Heavy Truck Drivers Research Articles

Relationships between risk of causing a motorway crash in Austria and attributes of drivers

ObjectiveThe emphasis of the study presented in this paper was to identify the attributes of drivers who are prone to cause a motorway crash. It was induced byambitions to enhance the effectiveness of traffic safety campaigns by identifying subgroups of drivers more precisely.MethodFor this purpose we conducted an accident data analysis of all injury crashes 2012–2014 on Austrian motorways. Since 2012 it is possible for the police to label the “mainly responsible person” for the crash in the Austrian electronic accident recording system. It turned out that the quality of the data had some limitations, which required considerable pre-processing. The analysis by comparing the proportions of “mainly responsible” and “not responsible” drivers was done using descriptive statistics and logistic regression models. The binary characteristic, if a person was, according to the police, mainly responsible for the crash served as response variable. It was regressed on various personal and vehicle characteristics in order to identify their influence on the probability of causing a crash.Results/ConclusionsThe results yield apparent tendencies, some of which support well-known pattern, e.g., the disproportionally high risk of motorcyclists and - to a lesser extent - young and elderly car drivers to cause an accident. Other results were less expected, e.g., the higher risk of foreign car drivers (compared to Austrian drivers) as well as drivers of light trucks, whereas drivers of heavy trucks revealed a below-average risk of causing a crash. The differences between male and female car drivers were small from young to middle age and fully disappeared in the high age group. There is some evidence that the frequency and experience of driving on a motorway have more influence on the risk of causing a crash than the driver’s gender. From this we conclude that motorway safety campaigns should on the one hand focus on the abovementioned groups of high risk drivers and on the other hand, in terms of car drivers, equally address both male and female drivers.

Management of heavy truck driver queuing and waiting for loading and unloading at road transport customers’ depots

Management of queuing and waiting for loading/unloading can influence the risk of fatigue for heavy truck drivers if it extends work hours or hampers drivers’ access to rest. Previous studies identified non-driving activities as a major contributor to driver fatigue in this industry despite Chain of Responsibility (CoR) legislation in Australia that establishes a duty on road transport customers to ensure their loading/unloading practices do not result in fatigued driving or breaches of work hours. This study examined how customer companies manage queuing and waiting and the barriers to good management. In phase one, 41 long distance truck drivers identified customer company depots where they had experienced good and poorer management of queuing and waiting. A subgroup (n = 27) provided more information about recent experiences in a survey. In phase two, representatives of 13 depots identified in phase one completed a qualitative interview about their queuing and waiting management. Drivers in phase one identified problems contributing to long queuing and waiting times and limited rest opportunities, with implications for fatigue risk, including communication issues, procedural efficiency, constraints on drivers, equity and fairness, depot capacity and resource management. Company results in phase two corroborated driver concerns. Infrastructure limitations, truck scheduling and the way work is managed were the main types of contributors. Financial and operational considerations were common cited barriers to good management. Companies did not perceive their primary CoR duty included managing hours or work and rest opportunities. Strategies to promote genuine fatigue risk management in loading/unloading processes must be pursued.

Determination of Occupational Safety and Health Factors in Young Workers

Background: An increase in the population in the ancient societies has enhanced the need to provide suitable employment conditions, along with the reduction of the probability of occupational accidents and diseases among young workers. In 2015, studies in 60 European countries showed that a quarter of workers were from working conditions and the risks associated with their jobs, and young workers were at greater risk than others. Most of the accidents have occurred among young workers in the retail industry due to heavy workload and high responsibilities, and also in heavy truck drivers under the age of 27. Besides the protection of workers’ safety and health, identification of vulnerable groups among them is important. Hence, this study was conducted to examine the determinants of occupational safety and health in young workers. Methods: This study covered the articles from 1994 to 2018 indexed in PubMed, Magiran, Google Scholar, SID, Scopus, Web of science which focused on occupational safety and health of workers. Results: 12528 articles addressed the issue of occupational health and safety and vulnerable among young workers. The candidate articles showed that mechanical factors such as heavy lifting, psychosocial factors such as low attention to working conditions, and workers and organizational factors such as climatic conditions in the workplace are affecting workers health and safety, as well as increased risk and job harm. The contact of workers with chemicals was associated with skin disorders, such as eczema, and lifting heavy objects caused mild back pain and high labor costs, which could cause mental harm in workers. Conclusion: According to the results, the vulnerable group among the workers with the highest number of occupational injuries and illnesses includes young people who are dropping out of education and entering the work environment, as well as trainees and novices. Therefore, in order to prevent job losses, isolation of vulnerable groups and provision of training in the work environment can be effective.

Permanent Night Work in Germany

Research on night work focuses almost solely on night work as part of rotating shift schedules. Thus, little is known about permanent night workers, their working conditions and health. The aim of this study is to give insight on characteristics of permanent night workers, their health status and their work–life balance. Data from the BAuA-Working Time Survey 2015 were used and 189 employees in permanent night work identified. Results are presented in comparison to statistics on employees in general and to rotating shift workers with night shifts in particular. The most common occupations among permanent night workers are professional nurses and heavy truck and lorry drivers. Night workers less often rated their health as (very) good or were satisfied with their worklife balance compared to employees in gen-eral. They also reported health complaints more often. Findings in comparison to employees working in rotating shifts with night work were mixed. The results point towards some concerns regarding health and work–life balance related to perma-nent night work.

Cross Sectional Crash Severity Analysis among Various Vehicle Driver Characteristics

The current study evaluated road crashes in three categories of drivers: passenger car drivers, heavy vehicle drivers and pickup truck drivers. The crash data of road crashes that occurred from 2009 to 2012 in Iranian suburban roads were analyzed. The crashes involved 194,041 damage, 9,677 injury and 1,303 fatality crashes. Because of the ordinal nature of crash severity, ordered logit model was selected for each vehicle driver category. In the passenger car driver category, the independent variables of driver’s gender, driver’s age and driver’s educational level (uneducated, less than high school diploma, high school diploma) were obtained for modeling; in the heavy vehicle driver category, the independent variables of driver’s age and driver’s educational level (uneducated, less than high school diploma) were obtained for modeling, and in the pickup truck driver category, the independent variables of driver’s age and driver’s educational level (uneducated, high school diploma) were obtained for modeling. The variable of driver’s gender with respect to passenger cars shows that crashes by female drivers are more severe than those involving male drivers in suburban roads. Regarding the variable of driver’s age, if the driver’s age increases in each vehicle driver category, the probability of occurrence of a severe crash will decrease. The variable of driver’s educational level shows that the severity of crashes involving a driver that has a low level of education is more compared with a driver that has a high level of education.

Work-related musculoskeletal discomfort among heavy truck drivers

Background. Heavy truck drivers are exposed to various psychological, psychosocial and physiological factors, some of which can cause musculoskeletal discomfort in different body regions. Purpose. This study aims to investigate the correlation between different factors of musculoskeletal discomfort in heavy truck drivers. Methods. A cross-sectional study design was applied. A total of 384 participants were interviewed using an updated version of the Nordic musculoskeletal questionnaire. While hypothesis testing was used to assess the association of different factors in musculoskeletal discomfort, logistic regression was applied to explore different correlations among questions of the survey. Results. The results demonstrate that hours of exposure to vibration were associated with discomfort in the neck and shoulders (p < 0.001). This relationship was not statistically significant in the lower back area (p = 0.300). Additionally, 19 equations, their correlations and their odds ratios were formulated with Nagelkerke R2 > 0.05. Conclusion. Fifty-seven percent of the drivers were suffering from discomfort in their lower back region. Moreover, seat comfort was found to be highly correlated with discomfort in the neck, shoulder and upper back areas. Additionally, with aging the likelihood of experiencing discomfort in the neck, upper back and knees is increased.

Promoting remanufactured heavy-truck engine purchase in China: Influencing factors and their effects

Abstract Due to the ever-increasing quantity of produced and sold automobiles in China, many side effects such as resource depletion, energy shortages and air pollution have emerged. Remanufacturing, as the highest form of the recycling economy, has been promoted by the Chinese government as a major measure to save resources and energy. The remanufactured products, however, get very low market recognition from Chinese consumers. Thus, understanding how to cultivate consumers potential behavior of purchasing remanufactured products is the first step and also very important for developing the remanufacturing industry. This paper, focusing on heavy truck engines due to their short life expectancy and repair frequency, aims to identify the factors influencing remanufactured heavy truck engine (RHTE) potential purchase and analyze the relationship among those factors and potential purchasing behavior. Based on 301 questionnaires from Chinese heavy truck drivers, this paper develops a conceptual model to hypothesize how the influencing factors affect RHTE potential purchasing behavior. Hierarchical regression results show that individual factors (including product knowledge, product trust and environmental values) mediate the relationship between environmental factors (including product attribute and advertisement) and RHTE purchasing intention. Contextual factors (including incentive policy and purchasing convenience) moderate the relationship between RHTE purchasing intention and potential purchasing behavior. Our results indicate that individual factors are essential in cultivating RHTE purchasing intention and environmental factors are helpful for improving individual factors. Contextual factors can motivate the transformation from RHTE purchasing intention to potential purchasing behavior.

Clinical characteristics of sleep disorders, sleepiness and workplace accident risk factors in heavy truck drivers

Clinical characteristics of sleep disorders, sleepiness and workplace accident risk factors in heavy truck drivers

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This article is a product of quantitative research of descriptive scope and of transversal section, whose objective allowed to describe the absence of work by common illness in employees linked by payroll of a power station located in Antioquia, in the established activity centers and classified by the Company as operational, maintenance and support administrative personnel, intervened for occupational health during the years 2009, 2010 and 2011. For the data collection, information was used from the second source, provided by the company’s Human Resources department, thus constructing a database that grouped all the variables and which were the input for the statistical analysis; Therefore a multivariate descriptive analysis was performed, in the analysis of the information were calculated percentages, frequencies and costs. The instruments used to present the information were made using histograms, frequency tables, trends and percentages of absenteeism to show the predominant causes of common illness and the representation of costs. The results of the study indicate that there is high absenteeism due to a common illness, and it is evident that diseases are the main cause of absenteeism in the business group; It is inferred that the prevalence of diseases causes, in the first instance, non-attendance. At the level of work absenteeism by gender it was established that it is greater in women than in men. Older people are the most disabled, being more common among the ranks of 51 to 59 years; To greater age greater absenteeism work. The positions that most presented absenteeism were heavy truck drivers, construction and support assistants and administrative technicians. This study allowed the definition of Human Talent Management guidelines for the company’s social welfare programs aimed at reducing absenteeism due to common illness.

Opportunities for improved heavy truck occupant protection in rollover and overhead loading impacts

ABSTRACTDriver compartments on medium and heavy trucks are essentially modular units that are applied to a chassis. The same cab is often utilised independent of what the rest of the truck application may be. However, the strength of the cabs has been found to be comparable to that of pickup trucks while the gross vehicle weights involved for the applications can be more than 10 times greater than their passenger vehicle counterparts. In this study, the background to the problem is reviewed. An example baseline cab configuration is then examined under various rollover loading and top loading conditions utilising virtual testing techniques. Under the same conditions, alternative design approaches are considered and evaluated. The results indicate that opportunities are available to provide substantially better improved compartment strengths to maintain the survival space for medium and heavy truck drivers.

Heavy Duty Truck Driver Behavior When Take-Over-Requests Were Provided on different level Automated Driving

Heavy Duty Truck Driver Behavior When Take-Over-Requests Were Provided on different level Automated Driving

Economic Effects of Automated Vehicles

Connected and fully automated or autonomous vehicles (CAVs) may soon dominate the automotive industry. Once CAVs are sufficiently reliable and affordable, they will penetrate markets and thereby generate economic ripple effects throughout industries. This paper synthesizes and expands on existing analyses of the economic effects of CAVs in the United States across 13 industries and the overall economy. CAVs will soon be central to the automotive industry, with software composing a greater share of vehicle value than previously. The number of vehicles purchased each year may fall because of vehicle sharing, but rising travel distances may increase vehicle sales. The opportunity for heavy-truck drivers to do other work or rest during long drives may lower freight costs and increase capacity. Personal transport may shift toward shared autonomous vehicle fleet use, reducing that of taxis, buses, and other forms of group travel. Fewer collisions and more law-abiding vehicles will lower demand for auto repair, traffic police, medical, insurance, and legal services. CAVs will also lead to new methods for managing travel demand and the repurposing of curbside and off-street parking and will generate major savings from productivity gains during hands-free travel and reduction of pain and suffering costs from crashes. If CAVs eventually capture a large share of the automotive market, they are estimated to have economic impacts of $1.2 trillion or $3,800 per American per year. This paper presents important considerations for CAVs’ overall effects and quantifies those impacts.

Naturalistic Study of Truck Following Behavior

A baseline case was created for the following behavior of heavy-truck drivers with the use of naturalistic driving data to support the development of automated platooning. A truck platoon is a string of trucks following each other in the same lane at short distances. Grouping vehicles in platoons can increase capacity on roads, save significant fuel, reduce emissions, and potentially result in improved safety. However, these benefits can be realized only if the platoons operate in an automated, coordinated manner. Because little literature of truck following behavior exists to support the development of such truck platoons, this research focused on how closely trucks follow other vehicles on highways under various environmental conditions, how closely a truck follows a leading vehicle when other vehicles cut in between, and the safety impact of following at different headways. Findings indicate that trucks follow other vehicles at an average headway of about 2 s overall, and those headways are shorter when following a passenger car rather than a heavy truck, on state highways rather than on Interstates, in clear weather rather than in rain or snow, and during the day rather than during at night. Vehicles usually do not cut in when a truck is following another vehicle at less than 25-m (82-ft) or 1.0-s headway. For manual response times, the rear-end crash risk increases considerably at headways of less than 1.0 s; for automated response times, crash risk is almost negligible at headways as low as 0.5 s.

A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies

Driver braking behavior was analyzed using time-series recordings from naturalistic rear-end conflicts (116 crashes and 241 near-crashes), including events with and without visual distraction among drivers of cars, heavy trucks, and buses. A simple piecewise linear model could be successfully fitted, per event, to the observed driver decelerations, allowing a detailed elucidation of when drivers initiated braking and how they controlled it. Most notably, it was found that, across vehicle types, driver braking behavior was strongly dependent on the urgency of the given rear-end scenario⿿s kinematics, quantified in terms of visual looming of the lead vehicle on the driver⿿s retina. In contrast with previous suggestions of brake reaction times (BRTs) of 1.5s or more after onset of an unexpected hazard (e.g., brake light onset), it was found here that braking could be described as typically starting less than a second after the kinematic urgency reached certain threshold levels, with even faster reactions at higher urgencies. The rate at which drivers then increased their deceleration (towards a maximum) was also highly dependent on urgency. Probability distributions are provided that quantitatively capture these various patterns of kinematics-dependent behavioral response. Possible underlying mechanisms are suggested, including looming response thresholds and neural evidence accumulation. These accounts argue that a naturalistic braking response should not be thought of as a slow reaction to some single, researcher-defined ⿿hazard onset⿿, but instead as a relatively fast response to the visual looming cues that build up later on in the evolving traffic scenario.

Exploring background risk factors for fatigue crashes involving truck drivers on regional roadway networks: a case control study in Jiangxi and Shaanxi, China.

BackgroundFatigue driving is a leading cause of traffic fatalities and injuries in China, especially among heavy truck drivers. The present study tried to examine which and how factors within the human-vehicle-roadway-environment system contribute to the occurrence of crashes involving fatigued truck drivers.FindingsTo reduce such risk on the road, a total of 9168 crashes which occurred in Jiangxi and Shaanxi between 2003 and 2014 were selected to measure the effects of potential factors on fatigue related truck crashes using a case control study. Pearson Chi-square test was used to determine the relationship between crash risk and independent factors, and a stepwise logistic regression model was developed to determine the significant risk factors. According to the data analysis results, driver’s gender, age, driving experience, and overspeeding behavior, vehicle’s commercial status, overloading conditions and brake performance, road’s type, slippery pavement and existence of sharp curve and long steep grade, and time of day, season, weather and visibility conditions, etc. were identified to be significantly associated with fatigue related truck crashes on Jiangxi and Shaanxi highways. Moreover, it is found that (a) in Jiangxi, an employed truck driver has a higher risk of crash involving multi-vehicles or a passenger car at bridge locations, and (b) in Shaanxi, the adult, tunnel location, summer and winter days prohibit statistically significant association with the occurrence of multi-vehicle and single-vehicle run-off-road/rollover crashes.ConclusionsYoung employed male truck drivers with less experience are at high risk, especially while driving across sharp curves, down long steep grades, over bridge or through tunnels, during the midnight period, on rainy, snowy or foggy days in rural areas. All these help recommend potential policy initiatives as well as effective safety promotion strategies at the public health scale for professional truck drivers.

NIOSH national survey of long-haul truck drivers: Injury and safety

Approximately 1,701,500 people were employed as heavy and tractor-trailer truck drivers in the United States in 2012. The majority of them were long-haul truck drivers (LHTDs). There are limited data on occupational injury and safety in LHTDs, which prompted a targeted national survey. The National Institute of Occupational Safety and Health conducted a nationally representative survey of 1265 LHTDs at 32 truck stops across the contiguous United States in 2010. Data were collected on truck crashes, near misses, moving violations, work-related injuries, work environment, safety climate, driver training, job satisfaction, and driving behaviors. Results suggested that an estimated 2.6% of LHTDs reported a truck crash in 2010, 35% reported at least one crash while working as an LHTD, 24% reported at least one near miss in the previous 7 days, 17% reported at least one moving violation ticket and 4.7% reported a non-crash injury involving days away from work in the previous 12 months. The majority (68%) of non-crash injuries among company drivers were not reported to employers. An estimate of 73% of LHTDs (16% often and 58% sometimes) perceived their delivery schedules unrealistically tight; 24% often continued driving despite fatigue, bad weather, or heavy traffic because they needed to deliver or pick up a load at a given time; 4.5% often drove 10miles per hours or more over the speed limit; 6.0% never wore a seatbelt; 36% were often frustrated by other drivers on the road; 35% often had to wait for access to a loading dock; 37% reported being noncompliant with hours-of-service rules (10% often and 27% sometimes); 38% of LHTDs perceived their entry-level training inadequate; and 15% did not feel that safety of workers was a high priority with their management. This survey brings to light a number of important safety issues for further research and interventions, e.g., high prevalence of truck crashes, injury underreporting, unrealistically tight delivery schedules, noncompliance with hours-of-service rules, and inadequate entry-level training.

Predicting Driver Injury Severity in Single-Vehicle and Two-Vehicle Crashes with Boosted Regression Trees

The boosted regression tree model is an emerging nonparametric tree-based model that can capture nonlinear effects of both discrete and continuous variables without preprocessing data. The model is particularly advantageous to predict severe injuries, which are more difficult to classify because of their small amount compared with nonsevere injuries. The objectives of this study were to investigate driver injury severity with the boosted regression tree model and other nonparametric models—the classification and regression tree and Random Forests—and to evaluate performance of the boosted regression tree model in comparison with the classification and regression tree model. The study identified important factors affecting injury severity by using 5-year crash records for provincial highways in Ontario, Canada. The results of the boosted regression tree model showed that ejection from a vehicle and head-on collisions commonly had a strong association with driver injury severity. Results also showed that marginal effects of continuous variables including truck percentage, annual average daily traffic (AADT), driver age, and vehicle age on injury severity were nonlinear. In particular, their effects on the injuries of heavy-truck drivers had different patterns compared with the effects on passenger-car and light-truck drivers; the risk of severe injury to heavy-truck drivers increased as the truck percentage and AADT increased and the driver's age decreased. The boosted regression tree model predicted driver injury severity more accurately than the classification and regression tree model for both single-vehicle and two-vehicle crashes. Thus, it is recommended that the boosted regression tree model be applied with separate data sets for single-vehicle crashes and different types of two-vehicle crashes for more accurate prediction of crash injury severity.

Occupational fatalities among driver/sales workers and truck drivers in the United States, 2003-2008.

This study provides a national profile of occupational fatalities among truck drivers and driver-sales workers. Data from the 2003-2008 Census of Fatal Occupational Injuries were used. Cases were extracted specifically for occupational subcategories included in the Driver/Sales Workers and Truck Drivers occupational category: Driver/Sales Workers, Heavy and Tractor-Trailer Truck Drivers, and Light Truck or Delivery Services Drivers. In 2003-2008, the group Driver/Sales Workers and Truck Drivers had 5,568 occupational fatalities, representing 17% of all occupational fatalities in the United States. The majority of these fatalities were in the subgroup Heavy and Tractor-Trailer Truck Drivers (85%) and due to transportation incidents (80%). Older and male drivers had higher fatality rates than their counterparts. Findings suggest a need for targeted interventions to reduce highway fatalities among heavy truck drivers. Better employment data are needed to separate the three occupational subcategories by worker characteristic and employment history for use in research and prevention efforts.

Noise exposure level of the drivers of heavy duty diesel trucks

Noise exposure is a key factor that influences the health and performance of truck drivers. This study measured the in-cab noise level status of 20 new, 2007 or 2008 model heavy-duty diesel trucks from four different manufacturers under actual driving conditions. Overall in-cab noise levels were found to be below 8-hour NIOSH (The National Institute for Occupational Safety and Health) and OSHA (Occupational Safety & Health Administration) standard limit values. Results indicated slightly higher noise levels occurred while driving on the federal interstate when compared to driving on the state highway. It is believed that noise from tires, engine and wind impacting the cab at higher road speeds contributed to the elevated noise levels measured during interstate travel because speed limits are higher on the interstate than on state highways. These results could serve as baseline data from which future similar studies may determine if truck designs have changed the existing state of these conditions for truck drivers.

Obesity and other risk factors: The National Survey of U.S. Long‐Haul Truck Driver Health and Injury

Drivers of heavy and tractor-trailer trucks accounted for 56% of all production and nonsupervisory employees in the truck transportation industry in 2011. There are limited data for illness and injury in long-haul truck drivers, which prompted a targeted national survey. Interviewers collected data during 2010 from 1,670 long-haul truck drivers at 32 truck stops across the 48 contiguous United States that were used to compute prevalence estimates for self-reported health conditions and risk factors. Obesity (69% vs. 31%, P < 0.01) and current smoking (51% vs. 19%, P < 0.01) were twice as prevalent in long-haul truck drivers as in the 2010 U.S. adult working population. Sixty-one percent reported having two or more of the risk factors: hypertension, obesity, smoking, high cholesterol, no physical activity, 6 or fewer hours of sleep per 24-hr period. Survey findings suggest a need for targeted interventions and continued surveillance for long-haul truck drivers.