Search

One of the most harmful of two-vehicle crashes to passenger vehicle occupants is when the front of passenger vehicle hits and passes underneath the rear of truck. It resulted in 23% of total death from two-vehicle crashes with a truck in 2018 based on data from the U.S. Department of transportation’s Fatality Analysis Reporting System (FARS). To reduce the violence of such accidents, the rear underrun protective device (RUPD) is installed on the rear of heavy goods vehicle (HGV), to cause the crumple zone of the impacting passenger vehicle absorbing the impact energy and prevent the impacting passenger vehicle from getting crushed under the HGV. This article demonstrates an approach to design the RUPD based on design inputs, including the structural strength, the local RUPD builders, and the variation of commercial HGV types in Thailand. The morphological analysis is applied along with brainstorming among design team, local manufacturers, and government agency, to generate a total of 72 potential RUPD solutions. In this study, three potential RUPD designs were proposed as RUPD prototypes for different HGV types to investigate their structural strength in terms of strain, deformation, and maximum reaction force. The explicit dynamic finite element (FE) method was implemented to accurately simulate the structural strength of the RUPD prototype since its results were validated by the real test of full-scale prototype with reference to the UN R58 standard. From the results, all proposed RUPD prototypes satisfied the UN R58 standard and are not violated by test loads at all relevant positions. In addition, different designs of the protective beam, which was found to be the main load-bearing resstive component of RUPD, were proposed. Their structural strength and energy-absorbing capability were examined by FE simulation to allow local RUPD builders to have alternatives for RUPD fabrication depending on their resources and applications. Besides, the proposed design approach in this study could be further applied as a guideline design for other RUPD types in a commercial scale.

Major contributors to the road damage are Heavy Goods Vehicles (HGV), resulting in high maintenance costs of roads. This high cost makes it necessary to look into the issue seriously for minimizing the road damage. An Automobile Engineer can reduce road damage through the efficient design of a suspension system. The design involves satisfying the two conflicting criteria of riding comfort and vehicle handling with the restriction on the suspension travel. This paper involves designing an automobile suspension system, to improve the performance of the vehicle without a significant change in the cost of the suspension system and minimize road damage. To achieve the aforesaid objective, the use of a nonlinear passive suspension is suitable as compared to a linear passive suspension system. For the analysis, a HGV model of vehicle suspension has been considered. The suspension system considered for investigation comprises of a cubical nonlinear spring and a linear damper. Road damage has been represented by the fourth power of the tire dynamic load. A genetic algorithm has been used to optimize the half truck model to minimize road damage. The solution has been obtained using MATLAB and SIMULINK.

This paper contributes to filling a knowledge gap by presenting new research within the practical field of road transport. It takes the buyers of road transport services as its point of entry and seeks to answer the follow question: How can buyers of road transport services contribute to safe road transport in northern Norway? A qualitative approach was selected for this study, and semi-structured interviews were conducted with six different buyers of road transport services. By using a modified version of The Pentagon Model, different aspects were analyzed in order to identify organizational characteristics and qualities that will improve the possibility for buyers of road transport to contribute to a safer road transport in Northern Norway and thereby contribute to fewer accidents and near-misses. The following characteristics and qualities were identified: 1) the importance of developing a detailed formal contract with the provider of road transport; 2) being aware of the possibilities with new technologies; 3) understanding that the decision criteria for ordering transport can influence road transport safety; 4) seeing the importance of good communication with both the transport organization and the authorities; 5) recognizing that knowledge of and trust in a transport organization is important but could also affect judgement regarding revisions and controls. This study suggests that buyers of road transport services can contribute to a safer road transport in northern Norway by emphasizing these five characteristics and qualities.

This paper presents the design of a suspension system for a Heavy Goods Vehicle (HGV). Four types of linear and non-linear, passive and semi-active suspension systems are modelled with Quarter Vehicle Model (QVM). A modified control law is proposed for the semi-active suspension system that uses a Proportional, Integral, Derivative (PID) controller. Suspension systems are designed by performing multi-objective optimization with road damage and goods damage as design criteria. In current optimization problems, objective function calculation is costly in terms of computational resources and time. Thus, it is necessary to reach actual optimal values in fewer generations with a small population. A fast-converging optimization algorithm is proposed to save computational cost and is used to design suspension systems. The results of the proposed algorithm are compared with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed algorithm saves a substantial amount of computational cost by fast convergence with a small population. Our results show that the semi-active suspension system with proposed control law performs better in terms of road-friendliness and goods safety.

Transportation of Dangerous goods by road may have serious consequences in case of an accident occur. The consequences of a road accident of a heavy goods vehicle carrying dangerous goods may affect not only the truck driver but also the nearby population present. Routing selection is a complicated issue influenced from a number of parameters that may vary during the day, a week or a month. The purpose of the research is to develop a preliminary tool concerning the Transportation of Dangerous Goods which will prove whether a risk analysis using real time data (traffic flows, meteorological conditions, etc.) can offer higher level of safety to the society and the personnel involved in the transportation. The final goal is to enhance safety by making the Dangerous Goods (DG) Risk transportation totally digitalized as a risk management process with real time data acquisition and real time risk assessment through an online platform linked with Global Positioning System (GPS). During the research the risk analysis conducted taking into account all critical parameters for two selected routes. All the necessary data derived from annual statistical data and “simulated” real time data. Data collected concerned all the critical parameters and constraints in order to compare the results to be comparable. Risk quantification was implemented using the DG Quantitative Risk Assessment Model (QRAM) and was illustrated in terms of F/N curves. The results of this research were compared with the ones existed till today which are calculated based on annual statistical data for the above-mentioned factors. The results obtained were compared by means of Societal Risk expressed by Expected Value (EV) and showed that specific factors affect the final routing selection because of the calculated risk.

This article is related to using modern LiDARs and neural networks based algorithms for vulnerable road users (VRU) detection. The problem is obvious especially when considering blind spots of heavy goods vehicles. LiDARs have developed a lot recently and the results indicate that adults can be detected up-to 75 m distance from the sensor even thought that pattern recognition requires sufficient point cloud-resolution. Two different LiDAR brands have been compared to understand costbenefits between LiDAR technologies. The results have been conducted using an automated passenger car while considering feasibility to big trucks. Due to automotive requirements, the processing rate is also considered since usually, the main bottleneck is computation power, which is limited in automotive products. The used neural network algorithm is Yolo based and has been designed for VRU detection.

Fast-acting pneumatic valves, combined with a slip-control braking algorithm, have recently been used to improve the straight-line braking performance of an experimental heavy goods vehicle, on low friction roads, by 16%. This paper describes how the fast-acting valves, which were central to the aforementioned research, were designed for use on a commercial vehicle. Design equations, as well as a generalized design method, are first presented for the fast-acting bistable pneumatic valve. A pressure observer is developed to predict the brake chamber pressure in cases where a pressure transducer is mounted upstream. A simple fault detection algorithm is then introduced, which utilizes some of the calculations made in the pressure observer, and is shown to correctly identify faults on a real vehicle. Performance comparisons are made between the new modulator and a conventional heavy goods vehicle electro-pneumatic brake system. Closed-loop frequency response tests show that the control bandwidth of brake chamber pressure on a heavy goods vehicle can be increased from 1.5 Hz to 10 Hz using the new hardware.

This paper proposes a novel passenger car equivalent and capacity estimation methods that determine the effect of deceleration and acceleration performance of heavy goods vehicles on the traffic flow and estimate the capacity to facilitate rescheduling container carriers. The development of the new methods considers the driver’s perception of time and braking competency level, and the out of the box vehicle displacement approach. The safety gap between the following and leading vehicle should provide sufficient time and space for the driver to bring the vehicle safely to a standstill, to prevent accidents and facilitate enough space for maneuvering. As a case study, the authors have collected and utilized the automatic traffic counters data and the average annual daily flow data from manual counting for the road connecting the Liverpool containership port with North-West England and the rest of the UK. However, the capacity estimation method is suitable for all urban roads and streets that have controlled intersections in the UK and the USA. The authors have found that the passenger car equivalent method is directly proportional to the vehicle’s speed, and gross mass and the capacity method is inversely and directly proportional to perception time and braking competency level, respectively. Also, building an extra lane will allow meeting the ports targets.

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., Highlights • Educational, infrastructural, and legislative change would improve driver safety. • Commercial drivers are essential stakeholders for a safe road system in Nepal. • Inadequate crash investigation means heavy goods vehicle drivers may be unfairly blamed. • Lack of a professional safety culture perpetuates poor driving practices.

P138 Table 1Employment status of COVID-19 dischargesN 138 Essential services 41 (30) Office/admin 37 (27) Healthcare 16 (12) Non essential services 15 (11) Public transport 10 (7) Enforcement 4 (3) Heavy Goods Vehicle driver 3 (2) Carers 2 (1) Unknown 10 (7) ConclusionOur preliminary data suggests significant symptom burden within 6 weeks post discharge after a COVID-19 infection admission, which may impact on the ability of patients to return to work. In the present analysis there was no significant interaction between return-to-work status and covid severity.

Heavy goods vehicles (HGVs) are involved in 4.5% of police-reported road crashes in Europe and 14.2% of fatal road crashes. Active and passive safety systems can help to prevent crashes or mitigate the consequences but need detailed scenarios based on analysis of region-specific data to be designed effectively; however, a sufficiently detailed overview focusing on long-haul trucks is not available for Europe. The aim of this paper is to give a comprehensive and up-to-date analysis of crashes in the European Union that involve HGVs weighing 16 tons or more (16 t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis, as follows. Crash statistics based on data from the Community Database on Accidents on the Roads in Europe (CARE) provide a general overview of crashes involving HGVs. These results are complemented by a more detailed characterization of crashes involving 16 t+ trucks based on national road crash data from Italy, Spain, and Sweden. This analysis is further refined by a detailed study of crashes involving 16 t+ trucks in the German In-Depth Accident Study (GIDAS), including a crash causation analysis. The results show that most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on nonhighway roads. Three main scenarios for 16 t+ trucks are characterized in-depth: rear-end crashes in which the truck is the striking partner, conflicts during right turn maneuvers of the truck with a cyclist riding alongside, and pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g., distraction) were the main crash causation factor in 72% of cases in the rear-end striking scenario while information access problems (e.g., blind spots) were present for 72% of cases in the cyclist scenario and 75% of cases in the pedestrian scenario. The three levels of data analysis used in this paper give a deeper understanding of European HGV crashes, in terms of the most common crash characteristics on EU level and very detailed descriptions of both kinematic parameters and crash causation factors for the above scenarios. The results thereby provide both a global overview and sufficient depth of analysis of the most relevant cases and aid safety system development.

This research addresses the deficit of empirical investigation of changes in industrial and warehouse property markets in the UK. It uses business rates (rating list) data for England and Wales to reveal changes in the quantum and distribution of premises over the last decade. Spatio-temporal analysis using geographical information systems identifies where new industrial and warehouse premises have been developed and examines spatial changes in the distribution of premises between the two sectors. The research focuses on the development of new large distribution warehouses (LDWs) to investigate whether there is a new pattern of warehouse premises located in close proximity to junctions on the national highway network. Findings confirm the emergence of a dynamic distribution warehouse property market where “super sheds” have been developed in areas with high levels of multi-modal connectivity. The comprehensive spatio-temporal analysis of all industrial and warehouse premises in England and Wales reconfigures the previously recognised Midlands “Golden Triangle” of distribution warehouses to a “Golden Pointer” and reveals the emergence of a rival “Northern Dumbbell” of distribution warehouse premises in the North of England. Further analysis using isochrones confirms that 85% of the population of Great Britain is situated within four hours average heavy goods vehicle drive time of these two concentrations of super sheds and over 60% of all LDWs floorspace is within 30 minutes’ drive of intermodal rail freight interchanges.

Articulated heavy goods vehicles and long combination vehicles offer improved efficiency and emissions but reduced low-speed manoeuvrability and high-speed stability compared to rigid lorries. Active control systems can help to address these issues but require additional instrumentation, particularly articulation angle sensing. Existing commercial and research solutions for articulation sensing are limited either in terms of measurement accuracy or practicality. In this paper, a camera-based articulation angle sensing concept using template-matching and an Unscented Kalman Filter is investigated, including detailed simulation and full-scale vehicle experiments. The effects of aliasing and trailer pitch angle are studied, and a correction model for trailer pitch is proposed. The sensing system demonstrates superior measurement accuracy compared to the published literature, with root mean square errors of 0.8°–1.8° for articulation angles up to 37° in full-scale experiments. The sensor solution proposed in this work addresses more of the practical criteria for this problem than the comparable solutions in the literature. It does so through the novel camera and image processing system which is unique to this application. The proposed sensor offers acceptable measurement accuracy in real-time, is non-contact, requires minimal knowledge of trailer parameters and is compatible with semi-trailers and rigid draw-bar trailers.

In October 2014, France abandoned the implementation of the ecotaxe, a major country-wide Electronic Tolling System (ETS) designed to charge for the use of national and local roads, which were not covered by the traditional toll system. The ecotaxe originated from a political consensus and was designed with the collaboration of business stakeholders. However, unforeseen implementation difficulties resulted in a renouncement at a late stage, when the infrastructure was already deployed. According to a recent report from the French body in charge of auditing public expenses, it generated a cost of 953 million euros. In analysing what happened during the policy delivery stage, this paper provides insights to policymakers in countries where ETS is envisaged. The ETS system was piloted in summer 2013, and the “go live” date was 1st September 2014. Data was collected ‘live’, in March 2014, featuring 21 interviews, with the aim of better understanding the expected challenges and impacts on the business stakeholders. At the time, stakeholders accepted that the project would go ahead: while further implementation challenges remained, few anticipated them to fully derail the project within 6 months. Retrospective analysis of the data collected in March 2014 can help to deepen policymakers’ insights into why the project ultimately failed and better understand the main lessons to be learnt. The findings show that the ecotaxe, presented as environmental taxation by policymakers, had been in reality perceived and accepted by business stakeholders as more of an infrastructure tax. Interestingly, this in itself does not explain the failure. The main explanation is to be found in the perceived inequities associated with the charging approach, excluding privately-operated motorways, and the failure of the ad valorem surcharging system designed as a means of passing the tax costs to shippers. These findings should be valuable for policymakers anywhere the introduction of a similar ETS system is being contemplated.

In 2017, the newly installed Dutch government announced in its coalition agreement to introduce a distancebased heavy goods vehicle charge, similar to the charges levied in other European countries. To study the possible transport impacts, we applied available models and methods in preparation for the introduction of this truck charge in the Netherlands in 2023, in order to present decision information to the government on different aspects of the charge. In this paper we present the analysis of different implementation scenarios for a distancebased truck charge. Different behavioural responses can be expected in terms of freight transport demand, mode choice, logistic efficiency, and route choice. Many studies however lack sufficient detail to properly describe theimpact of road charges for HGV on OD flows and freight traffic. In our contribution we explore the bandwidth of impacts of different pricing schemes, using strategic transport models for freight demand and traffic assignment,with detailed modal split and route choice models, ensuring a proper representation of generalsed transport costs. We explain how we use available transport models in an overarching analytical framework to make acomprehensive impact assessment of the different responses, and to decompose the impacts on the different responses. Final impacts are quantified in terms of freight demand (spatial pattern of transport flows), modal split and traffic flows (route choice, and congestion). Depending on the pricing scenario the tonne kilometres decrease by 0.4%–4.8% on average. The modal shift impacts are stronger on longer transport distances: this is explained both by the larger impact of a distance-based charge on these routes, and by higher substitution possibilities to barge or rail. The results indicate that the overall impacts of the introduction of the different charging alternatives are moderate. However, the network impacts at local level can be substantial due to the impact of re-routing of truck trips to avoid charge.

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 HGV drivers (98.5% men) recruited across an international logistics company within the midland’s region, UK. Sleep duration and efficiency were assessed via wrist-worn accelerometry (GENEActiv) over 8 days. Proportions of drivers with short sleep duration (Results58% of drivers had a mean sleep duration of ConclusionsThe high prevalence of short sleep duration and insufficient sleep quality (efficiency) rate suggest that many HGV drivers have increased risk of excessive daytime sleepiness, road traffic accidents and chronic disease. Future sleep research in UK HGV cohorts is warranted given the road safety and public health implications.

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.

Dissertação de Mestrado em Design com a especialização em Design de Produto apresentada na Faculdade de Arquitetura da Universidade de Lisboa para obtenção do grau de Mestre. A mobilidade é algo que se torna vital e imprescindível numa sociedade. É possível integrar diversos conceitos de mobilidade e de tecnologia em equipamentos e/ou serviços. Atualmente, embora este tipo de conceitos sejam abordados de forma individual, procuram sempre melhorar a qualidade de vida do utilizador, e das pessoas que o rodeiam, e do próprio meio ambiente, sempre com o intuito de o tornar mais eficiente, eficaz e economicamente sustentável. No entanto, vigoram modos de produzir e utilizar os produtos sob estéticas e pressupostos pouco modernos e apelativos, quando comparados com outros de categoria equivalente, não correspondendo na totalidade às demandas e aos anseios de quem pretende usufruir. As sociedades abriram espaço para os veículos autónomos, considerados como o futuro do automóvel e da própria mobilidade, criando novos desafios para os construtores. Neste contexto e beneficiando da constante modernização e alteração do paradigma da mobilidade rodoviária, a presente investigação desenvolveu um veículo pesado para transporte de mercadorias e de condução autónoma com o intuito de otimizar o transporte de bens de consumo nas áreas interurbanas. Esta investigação recairá numa metodologia mista, não-intervencionista e intervencionista de caráter qualitativo. São utilizados métodos não intervencionistas aplicados no estado da arte e estudos de caso, e métodos intervencionistas, aplicados nas entrevistas e na investigação ativa, podendo corroborar as hipóteses levantadas e contribuir para um maior conhecimento nesta área de estudo. ABSTRACT: Mobility is something that becomes vital and essential in a society. It is possible to integrate several concepts of mobility and technology in equipment and / or services. Currently, although these types of concepts are addressed individually, they always seek to improve the quality of life of the user, and the people around him, and the environment itself, always with the aim of making it more efficient, effective and economically sustainable. However, there are ways to produce and use products under aesthetics and assumptations not very modern and appealing, when compared with others of an equivalent category, not fully meeting the demands and desires of those who want to enjoy them. Societies have opened up space for autonomous vehicles, considered as the future of the automobile and mobility itself, creating new challenges for manufacturers. In this context and benefiting from the constant modernization and alteration of the road mobility paradigm, the present investigation has developed a heavy vehicle for the transport of goods and autonomous driving in order to optimize the transport of consumer goods in the interurban areas. This investigation will fall on a mixed, non-interventionist and qualitative interventionist methodology. Non-interventionist methods applied in the state of the art and case studies are used, and interventionist methods, applied in interviews and active research, which can corroborate the hypotheses raised and contribute to greater knowledge in this area of study. N/A

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.

In this study, the authors numerically simulated heavy goods vehicle (HGV) fire scenarios in order to investigate the tenable conditions of a two-way traffic road tunnel with point-extraction ventilation system consisting of water spray system. A computational fluid dynamics (CFD) model was used to simulate the interaction between the point-extraction ventilation and the water spray system. A total of four cases were carried out in a 600 m tunnel model. Distributions of smoke, temperature, visibility, and CO concentration profiles in tunnels axial-sections for the considered model and point-extraction ventilation system were provided. Results show that the characteristics of tenable conditions for the tunnel fires having water spray are distinctive from those of the tunnel without water spray and ventilation. Tunnel with the point-extraction ventilation and water spray system can provide the relative safety region for occupants at the outside of the water spray zone once HGV fires occur.

Heavy goods vehicles turning left across the path of a cyclist cause approximately 40% of the most serious injuries and fatalities to cyclists. A collision avoidance strategy is proposed in this study. Based on measurement of the current position and motion of the cyclist relative to the heavy goods vehicle, the future position of the cyclist after a short period is predicted by assuming constant acceleration and constant yaw rate. The brakes on the heavy goods vehicle are applied if the predicted future cyclist position overlaps the future envelope of the heavy goods vehicle. A parametric study shows that a high portion of potential collisions could be prevented in this way. Nineteen fatal accidents involving left-turning heavy goods vehicles and cyclists are reconstructed in simulation from police report files and the collision avoidance system is simulated. It is concluded that the introduction of the proposed collision avoidance strategy could possibly have prevented up to 18 of the 19 deaths in these accidents.

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.

In Norway, approximately 688 people are injured each year in traffic accidents involving heavy goods vehicles (HGVs), and for every third road fatality there is an HGV involved. Norway has approximately 35% more fatalities per inhabitant resulting from accidents involving HGVs compared to the rest of Europe. These numbers suggest that interventions are needed to reduce road accidents involving HGVs in Norway. This paper contributes to the field of road transportation research by identifying how strategic management decisions can affect road transport organizations’ ability to develop a good safety culture. Semi-structured interviews with 16 participants were conducted. The findings suggest that road transport organizations that choose a low-cost leadership strategy struggle to be profitable. Moreover, such strategies lead to high rivalry between organizations. Such rivalry makes it difficult to be profitable, hence there are fewer resources available to invest in building a good safety culture. In contrast, road transport organizations that choose a differentiation or focus leadership strategy are more likely to be profitable. As a consequence, they have more resources to invest in building a safety culture.

Heavy Goods Vehicle (HGV) collisions are responsible for a disproportionate number of urban vulnerable road user casualties (VRU - cyclists and pedestrians). Blind-spots to the front and side of HGVs can make it difficult (sometimes impossible) to detect close proximity VRUs and may be the cause of some collisions. The current solution to this problem is to provide additional mirrors that can allow the driver to see into the blind-spots. However, keeping track of many mirrors requires frequent off-road glances which can be difficult to execute during demanding driving situations. One suggestion is that driving safety could be improved by redesigning cabs in order to reduce/remove blind-spot regions, with the aim of reducing the need for mirrors, and increasing detection rates (and thereby reducing collisions). To examine whether mirrors delay driver responses we created a series of simulated driving tasks and tested regular car drivers and expert HGV drivers. First we measured baseline reaction times to objects appearing when not driving ('Parked'). Participants then repeated the task whilst driving through a simulated town (primary driving tasks were steering, braking, and following directional signs): driving slowed reaction times to objects visible in mirrors but not to objects visible through the front windscreen. In a second experiment cognitive load was increased, this slowed RTs overall but did not alter the pattern of responses across windows and mirrors. Crucially, we demonstrate that the distribution of mirror RTs can be captured simply by the mirror's spatial position (eccentricity). These findings provide robust evidence that drivers are slower reacting to objects only visible in eccentric mirrors compared to direct viewing through the front windscreen.