Goods Vehicle Drivers Research Articles

The risk of road traffic crashes for occupational drivers: A responsibility study with comparison to the general population.

Road accidents are the leading type of work-related fatalities, but the impact of work-related travel on overall traffic safety has been scarcely studied. The main objective of the present study was to assess drivers' relative road accident risk between work-related and personal journeys. A responsible/non-responsible case-control study was performed on a sample of 7,051 road accidents in France from the VOIESUR project. Logistic regression determined odds-ratios according to work-related versus personal travel, and identified risk factors for responsibility, specific to each of the two sub-groups. Drivers traveling on duty or commuting home were significantly less often responsible for accidents than drivers on personal journeys: OR = 0.75 [0.63; 0.89] and 0.65 [0.53; 0.80] respectively. Responsibility was significantly more frequent in commuting to versus from work: OR = 1.38 [1.06; 1.78]. Among on-duty drivers, professional passenger-transport drivers had the lowest risk of responsibility (OR = 0.25 [0.11; 0.58]), while those on temporary or work/study contracts and professional light goods vehicle drivers had the highest risk (OR = 11.64 [2.15; 62.94] and OR = 29.83 [5.19; 171.38] respectively). When driving under the influence of alcohol, risk of responsibility was higher in commuting home than in personal journeys. On-duty drivers showed lower risk of responsibility for an accident than other drivers. However, on-duty drivers on temporary or work/study contracts, who are usually not subject to specific regulations, showed higher risk, and should be the subject of particular attention regarding occupational risk prevention.

Prevalence and Factors Associated with Psychoactive Substance Misuse among Heavy Goods Vehicle Drivers in Cotonou, Benin

Prevalence and Factors Associated with Psychoactive Substance Misuse among Heavy Goods Vehicle Drivers in Cotonou, Benin

Drivers with and without Obesity Respond Differently to a Multi-Component Health Intervention in Heavy Goods Vehicle Drivers.

Physical inactivity and obesity are widely prevalent in Heavy Goods Vehicle (HGV) drivers. We analysed whether obesity classification influenced the effectiveness of a bespoke structured lifestyle intervention ('SHIFT') for HGV drivers. The SHIFT programme was evaluated within a cluster randomised controlled trial, across 25 transport depots in the UK. After baseline assessments, participants within intervention sites received a 6-month multi-component health behaviour change intervention. Intervention responses (verses control) were stratified by obesity status (BMI < 30 kg/m2, n = 131; BMI ≥ 30 kg/m2, n = 113) and compared using generalised estimating equations. At 6-months, favourable differences were found in daily steps (adjusted mean difference 1827 steps/day, p < 0.001) and sedentary time (adjusted mean difference -57 min/day, p < 0.001) in drivers with obesity undertaking the intervention, relative to controls with obesity. Similarly, in drivers with obesity, the intervention reduced body weight (adjusted mean difference -2.37 kg, p = 0.002) and led to other favourable anthropometric outcomes, verses controls with obesity. Intervention effects were absent for drivers without obesity, and for all drivers at 16-18-months follow-up. Obesity classification influenced HGV drivers' behavioural responses to a multi-component health-behaviour change intervention. Therefore, the most at-risk commercial drivers appear receptive to a health promotion programme.

Clear Roads and Dirty Air? Indirect effects of reduced private traffic congestion on emissions from heavy traffic

Traffic and transportation are a major source of CO2 emissions. As the volume of heavy goods vehicle (HGV) transportation is difficult to reduce, many governments target private traffic. Next to the direct effect of fewer private vehicles on the roads, an indirect effect may be very important: The less congestion, the more fuel-efficient the remaining drivers may be able to drive because there would be less need to speed up, brake, and maneuver, for example while overtaking. On the other hand, clear roads may be tempting for drivers to speed and thus result in a negative impact of less private traffic. The direction and size of this indirect effect is difficult to measure for two reasons: First, we usually have no real-time driving data from heavy trucks. Second, traffic density usually does not vary to a large extent. We set out to assess the margins of this indirect effect using a unique data set from a large German logistics fleet. We measured truck drivers’ driving behavior as well as emissions from their trucks between January and May 2020. During that time, the COVID-19-related policy measures led to a significant decline in private traffic on highways. We find that less private traffic volume results in improved fuel-efficient driving behavior, resulting in reduced overall CO2 emissions. The effect is u-shaped; too little private traffic density leads to less fuel-efficient driving by the remaining heavy goods vehicle drivers. Moreover, removing the worst drivers from the roads has the same effect in terms of magnitude as reducing private traffic congestion to the medium-density optimum.

A multicomponent structured health behaviour intervention to improve physical activity in long-distance HGV drivers: the SHIFT cluster RCT

BackgroundLong-distance heavy goods vehicle drivers are exposed to a multitude of risk factors associated with their occupation. The working environment of heavy goods vehicle drivers provides limited opportunities for a healthy lifestyle, and, consequently, heavy goods vehicle drivers exhibit higher than nationally representative rates of obesity and obesity-related comorbidities, and are underserved in terms of health promotion initiatives.ObjectiveThe aim of this trial was to test the effectiveness and cost-effectiveness of the multicomponent Structured Health Intervention For Truckers (SHIFT) programme, compared with usual care, at both 6 months and 16–18 months.DesignA two-arm cluster randomised controlled trial, including a cost-effectiveness analysis and process evaluation.SettingTransport depots throughout the Midlands region of the UK.ParticipantsHeavy goods vehicle drivers.InterventionThe 6-month SHIFT programme included a group-based interactive 6-hour education session, health coach support and equipment provision [including a Fitbit®(Fitbit Inc., San Francisco, CA, US) and resistance bands/balls to facilitate a ‘cab workout’]. Clusters were randomised following baseline measurements to either the SHIFT arm or the control arm.Main outcome measuresOutcome measures were assessed at baseline, with follow-up assessments occurring at both 6 months and 16–18 months. The primary outcome was device-measured physical activity, expressed as mean steps per day, at 6-month follow-up. Secondary outcomes included device-measured sitting, standing, stepping, physical activity and sleep time (on any day, workdays and non-workdays), along with adiposity, biochemical measures, diet, blood pressure, psychophysiological reactivity, cognitive function, functional fitness, mental well-being, musculoskeletal symptoms and work-related psychosocial variables. Cost-effectiveness and process evaluation data were collected.ResultsA total of 382 participants (mean ± standard deviation age: 48.4 ± 9.4 years; mean ± standard deviation body mass index: 30.4 kg/m2 ± 5.1 kg/m2; 99% male) were recruited across 25 clusters. Participants were randomised (at the cluster level) to either the SHIFT arm (12 clusters,n = 183) or the control arm (13 clusters,n = 199). At 6 months, 209 (54.7%) participants provided primary outcome data. Significant differences in mean daily steps were found between arms, with participants in the SHIFT arm accumulating 1008 more steps per day than participants in the control arm (95% confidence interval 145 to 1871 steps;p = 0.022), which was largely driven by the maintenance of physical activity levels in the SHIFT arm and a decline in physical activity levels in the control arm. Favourable differences at 6 months were also seen in the SHIFT arm, relative to the control arm, in time spent sitting, standing and stepping, and time in moderate or vigorous activity. No differences between arms were observed at 16–18 months’ follow-up. No differences were observed between arms in the other secondary outcomes at either follow-up (i.e. 6 months and 16–18 months). The process evaluation demonstrated that the intervention was well received by participants and that the intervention reportedly had a positive impact on their health behaviours. The average total cost of delivering the SHIFT programme was £369.57 per driver, and resulting quality-adjusted life-years were similar across trial arms (SHIFT arm: 1.22, 95% confidence interval 1.19 to 1.25; control arm: 1.25, 95% confidence interval 1.22 to 1.27).LimitationsA higher (31.4%) than anticipated loss to follow-up was experienced at 6 months, with fewer (54.7%) participants providing valid primary outcome data at 6 months. The COVID-19 pandemic presents a major confounding factor, which limits our ability to draw firm conclusions regarding the sustainability of the SHIFT programme.ConclusionThe SHIFT programme had a degree of success in positively impacting physical activity levels and reducing sitting time in heavy goods vehicle drivers at 6-months; however, these differences were not maintained at 16–18 months.Future workFurther work involving stakeholder engagement is needed to refine the content of the programme, based on current findings, followed by the translation of the SHIFT programme into a scalable driver training resource.Trial registrationThis trial is registered as ISRCTN10483894.FundingThis project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full inPublic Health Research; Vol. 10, No. 12. See the NIHR Journals Library website for further project information.

Sleep Variability in UK Long Distance Heavy Goods Vehicle Drivers.

Sleep variability levels are unknown in heavy goods vehicle (HGV) drivers yet are associated with adverse health outcomes and reduced driver vigilance when high. Two hundred and thirty-three HGV drivers recruited across 25 UK depots provided sleep variability, sleep duration, and sleep efficiency data via wrist-worn accelerometry (GENEActiv) over 8 days. Sleep variability indicators included social jetlag (the difference in midpoint of the sleep window between work and nonworkdays) and intraindividual variability of sleep window onset time, out-of-bed time, and sleep duration. Fifty-three percent of drivers experienced social jetlag (≥1 hour), and 27% experienced high (>2 hours) social jetlag. Drivers with the highest sleep variability had the shortest sleep duration and lowest sleep efficiency during workdays. Drivers with high sleep variability may experience more fatigue when driving given the poor sleep outcomes during workdays observed.

The effectiveness of the Structured Health Intervention For Truckers (SHIFT): a cluster randomised controlled trial (RCT)

BackgroundLong distance heavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related co-morbidities, and are underserved in terms of health promotion initiatives. The purpose of this study was to evaluate the effectiveness of the multicomponent ‘Structured Health Intervention For Truckers’ (SHIFT), compared to usual care, at 6- and 16–18-month follow-up.MethodsWe conducted a two-arm cluster RCT in transport sites throughout the Midlands, UK. Outcome measures were assessed at baseline, at 6- and 16–18-month follow-up. Clusters were randomised (1:1) following baseline measurements to either the SHIFT arm or usual practice control arm. The 6-month SHIFT programme included a group-based interactive 6-h education and behaviour change session, health coach support and equipment provision (Fitbit® and resistance bands/balls to facilitate a ‘cab workout’). The primary outcome was device-assessed physical activity (mean steps/day) at 6 months. Secondary outcomes included the following: device-assessed sitting, physical activity intensity and sleep; cardiometabolic health, diet, mental wellbeing and work-related psychosocial variables. Data were analysed using mixed-effect linear regression models using a complete-case population.ResultsThree hundred eighty-two HGV drivers (mean ± SD age: 48.4 ± 9.4 years, BMI: 30.4 ± 5.1 kg/m2, 99% male) were recruited across 25 clusters (sites) and randomised into either the SHIFT (12 clusters, n = 183) or control (13 clusters, n = 199) arms. At 6 months, 209 (55%) participants provided primary outcome data. Significant differences in mean daily steps were found between groups, in favour of the SHIFT arm (adjusted mean difference: 1008 steps/day, 95% CI: 145–1871, p = 0.022). Favourable differences were also seen in the SHIFT group, relative to the control group, in time spent sitting (− 24 mins/day, 95% CI: − 43 to − 6), and moderate-to-vigorous physical activity (6 mins/day, 95% CI: 0.3–11). Differences were not maintained at 16–18 months. No differences were observed between groups in the other secondary outcomes at either follow-up.ConclusionsThe SHIFT programme led to a potentially clinically meaningful difference in daily steps, between trial arms, at 6 months. Whilst the longer-term impact is unclear, the programme offers potential to be incorporated into driver training courses to promote activity in this at-risk, underserved and hard-to-reach essential occupational group.Trial registrationISRCTN10483894 (date registered: 01/03/2017)

Physical Activity, Sedentary Time, and Cardiometabolic Health in Heavy Goods Vehicle Drivers.

Physical inactivity, prolonged sitting, and unhealthy dietary habits are common in Heavy Goods Vehicle (HGV) drivers. These factors increase risk of long-term health conditions. 329 HGV drivers across 25 UK depots completed a health assessment, including questionnaire completion, and objectively measured anthropometrics, blood biomarkers, physical activity (PA), and sedentary behavior. The sample demonstrated a high-risk cardiometabolic health profile. 88.1% were overweight or had obesity, and 11.9% had pre-diabetes or diabetes. 28.3% had hypertension, 83.6% had clinically elevated circulating low-density lipoprotein-cholesterol concentrations (>2mmol/l), and 66.6% had high total cholesterol levels (>4mmol/l). On workdays drivers accumulated 12 hours/day of sitting, 1.7 hours/day of light PA, and 9.8 mins/day of moderate-to-vigorous PA. Associations between light PA and cardiometabolic markers were observed. This sample presents high levels of inactivity, overweight, and obesity, and unhealthy cardiometabolic health profiles.

Road safety and heavy goods vehicle driving in LMICs: Qualitative evidence from Nepal

BackgroundHeavy 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. MethodsWe 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. ResultsFour 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. ConclusionHeavy 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.

Sleep duration and sleep efficiency in UK long-distance heavy goods vehicle drivers

ObjectivesTo profile sleep duration and sleep efficiency in UK long-distance heavy goods vehicle (HGV) drivers and explore demographic, occupational and lifestyle predictors of sleep.MethodsCross-sectional analyses were carried out on 329...

An Assessment on Driving Behaviourism of Goods Vehicle Drivers in Kerala

Road Safety has become a serious issue in this era as the population in terms of both people as well as vehicles has increased to a large extend. The behaviour of drivers is influenced by several factors, which include their socio-economic – demographic factors and vehicle characteristics. Accidents comprising of goods vehicles have been on the surge in Kerala over the years. Even though the numbers of heavy vehicles plying on Kerala roads are less compared to two wheelers and cars, the proportion of crashes involving heavy vehicles is a cause of concern. Fallacious driving behaviourism is generally considered as the leading root of such accidents. The present study intends to investigate the elements involved in the Driver Behaviour Questionnaire (DBQ), then to explore the relationships between the elements of the DBQ and accident involvement. The data were interpreted using percentage analysis. The analysis showed the level of violations, errors, lapses committed by drivers on the basis of driving behaviourism and non –driving behaviourism of the goods vehicle driver.

Competence, equipment and behavioural adaptation on Norwegian winter roads: A comparison of foreign and Norwegian HGV drivers

There seems to be a widespread view that foreign lorry drivers’ lack of competence on Norwegian roads, especially related to winter driving, is a significant safety problem. It has, however, been suggested that foreign heavy goods vehicle (HGV) drivers perform better than expected on Norwegian winter roads, as they feel less safe than Norwegian drivers, and adapt by driving slower and more carefully. The aim of the present paper is twofold. First, we examine whether foreign HGV drivers in Norway actually have poorer competence on, training for, experience with and equipment for winter driving than Norwegian HGV drivers. Second, we discuss whether the expected negative effect of these safety challenges is mitigated, as foreign HGV drivers adapt their behaviours. We use four data sources to shed light on the aims: (1) interviews, (2) roadside inspections, (3) small-scale survey and (4) towing incidents. Our data support the hypothesis about behavioural adaptation, indicating that foreign HGV drivers experience winter driving as more difficult or unsafe, as they have supposedly less suitable vehicles and equipment, less experience, training and competence for winter driving. They are therefore more likely to get stuck while driving uphill on winter roads, supposedly as they drive more carefully and slower than Norwegian HGV drivers. Norwegian HGV drivers feel safer and more confident while driving on winter roads, because of their equipment and their experience.

Evaluating the impact of Heavy Goods Vehicle driver monitoring and coaching to reduce risky behaviour

Determining the impact of driver-monitoring technologies to improve risky driving behaviours allows stakeholders to understand which aspects of onboard sensors and feedback need enhancement to promote road safety and education. This study investigates the influence of camera monitoring on Heavy Goods Vehicle (HGV) drivers’ risky behaviours. We also assess whether monitoring affects individual driving events further when coupled with safe driving practices coaching. We evaluate the outcome of those practices on three telematics incidents heavily reliant on driving errors and violations, i.e., the number of vehicle harsh braking, harsh cornering and over speeding incidents. The objective is to understand how frequently individual incidents caused by risky driving behaviour occur (a) without camera monitoring and without any coaching; (b) after camera installation; and (c) after camera installation and coaching. We investigate two commercial HGV companies (Company 1 and Company 2) with 263 and 269 vehicles, respectively, over a 16 months period, from which the first 8 months contain data collected before the installation of cameras (baseline) and the rest of the dataset contains incident counts after the installation of cameras (intervention). Company 1 provides coaching during the intervention phase while Company 2 does not offer coaching. Our analysis considers the baseline and the intervention phases during the same seasons to eliminate any possible bias due to the influence of weather on driving behaviour. Results show an overall significant reduction in the mean frequency of harsh braking incidents from baseline to intervention by 16.82% in Company 1 and 4.62% in Company 2, and a significant reduction in the mean frequency of over speeding incidents from baseline to intervention by 34.29% in Company 1 and 28.13% in Company 2. Furthermore, the effect of coaching has a significant difference in reducing the frequency of harsh braking (p = .011) and harsh cornering (p < .001) compared to just camera monitoring. These results suggest that coaching interventions are more effective in reducing driving errors while monitoring reduces both driving errors and violations.

Signal Sensing on Heavy Goods Vehicle (Hgv) Blind Spot Area for Construction Logistics

This paper will explore the issues and the causes of accidents contributed by heavy goods vehicles (HGV) specifically instigated by blind spot. A blind spot is an area or zone that cannot be directly observe by the truck driver on their side mirror. Unfortunately, due to this, high number of accidents had happened because of HGV drivers were not alert or aware of another road user or pedestrian hidden in the blind spot area. This often occurred to heavy goods vehicle drivers. The aim of this paper is to understand the issue of HGV blind spot and identify the potential use signal sensing as an alert mechanism for the blind spot of a heavy goods vehicles. This is to detect other road users who are in the dangerous distance of the HGV. This study has revealed the holistic understanding of HGV blind spot issues and problem by finding the answer for research question initially outlined.

Cluster randomised controlled trial to investigate the effectiveness and cost-effectiveness of a Structured Health Intervention For Truckers (the SHIFT study): a study protocol

IntroductionHeavy goods vehicle (HGV) drivers exhibit higher than nationally representative rates of obesity, and obesity-related comorbidities, in comparison to other occupational groups. Their working environments are not conducive to a...

Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom

Although driving behavior has been largely studied amongst private motor vehicles drivers, the literature addressing heavy goods vehicle (HGV) drivers is scarce. Identifying the existing groups of driving stereotypes and their proportions enables researchers, companies, and policy makers to establish group-specific strategies to improve safety and economy. In addition, insight into driving styles can help predict drivers’ reactions and therefore enable the modeling of interactions between vehicles and the possible obstacles encountered on a journey. Consequently, there are also contributions to the research and development of autonomous vehicles and smart roads. In this paper, our interest lies in investigating driving behavior within the HGV community in the United Kingdom (U.K.). We conduct analysis of a telematics dataset containing the incident information on 21 193 HGV drivers across the U.K. We are interested in answering two research questions: 1) What groups of behavior are we able to uncover? 2) How do these groups complement current findings in the literature? To answer these questions, we apply a two-stage data analysis methodology involving consensus clustering and ensemble classification to the dataset. Through the analysis, eight patterns of behavior are uncovered. It is also observed that although our findings have similarities to those from previous work on driving behavior, further knowledge is obtained, such as extra patterns and driving traits arising from vehicle and road characteristics.

Associations Between Musculoskeletal Conditions Risk, Sedentary Behavior, Sleep, and Markers of Mental Health: A Cross-Sectional Observational Study in Heavy Goods Vehicle Drivers. Musculoskeletal Conditions Risk in HGV Drivers.

To explore the risk of having musculoskeletal conditions (MSKs) associated with sitting and sleeping time during workdays, presenteeism, work engagement anxiety, and depression in a sample of UK heavy goods vehicle drivers. Eighty-eight male drivers participated in this cross-sectional study. Binary logistic regression analyses were performed to explore the associations between two-or-more MSKs and common health risk factors. Possessing two or more MSKs is associated with prolonged sitting time (odds ratio [OR] 4.34) and working hours per day (OR 3.10) and per week (OR 3.12), severe sleep deprivation (OR 33.19), presenteeism (OR 4.22), and borderline or abnormal scores of depression (OR 11.69) and anxiety (OR 4.44), compared with the reference categories. Workplace policies and health promotion interventions to improve heavy goods vehicle drivers working environment are required to minimize the risk of MSK's across this sector.

Predicting fruit and vegetable consumption in long-haul heavy goods vehicle drivers: Application of a multi-theory, dual-phase model and the contribution of past behaviour

Fruit and vegetable intake is insufficient in industrialized nations and long-haul heavy goods vehicle (HGV) drivers are considered a particularly at-risk group. The aim of the current study was to test the effectiveness of a multi-theory, dual-phase model to predict fruit and vegetable consumption in Australian long-haul HGV drivers. A secondary aim was to examine the effect of past fruit and vegetable consumption on model paths. A prospective design with two waves of data collection spaced one week apart was adopted. Long-haul HGV drivers (N = 212) completed an initial survey containing theory-based measures of motivation (autonomous motivation, intention), social cognition (attitudes, subjective norms, perceived behavioural control), and volition (action planning, coping planning) for fruit and vegetable consumption. One week later, participants (n = 84) completed a self-report measure of fruit and vegetable intake over the previous week. A structural equation model revealed that autonomous motivation predicted intentions, mediated through attitudes and perceived behavioural control. It further revealed that perceived behavioural control, action planning, and intentions predicted fruit and vegetable intake, whereby the intention-behaviour relationship was moderated by coping planning. Inclusion of past behaviour attenuated the effects of these variables. The model identified the relative contribution of motivation, social cognition, and volitional components in predicting fruit and vegetable intake of HGV drivers. Consistent with previous research, inclusion of past fruit and vegetable consumption led to an attenuation of model effects, particularly the intention-behaviour relationship. Further investigation is needed to determine which elements of past behaviour exert most influence on future action.

Cross-sectional surveillance study to phenotype lorry drivers’ sedentary behaviours, physical activity and cardio-metabolic health

ObjectivesElevated risk factors for a number of chronic diseases have been identified in lorry drivers. Unhealthy lifestyle behaviours such as a lack of physical activity (PA) and high levels of...

Too individualistic for safety culture? Non-traffic related work safety among heavy goods vehicle drivers

IntroductionThis article reports on a study of non-traffic related work safety among drivers of heavy goods vehicles in Denmark. In the heavy goods vehicle transport (HGV) sector only 6.4% of workplace accidents involving drivers are traffic related. HGV work is characterised by solitary work, as drivers tend to work at a physical distance from their own company and their working environment is also influenced by the working environment of other companies e.g. the places where they deliver goods. This study focuses on an analysis of HGV drivers’ and managers’ differentiated understandings of risk and safety and its management within an organisational context. The situational focus involves viewing HGV drivers’ working environment as a part of the organisational structure as well as of other social relationships. An understanding of safety culture as practice is applied with the view of identifying values and attitudes as well as organisational and technical aspects in relation to how individualist or collectivist understandings of risk and safety influence the working environment in HGVs. MethodThe study applied a mixed methods approach and in this article the qualitative interviews conducted with drivers and managers is the primary data source. ResultsThis study suggests a widespread understanding of drivers as being individually oriented in their work, from drivers and management alike. However, the study also demonstrates that, in conducting their work, the drivers are actually interdependent, and share knowledge frequently, albeit informally. The organisational structure of the company shapes their individual attitudes towards safety but they also report being dependent on relationships with, and information from, their fellow colleagues, former colleagues and friends who shape their understandings and attitudes towards hazards and safety practices. The analysis points to risk-taking and unsafe practices as prevalent among HGV drivers, who often refer to risk as trivial and the management of such risks as one’s own responsibility. Knowledge of how to manage risks in everyday practice is shown to be principally related to personal experiences but also to the good advice and examples of fellow drivers. ConclusionsThe analysis points to interdependent and collectivist practices among HGV drivers even though they are perceived as being individualistically oriented when it comes to safety. Therefore, non-traffic related safety practices, in this case the loading and unloading of vehicles, occur in the grey zone of organisational safety management. Despite the fact that organisational safety initiatives are initiated, the management sees limited possibilities for enforcing them and hence safety practice is often left to the individual driver. Practical applicationsA safety culture perspective might enhance work safety among HGV drivers if we are able to understand workplace culture in a pluralistic way. Collectivist practice among the drivers can be utilised in order to improve knowledge sharing and situational safety practices. The informal communication identified among the drivers might offer a new model for safety initiatives based on more collectivist, albeit informal, safety culture practices on behalf of HGV companies.