Search Results (25)

This study examines crash involvement, safety training exposure, and e-learning readiness among commercial heavy goods vehicle (HGV) drivers in Ethiopia. Data were collected through a cross-sectional survey of 202 male drivers operating along the Addis Ababa–Djibouti trade corridor, a high-risk freight route that carries approximately 95% of Ethiopia’s international trade and serves as the country’s primary gateway to global markets. The survey assessed crash history, safety training experiences, perceived safety challenges, and barriers to and motivators for e-learning adoption. Results indicate persistently high crash involvement despite widespread participation in conventional classroom-based training, suggesting a gap between training provision and real-world safety outcomes. Older and mid-career drivers exhibited higher crash involvement, highlighting a gap between training provision and behavioral or operational safety outcomes, while younger and more educated drivers showed greater readiness for technology-enhanced training. Although most drivers valued safety training, many perceived existing programs as repetitive, insufficiently interactive, and poorly aligned with operational demands. Key facilitators for e-learning adoption included flexible schedules, ease of use, and motivational support, whereas limited digital skills and low perceived usefulness remained barriers for some groups. The findings highlight the need for age-responsive, flexible, and interactive e-learning approaches to complement traditional training and address persistent safety risks, such as fatigue and unsafe driving behaviors. These approaches also support scalable, technology-enhanced interventions tailored to Ethiopia’s high-risk freight corridors, while guiding future research directions. Full article

While an advanced emergency braking system (AEBS) significantly improves the safety of a heavy goods vehicle (HGV), current implementations face limitations including inadequate scenario coverage for vulnerable road users (VRUs), overriding driver control and limited human–machine collaboration mechanisms, and an insufficient consideration of blind spot challenges in HGVs. To improve the adaptability of the AEBS for HGVs, this study proposes and validates a novel 2D AEBS control algorithm incorporating driver’s control and 3D visibility of VRUs. The proposed algorithm is designed to firstly identify the motion state scenarios based on the spatial relationship between the HGV and VRU. Then, based on the scenario classification result, the proposed algorithm determines whether the HGV needs to brake in the current scenario according to the 2D time to collision for both entities to reach the potential collision area while maintaining their current speeds. Finally, for situations requiring braking, it evaluates whether safety can be ensured under three conditions: the ego vehicle in free driving, the ego vehicle under driver-controlled braking (considering the 3D visibility of the VRU), and the ego vehicle under 2D AEBS-controlled braking. According to the test results, the proposed algorithm can deal with the VRU crossing scenario and leverage the driver’s control capabilities while utilizing AEBS as a safety net function. Full article

Internal combustion engine vehicles damage the environment and public health by emitting toxic fumes, such as CO₂ or CO and other trace compounds. The use of electric cars helps to reduce the emission of pollutants into the environment due to the use of batteries with no direct and local emissions. However, accidents of battery electric vehicles pose new challenges, such as thermal runaway. Such accidents can be serious and, in some cases, may result in uncontrolled overheating that causes the battery pack to spontaneously ignite. In particular, the most dangerous vehicles are heavy goods vehicles (HGVs), as they release a large amount of energy that generate high temperatures, poor visibility, and respiratory damage. This study aims to determine the potential consequences of large BEV fires in road tunnels using computational fluid dynamics (CFD). Furthermore, a comparison between a BEV and an ICEV fire shows the differences related to the thermal and the toxic impact. Furthermore, the adoption of a longitudinal ventilation system in the tunnel helped to mitigate the BEV fire risk, keeping a safer environment for tunnel users and rescue services through adequate smoke control. Full article

This study explores the impact of road transport on the environment, focusing on noise pollution. Using high-resolution, one-minute data from a low-cost environmental sensor, this research examines traffic flow dynamics, meteorological influences, and their relationship to noise along a major transport corridor. The methodology combines cluster analysis and descriptive statistics to evaluate the effects of deploying a Smart Motorway Variable Speed Limit (SMVSL) system over a six-month monitoring period. Results indicate that SMVSL systems not only smooth traffic flow but also significantly reduce noise variability, particularly during peak hours, thus mitigating noise peaks associated with adverse health outcomes. LAeq values were found to differ modestly between day and night, with clustering revealing a reduction in extreme noise events (LAmax > 70 dB(A)) in SMVSL scenarios dominated by heavy goods vehicles. This study further identifies associations between unmanaged speed regimes and elevated noise levels, enriching our understanding of the environmental impacts of unregulated traffic conditions. These findings inform sustainable planning and policy strategies aimed at improving urban environmental quality and enhancing public health outcomes. Full article

The transport sector is responsible for nearly a quarter of global CO₂ emissions annually, underscoring the urgent need for cleaner, more sustainable alternatives such as electric vehicles (EVs). However, the electrification of heavy goods vehicles (HGVs) has been slow due to the substantial power and battery capacity required to match the large payloads and extended operational ranges. This study addresses the research gap in battery pack design for commercial HGVs by investigating the electrical and thermal behaviour of a novel battery pack configuration using an electro-thermal model based on the equivalent circuit model (ECM). Through computationally efficient 1D modelling, this study evaluates critical factors such as cycle ageing, state of charge (SoC), and their impact on the battery’s range, initially estimated at 285 km. The findings of this study suggest that optimal cooling system parameters, including a flow rate of 18 LPM (litres per minute) and actively controlling the inlet temperature within ±7.8 °C, significantly enhance thermal performance and stability. This comprehensive electro-thermal assessment and the advanced cooling strategy set this work apart from previous studies centred on smaller EV applications. The findings provide a foundation for future research into battery thermal management system (BTMS) design and optimised charging strategies, both of which are essential for accelerating the industrial deployment of electrified HGVs. Full article

Accidents involving cyclists and trucks are among the most severe road accidents. In 2021, 199 cyclists were killed in accidents involving a truck in the EU. The main accident situation is a truck turning right and a cyclist going straight ahead. A large proportion of these accidents are caused by the inadequate visibility in an HGV (Heavy Goods Vehicle). The blind spot, in particular, is a significant contributor to these accidents. A BSD (Blind Spot Detection) system is expected to significantly reduce these accidents. There are only a few studies that estimate the potential of assistance systems, and these studies include a combined assessment of cyclists and pedestrians. In the present study, accident simulations are used to assess a warning and an autonomously intervening assistance system that could prevent truck to cyclist accidents. The main challenges are local sight obstructions such as fences, hedges, etc., rule violations by cyclists, and the complexity of correctly predicting the cyclist’s intentions, i.e., detecting the trajectory. Taking these accident circumstances into consideration, a BSD system could prevent between 26.3% and 65.8% of accidents involving HGVs and cyclists. Full article

This review explores the performance and reliability of power semiconductor devices required to enable the electrification of heavy goods vehicles (HGVs). HGV electrification can be implemented using (i) batteries charged with ultra-rapid DC charging (350 kW and above); (ii) road electrification with overhead catenaries supplying power through a pantograph to the HGV powertrain; (iii) hydrogen supplying power to the powertrain through a fuel cell; (iv) any combination of the first three technologies. At the heart of the HGV powertrain is the power converter implemented through power semiconductor devices. Given that the HGV powertrain is rated typically between 500 kW and 1 MW, power devices with voltage ratings between 650 V and 1200 V are required for the off-board/on-board charger’s rectifier and DC-DC converter as well as the powertrain DC-AC traction inverter. The power devices available for HGV electrification at 650 V and 1.2 kV levels are SiC planar MOSFETs, SiC Trench MOSFETs, silicon super-junction MOSFETs, SiC Cascode JFETs, GaN HEMTs, GaN Cascode HEMTs and silicon IGBTs. The MOSFETs can be implemented with anti-parallel SiC Schottky diodes or can rely on their body diodes for third quadrant operation. This review examines the various power semiconductor technologies in terms of losses, electrothermal ruggedness under short circuits, avalanche ruggedness, body diode and conduction performance. Full article

The paper’s main aim is to present the impact on the city’s road traffic generated by the Port of Gdynia’s operations and propose the optimal solution for transport network development around the port. Firstly, the authors demonstrate a case study determining the impact of heavy goods vehicles (HGVs) generated by port facilities on local traffic. To this end, the average travel time of cars in the network on selected measurement sections is conditioned on the varying number of HGVs generated by the port. Next, based on the data obtained from the traffic monitoring system, PTV Vissim software is used as a modelling tool to analyse and assess the impact on local traffic. Finally, considering the analysis’ results, the vulnerability of the transport network is discussed. The optimal solution for the transport network around the port’s area is proposed. The paper is an extended version of the materials presented at the XIX Maritime Traffic Engineering Conference. Full article

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. Full article

Road traffic accidents are a major health concern all over the world. Each year, 1.3 million people die in fatal road traffic accidents. Fatal and serious heavy goods vehicle (HGV) crashes are over-represented in many countries. This paper is a contribution to the road safety literature and has two aims. First, the study seeks to identify important factors in managing road safety for work-related driving of HGVs. Second, the study proposes an overall framework for how safety training could be executed and its overall content. Methods used were a literature review and a case study. The results show that important factors for management of road safety could be arranged at different levels: governmental level, third-party level, organizational level and driver level. Most important is that a systematic approach to road traffic safety for HGVs is essential. Every party is jointly responsible for road traffic safety, and parties must communicate and work together to increase road traffic safety for work-related driving of HGVs. By developing a safety training program for all parties in the system, the study proposes a method for increased communication, collaboration and cooperation between parties. Full article

The Rear Underrun Protective Device (RUPD) is a basic means to prevent a passenger car from running under the rear of a motor truck (also referred to as heavy goods vehicle or HGV) or a trailer in the case of a rear-end collision and thus to reduce deformations of the car’s passenger compartment (“survival space”). In many publications dealing with such devices, the increasing of RUPD stiffness by applying innovative design solutions or using high-strength materials has been considered; in some designs, additional RUPD components are introduced to absorb the impact energy. In this paper, a review of the RUPD designs is presented and some of them are analyzed, where their characteristics that are essential for the compliance with normative market requirements are indicated. Results of the authors’ research on the selection of an energy absorber incorporated in the rear impact guard bar of an HGV are presented as well. Full article

This study complements our previous work with a simultaneous analysis of user safety and road tunnel resilience. We developed a computational fluid dynamics (CFD) model and simulated the corresponding egress process to evaluate the risk level of users exposed to different types of fire, such those which might occur on the undisrupted lane of a partially closed tube tunnel due to a traffic accident, or in the adjacent tube when used for two-way traffic in the case of the complete closure of the tube involved in the accident. The CFD results showed that: (i) better environmental conditions were found with the partial closure of the tube rather than the complete one; (ii) additional benefits can be achieved by activating variable message signs (VMSs) that suggest an alternative itinerary for heavy good vehicles (HGVs) only; (iii) safety issues for human health may arise only in the case of a 100 MW fire, occurring during the complete closure of the tube and the use of the parallel one for two-way traffic. The findings of the CFD simulations were subsequently used to perform a quantitative risk analysis (QRA) based on a probabilistic approach. The findings of the QRA were found to be consistent with those obtained by the tunnel resilience analysis. In particular, the lowest risk level for user safety was found with the partial closure of the tube instead of the complete one, and by activating the VMSs to redirect HGVs only towards an alternative itinerary. This finding was found to correspond to a higher resilience index of the tunnel (i.e., a lower resilience loss due to a traffic accident occurring in a tube). This study increases our knowledge on certain relevant aspects of the operating conditions of tunnels and can serve as a possible reference for tunnel management agencies (TMAs) in their choice of the most appropriate arrangement to recover the functionality of a tunnel taking into account both user safety and resilience at the same time. Full article

In Europe, heavy goods vehicles (HGVs) are disproportionately involved in serious and fatal collisions with vulnerable road users (VRUs). An interrogation of 2019 national crash data for Great Britain (Stats19) suggested that detection of cyclists and pedestrians in the nearside and front blind spots of HGVs is still a significant problem during forward or left-turn manoeuvres of the HGV. To improve detection, Transport for London introduced Direct Vision and Safe System Standards in 2021 for HGVs entering the Greater London area. This research assessed the efficacy of one of the Safe System requirements—the fitment of sensors to detect vulnerable road users on the nearside of the vehicle. A physical testing procedure was developed to determine the performance of a sensor system meeting the Transport for London Safe System requirements. Overall, the Safe System compliant sensor system missed 52% of expected detection nodes on the nearside of the vehicle. A total of 56% of the “stop vehicle” nodes, 45% of the “slow down” and 48% of the “proceed with caution” nodes were not recognised. The most forward sensor did not fully cover the front-left corner blind spot, missing 70% of the desired detection nodes. Nearside sensor systems fitted to Safe System requirements may cover a reasonable area but could still leave many undetected zones to the left and front of the vehicle. Standardising sensor range and location could help to eliminate sensor blind spots. Mandating additional front sensors would help cover the blind spot at the front-left corner of the HGV. Full article

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. Full article

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels. Full article