found between driver fatality and rural district, night driving, gross vehicle weight of 72,000 pounds or more, single-vehicle collision, intercity trip, and employment on an occasional basis.
A telephone survey was conducted of a random sample of New York State licensed drivers to determine the prevalence and circumstances of drowsy driving. Based on the survey responses, 54.6% of the drivers had driven while drowsy within the past year; 22.6% had ever fallen asleep at the wheel without having a crash, 2.8% had ever crashed when they fell asleep, and 1.9% had crashed when driving while drowsy. Of the reported crashes due to driving while drowsy or falling asleep at the wheel, 82.5% involved the driver alone in the vehicle, 60.0% occurred between 11:00 p.m. and 7:00 a.m. 47.5% were drive-off-road crashes, and 40.0% occurred on a highway or expressway. Multiple regression analysis suggested that the following driver variables are predictive of an increased frequency of driving drowsy: demographic characteristics (younger drivers, more education, and men); sleep patterns (fewer hours of sleep at night and greater frequency of trouble staying awake during the day); work patterns (greater frequency of driving for job and working rotating shifts); and driving patterns (greater number of miles driven annually and fewer number of hours a person can drive before becoming drowsy).
Twenty seven professional truck drivers completed a 12 hour, 900 km trip under each of three driving regimes-a relay (staged) trip, a working hours regulated one-way (single) trip, and a one-way (flexible) trip with no working hours constraints. The results indicated that none of the driving regimes prevented fatigue and that the pattern of fatigue experienced during the trips appeared to be related to pretrip fatigue levels.
Sleep deprivation is known to affect driving safety. Housestaff (HS) are routinely sleep-deprived when on call. We hypothesized that this would affect their driving. We therefore administered questionnaires regarding driving to 70 pediatric HS, who were on call every fourth night, and to 85 faculty members (FAC), who were rarely disturbed at night. HS were questioned about events during their residency, and FAC were questioned about events during the preceding three years. There was an 87% response rate for each group. HS slept 2.7 +/- 0.9 (SD) hours when on call vs 7.2 +/- 0.8 hours when not on call (p < 0.001). 44% of HS had fallen asleep when stopped at a light, vs 12.5% FAC (p < 0.001). 23% of HS had fallen asleep while driving vs. 8% FAC (ns). A total of 49% of HS had fallen asleep at the wheel; 90% of these events occurred post-call. In contrast, only 13% of FAC had fallen asleep at the wheel (p < 0.001). HS had received a total of 25 traffic citations for moving violations vs. 15 for FAC and were involved in 20 motor vehicle accidents vs. 11 for FAC. One traffic citation clearly resulted from HS falling asleep at the wheel vs. none for FAC. We conclude that HS frequently fall asleep when driving post-call. We speculate that current HS work schedules may place some HS at risk for injury to themselves and others. Further study, using prospectively objective measures is indicated.
Drivers and companies operating in the heavy road transport industry were surveyed about drivers' hours of work and perceptions of the causes and magnitude of fatigue as an industry problem. These drivers were operating in a state which, at the time of the survey, did not restrict driving hours for heavy haulage drivers. On the day of the interview, estimates based on retrospective and prospective reports, suggest that in a 24 hour period about 38% of drivers exceed 14 hours of driving, and 51% exceed 14 hours of driving plus other non-driving work. About 12% of drivers reported less than 4 hours of sleep on one or more working days in the week preceding the interview. These drivers are likely to be operating their vehicles while having a significant sleep debt. About 20% of drivers reported less than 6 hours sleep before starting their current journey, but nearly 40% of dangerous events that occurred on the journey were reported by these drivers (p < 0.05). Many drivers and company representatives reported fatigue to be a problem for other drivers, but considered themselves or their companies' drivers to be relatively unaffected by fatigue. There were differences between drivers' and companies' perceptions about causes of fatigue, and strategies that should be used to manage it. The results obtained from these drivers in an unregulated state were compared with earlier findings from drivers in states where driving hours restrictions are in place.
This paper presents the results of a postal questionnaire survey of just over 4600 male drivers aimed at exploring the relationship between accidents and daytime sleepiness. Drivers in this survey provided details of the accidents they had experienced in the last 3 years, and identified those factors they thought had contributed to their accidents. In addition to the normal demographic and exposure variables, drivers completed the Epworth scale measuring daytime sleepiness. Drivers also reported whether they had felt close to falling asleep whilst driving during the past 12 months and whether the car they drove most was privately or company owned. The analysis of this data has identified the characteristics of tiredness-related accidents. The probability of feeling close to falling asleep at the wheel has been related to demographic variables and the Epworth score using a logistic model. Drivers reported that ca 7% of accident involvements were associated with tiredness (ca 9-10% of accidents). The accident liability of the drivers has been evaluated using a multivariate statistical model; for some drivers, accident liability is shown to be sensitive to daytime sleepiness.
Studies have consistently shown that sleep apnea patients have high accident rates, but the generalizability of the association beyond clinic populations has been questioned. The goal of this investigation was to determine if unrecognized sleep-disordered breathing in the general population, ranging from mild to severe, is associated with motor vehicle accidents. The sample comprised 913 employed adults enrolled in an ongoing study of the natural history of sleep-disordered breathing. Sleep-disordered breathing status was determined by overnight in-laboratory polysomnography and motor vehicle accident (MVA) history was obtained from a statewide data base of all traffic violations and accidents from 1988 to 1993. Men with five or more apneas and hypopneas per hour of sleep [apnea-plus-hypopnea index (AHI) > 5], compared to those without sleep-disordered breathing, were significantly more likely to have at least one accident in 5 years (adjusted odds ratio = 3.4 for habitual snorers, 4.2 for AHI 5-15, and 3.4 for AHI > 15). Men and women combined with AHI > 15 (vs. no sleep-disordered breathing) were significantly more likely to have multiple accidents in 5 years (odds ratio = 7.3). These results, free of clinic selection bias, indicate that unrecognized sleep-disordered breathing in the general population is linked to motor vehicle accident occurrence. If the association is causal, unrecognized sleep-disordered breathing may account for a significant proportion of motor vehicle accidents.
Factor Analysis A Study of the Relationships among Fatigue, Hours of Service, and Safety of Operations of Truck and Bus Drivers, BMCS-RD-71-2, US Department of Transportation
- R L Gorsuch
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Commercial Motor Vehicle Driver Fatigue and Alertness Study: Technical Summary
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New approaches to fatigue management: a regula-tor's perspective. International Conference Proceedings: Manag-ing Fatigue in Transportation
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Work and sleep/rest factors associated with driving while drowsy experiences among long-distance truck drivers
- A T Mccartt
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Long hours and fatigue: a study of tractor-trailer drivers
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- W Harris
New approaches to fatigue management: a regulator’s perspective
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