Academic literature on the topic 'Heavy vehicle crashes'
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Journal articles on the topic "Heavy vehicle crashes"
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Rangam, Harikrishna, Sathish Kumar Sivasankaran, and Venkatesh Balasubramanian. "Investigation of Injury patterns in Heavy-duty Single Vehicle crashes based on real-world accident data in Tamilnadu, India." Journal of Road Safety 32, no. 2 (May 1, 2021): 30–40. http://dx.doi.org/10.33492/jrs-d-20-00127.
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According to the reports of NITI (National Institute of Transforming India) Aayog Freight 2018, Road freight is the prime mode (59%) of transport in India with the highest per ton-mile cost than rail or water freight (NITI Aayog, 2018). This road freight usually uses heavy-duty vehicles to transmit voluminous goods and services to the destination in time. Due to this, the heavy-duty vehicle population increased on the Indian roads. Heavy-duty vehicle crashes cause a substantial economic burden to the nation and result in more severity to the involved because of differences in weight, speed, and size. Among heavy-duty vehicle crashes, a significant proportion of crashes are heavy-duty single-vehicle crashes. Single-vehicle crashes are those crashes where the vehicle drivers either involve in self-skidding or hit a stationary object (like a tree). The purpose of this study is to investigate the injury pattern in heavy-duty single vehicle crashes. For this study, the data is extracted from the RADMS (Road Accident Database Management System) database and linked with hospital data. This data includes demographic information, road, environmental and injury characteristics. Later, descriptive statistics performed on the dataset to analyse all heavy-duty single-vehicle crashes between January 2013 and December 2018. Overall, 4704 single heavy-duty vehicle crashes occurred during this period, among which 1244 were fatal crashes. Results show that male drivers aged 26 to 64 years old suffered more fatalities (88%), followed by the 18-25 age group (8%). Examination of injury information found that heavy-duty vehicle drivers mostly sustained multiple injuries (9.05%), head injuries (5.05%), followed by leg injuries (4.29%). The results showed that specific road and environmental factors increase the chance of fatal crashes among heavy-duty vehicle drivers. Furthermore, the proposed study gives insight into the injury characteristics and key contributing factors causing heavy-duty single-vehicle crashes. Finally, this study provides appropriate countermeasures and techniques that can mitigate heavy-duty single-vehicle collisions.
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Wang, Chen, Ming Zhong, Hui Zhang, and Siyao Li. "Impacts of Real-Time Traffic State on Urban Expressway Crashes by Collision and Vehicle Type." Sustainability 14, no. 4 (February 16, 2022): 2238. http://dx.doi.org/10.3390/su14042238.
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With the rapid development of urban expressway systems in China in recent years, traffic safety problems have attracted more attention. Variation of traffic flow is considered to have significant impact on the safety performance of expressways. Therefore, the motivation of this study is to explore the mechanism of how the variation of traffic flow measurements such as average speed, speed variation and traffic volume impact the crash risk. Firstly, the crashes were classified according to crash type and vehicles involved: and they are labeled with rear-end collisions or side-impact collisions, they are labeled with heavy-vehicle related collisions or light-vehicle related collisions as well. Then, the corresponding crash data were aggregated based on the similarity of traffic flow conditions and types of crashes. Finally, a random effect negative binomial model was introduced to consider the heterogeneity of the crash risk due to the variance within the traffic flow and crash types. The results show that the significant influencing factors of each type of crashes are not consistent. Specifically, the percentage of heavy vehicles within traffic flow is found to have a negative impact on rear-end collisions and light-vehicle-related collisions, but it has no obvious correlation with side-impact collisions and heavy-vehicle-related collisions. Average speed, speed variation and traffic volume have an interactive effect on the crash rate. In conclusion, if the traffic flow is with higher speed variation within lanes and is with lower average speed, the risk of all types of crashes tends to be higher. If the speed variation within lanes decreases and the average speed increases, the crash risk will also increase. In addition, if the traffic flow is under the conditions of higher speed variation between lanes and lower traffic volume, the risk of rear-end collisions, side-impact collisions and heavy-vehicles related collisions tend to be higher. Meanwhile, if the speed variation between lanes decreases and the traffic volume increases, the crash risk is found to increase as well.
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Tulu, Getu, Robert Lisinge, and Bikila Wedajo. "Heavy vehicle crashes in Addis Ababa: Relationship between contributing factors and severity of outcomes." Journal of Sustainable Development of Transport and Logistics 7, no. 2 (November 19, 2022): 25–40. http://dx.doi.org/10.14254/jsdtl.2022.7-2.2.
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Random parameter logit regression is used to analyze police-reported data on 8,253 heavy vehicle-related crashes in Addis Ababa between July 2014 and June 2017. The analysis shows that fatal crashes are more likely to occur during the day and on weekdays, particularly when the circulation of trucks is high. It also shows the disproportionately high involvement of young drivers in heavy vehicle crashes in the city. However, the likelihood of crashes resulting in fatalities and serious injuries increases slightly compared to those resulting only in property damage as the age of drivers increases. Low levels of drivers' education, the fact that drivers are often not the owners of vehicles, ownership of vehicles by companies and government organizations, and inappropriate road medians' inappropriate design are also significant contributors to fatal crashes. Curbing deaths and injuries from heavy vehicle crashes in Addis Ababa requires strict enforcement of traffic rules and regulations, particularly speed limits; reforms in driver's training and certification; improved safety culture of vehicle owners and design of road infrastructure. Ethiopia's national road safety strategy launched in July 2022 addresses these issues. Hence the government is taking steps in the right direction.
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Wen, Huiying, Jiaren Sun, Qiang Zeng, Xuan Zhang, and Quan Yuan. "The Effects of Traffic Composition on Freeway Crash Frequency by Injury Severity: A Bayesian Multivariate Spatial Modeling Approach." Journal of Advanced Transportation 2018 (August 7, 2018): 1–7. http://dx.doi.org/10.1155/2018/6964828.
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This study sets out to investigate the effects of traffic composition on freeway crash frequency by injury severity. A crash dataset collected from Kaiyang Freeway, China, is adopted for the empirical analysis, where vehicles are divided into five categories and crashes are classified into no injury and injury levels. In consideration of correlated spatial effects between adjacent segments, a Bayesian multivariate conditional autoregressive model is proposed to link no-injury and injury crash frequencies to the risk factors, including the percentages of different vehicle categories, daily vehicle kilometers traveled (DVKT), and roadway geometry. The model estimation results show that, compared to Category 5 vehicles (e.g., heavy truck), larger percentages of Categories 1 (e.g., passenger car) and 3 (e.g., medium truck) vehicles would lead to less no-injury crashes and more injury crashes. DVKT, horizontal curvature, and vertical grade are also found to be associated with no-injury and/or injury crash frequencies. The significant heterogeneous and spatial effects for no-injury and injury crashes justify the applicability of the proposed model. The findings are helpful to understand the relationship between traffic composition and freeway safety and to provide suggestions for designing strategies of vehicle safety improvement.
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Wiratama, Bayu Satria, Li-Min Hsu, Yung-Sung Yeh, Chia-Che Chen, Wafaa Saleh, Yen-Hsiu Liu, and Chih-Wei Pai. "Joint Effect of Heavy Vehicles and Diminished Light Conditions on Paediatric Pedestrian Injuries in Backover Crashes: A UK Population-Based Study." International Journal of Environmental Research and Public Health 19, no. 18 (September 16, 2022): 11689. http://dx.doi.org/10.3390/ijerph191811689.
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Backover crashes cause considerable injuries especially among young children. Prior research on backover crashes has not assessed the joint effect of heavy vehicles and diminished light conditions on injuries. By analysing the United Kingdom STATS19 crash dataset from 1991 to 2020, this study focused on backover crashes involving paediatric cyclists or pedestrians aged ≤17 years and other motorised vehicles. By estimating the adjusted odds ratio (AOR) of multiple logistic regression models, pedestrians appeared to have 82.3% (95% CI: 1.78–1.85) higher risks of sustaining killed or serious injuries (KSIs) than cyclists. In addition, casualties involved in backover crashes with heavy vehicles were 39.3% (95% CI: 1.35–1.42) more likely to sustain KSIs than those involved in crashes with personal cars. The joint effect of heavy vehicles and diminished light conditions was associated with a 71% increased probability of sustaining KSIs (AOR = 1.71; 95% CI: 1.60–1.83). Other significant joint effects included young children (aged 0 to 5 years) as pedestrian (AOR = 1.92; 95% CI: 1.87–1.97), in diminished light conditions (AOR = 1.23; 95% CI: 1.15–1.31), and with heavy vehicle (AOR = 1.37; 95% CI: 1.28–1.47).
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Hanowski, Richard J., Robert J. Carroll, Walter W. Wierwille, and Rebecca L. Olson. "Light Vehicle-Heavy Vehicle Interactions: A Preliminary Assessment Using Critical Incident Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 22 (September 2002): 1844–47. http://dx.doi.org/10.1177/154193120204602214.
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Two recently completed on-road in situ data collection efforts, one involving local/short haul trucking and the other long-haul trucking, provided a large data set in which to conduct an examination of critical incidents (crashes and near-crashes) that occurred between light vehicles and heavy vehicles. Video and non-video data collected during the two studies were used to characterize critical incidents that were recorded between light vehicle and heavy vehicle drivers. Across both studies, 210 light vehicle-heavy vehicle (LV-HV) critical incidents were recorded. Of these, 78 percent were initiated by the light vehicle driver. Aggressive driving on the part of the light vehicle driver was found to be the primary contributing factor for light vehicle driver initiated incidents. For heavy vehicle driver initiated incidents, the primary contributing factor was poor driving technique. The results suggest that efforts at addressing LV-HV interaction incidents should focus on light vehicle drivers who drive aggressively. Additionally, it is recommended that heavy vehicle drivers might benefit from improved driver training that includes instruction on defensive driving.
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Schindler, Ron, Michael Jänsch, András Bálint, and Heiko Johannsen. "Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data." International Journal of Environmental Research and Public Health 19, no. 2 (January 7, 2022): 663. http://dx.doi.org/10.3390/ijerph19020663.
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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.
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Rassafi, Amir Abbas, Mirbahador Yazdani, and Bahram Shirini. "Cross Sectional Crash Severity Analysis among Various Vehicle Driver Characteristics." Civil Engineering Journal 4, no. 9 (September 30, 2018): 2143. http://dx.doi.org/10.28991/cej-03091146.
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The current study evaluated road crashes in three categories of drivers: passenger car drivers, heavy vehicle drivers and pickup truck drivers. The crash data of road crashes that occurred from 2009 to 2012 in Iranian suburban roads were analyzed. The crashes involved 194,041 damage, 9,677 injury and 1,303 fatality crashes. Because of the ordinal nature of crash severity, ordered logit model was selected for each vehicle driver category. In the passenger car driver category, the independent variables of driver’s gender, driver’s age and driver’s educational level (uneducated, less than high school diploma, high school diploma) were obtained for modeling; in the heavy vehicle driver category, the independent variables of driver’s age and driver’s educational level (uneducated, less than high school diploma) were obtained for modeling, and in the pickup truck driver category, the independent variables of driver’s age and driver’s educational level (uneducated, high school diploma) were obtained for modeling. The variable of driver’s gender with respect to passenger cars shows that crashes by female drivers are more severe than those involving male drivers in suburban roads. Regarding the variable of driver’s age, if the driver’s age increases in each vehicle driver category, the probability of occurrence of a severe crash will decrease. The variable of driver’s educational level shows that the severity of crashes involving a driver that has a low level of education is more compared with a driver that has a high level of education.
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Hassan, Hany M., Nuha M. Albusaeedi, Atef M. Garib, and Hussain A. Al-Harthei. "Exploring the Nature and Severity of Heavy Truck Crashes in Abu Dhabi, United Arab Emirates." Transportation Research Record: Journal of the Transportation Research Board 2517, no. 1 (January 2015): 1–9. http://dx.doi.org/10.3141/2517-01.
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Traffic crashes involving heavy trucks long have been a major concern in the field of traffic safety because of their great effect on accident severity. The emirate of Abu Dhabi, capital of the United Arab Emirates, features a unique situation: several roads designed mainly for truck movement. Even though those roads were constructed more than 10 years ago to decrease the severity of truck-related crashes, no prior studies have examined their effects on traffic safety improvements. The goals of this study were to understand better the nature, characteristics, and causes of heavy truck crashes occurring in Abu Dhabi; to identify the factors associated with crash severities; and to examine the probability of truck crashes involving fatalities on truck roads versus on mixed-vehicle roads. Data were analyzed from a sample of 1,426 heavy truck–related crashes with reported fatalities or injuries that occurred in Abu Dhabi between 2007 and 2013. First, conditional distributions, two-way analysis, and odds ratios were performed. Second, ordered probit and structural equation models were developed. Results indicated that the likelihood of truck crashes involving fatalities was 35% higher on truck roads than on mixed-vehicle roads. In addition, findings showed that human error, driver education, location, road type, and road speed variables were significant in affecting the severity of heavy truck– related crashes. Finally, practical suggestions on how to reduce the number of heavy truck–related crashes in Abu Dhabi are presented and discussed.
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Anderson, Jason, and Salvador Hernandez. "Heavy-Vehicle Crash Rate Analysis: Comparison of Heterogeneity Methods Using Idaho Crash Data." Transportation Research Record: Journal of the Transportation Research Board 2637, no. 1 (January 2017): 56–66. http://dx.doi.org/10.3141/2637-07.
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Studies investigating crash rates by roadway classification are few and far between and even more rare if extended to focus on heavy vehicles. This study explored and compared two advanced econometric methods—random-parameter Tobit regression and latent class Tobit regression—to determine contributing factors for heavy-vehicle crashes per million vehicle miles traveled while accounting for the unobserved heterogeneity present in crash data. The increasing crash rates in Idaho, crash proportion by roadway classification, and available data made an ideal case study. Empirical results show that although the random-parameter Tobit regression model provides better insight into heavy-vehicle crash rates than the fixed-parameter approach, the latent class Tobit regression model is the preferred methodology for the given data set. Traffic volumes, roadway characteristics, and traffic control devices were among the variables found to be statistically significant. Results from this study provide an alternate framework to account for heterogeneity while identifying key factors by roadway classification that influence heavy-vehicle crash rates. The illustrated framework and analysis by roadway classification can provide guidance to transportation agencies and policy makers and prompt future studies to include a latent class analysis, analysis by road classification, or both.
Dissertations / Theses on the topic "Heavy vehicle crashes"
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Edwards, Jason R. "Safety culture and the australian heavy vehicle industry : a concept in chaos : an industry in need." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/72870/1/Jason_Edwards_Thesis.pdf.
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This research proposed a new framework for safety culture and examined the influence that culture has on safety in the heavy vehicle industry. The results gave evidence for an industry wide culture, allowing future safety interventions to be designed in a culturally-relevant manner. Designing culturally-relevant interventions may maximise their effectiveness and reduce the levels of resistance to safety that have been evident in past years.
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(9787226), Ivan Cikara. "Systemic investigations are needed to improve safety in the heavy vehicle transport industry." Thesis, 2022. https://figshare.com/articles/thesis/Systemic_investigations_are_needed_to_improve_safety_in_the_heavy_vehicle_transport_industry/20779381.
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Death and serious injuries caused by heavy vehicle crashes occur daily in the heavy vehicle transport industry, which has been described as the deadliest industry to work in. There is much suffering and grief amongst families caused by these deaths and serious injuries, and there is a significant financial burden costing the economy billions of dollars each year, yet crash investigations do not appear to identify the underlying causes of these crashes and why heavy vehicle drivers, as well as other road users, are being killed or seriously injured. This is a worldwide problem and not unique to any one country. This research has been undertaken to identify whether systemic investigations are needed to improve safety in the heavy vehicle transport industry.
A systemic investigation is the detailed process of collecting and analysing crash information from a broad and varied scope, using a wide range of resources, techniques and methods in order to identify and establish the underlying causes of a crash. The heavy vehicle transport industry operates in a socio-technical system that has been described as a multi-layered hierarchical system, which is multifaceted, non-linear and complex, and contains a level of uncertainty where actors, technologies and tasks are interacting across levels of the hierarchical layers. Their relationships are interlinked and interconnected, having causal ties where there are direct or indirect operational requirements. For this research the socio-technical system has been identified as consisting of government, regulatory/enforcement agencies, supply chain parties, heavy vehicle companies, drivers/co-drivers, and environment/road and vehicles. A part of the heavy vehicle transport industry socio-technical system comprises of policies, rules, legislation and procedures to help guide the decision-making process to ensure both safety and compliance within the system. The intent is captured in the legislation that governs the system where compliance to the legislation is required.
Heavy vehicle crashes are investigated by state and territory police forces as well as regulatory agencies. These police forces and regulatory agencies have a mandate to investigate for the purposes of identifying driver liability, and as a consequence look for blame. However, the recent enactment of the Heavy Vehicle National Law and Compliance and Enforcement legislation does not support this approach and seeks to apportion blame throughout the logistics chain, rather than placing blame on the driver.
This research discovered that there are a number of underlying causes that adversely influence heavy vehicle driver behaviour and contribute to crashes; however, these causes are not usually identified in investigations, with the outcome of an investigation often being to blame the driver. Investigations do not tend to look at the socio-technical system within which the heavy vehicle transport industry operates to identify the interactions and interconnections that can influence and impact upon a driver’s behaviour. In most instances when human errors are identified the investigation ceases with no further exploration as to what caused the human errors.
This research has identified that investigators do not use a systemic investigation methodology, indeed many who have conducted investigations of heavy vehicle crashes have no knowledge of what a systemic investigation is. In addition, this research discovered that investigators did not have the training, skills and competencies or specialist knowledge of the heavy vehicle transport industry to investigate heavy vehicle crashes. These investigators primarily gained their skills and competencies ‘on the job’ through a tacit transfer of knowledge, essentially learning as they worked.
Unfortunately, the investigators from the state and territory police forces and regulatory agencies are not specialists in the heavy vehicle transport industry and lack the understanding of the heavy vehicle transport socio-technical system. These investigators have a mandate to investigate for the purposes of prosecution, and as a consequence look for the attribution of blame. These agencies do not apply a systemic investigation methodology to determine the underlying causes of a crash. Even the recent enactment of the Heavy Vehicle National Law, which seeks to apportion liability to others throughout the logistics chain, is consistent with this prosecutorial approach.
In contrast, investigations into aviation, rail and maritime incidents are conducted by the Australian Transport Safety Bureau (ATSB), which adopts a “no blame-no liability” investigation methodology, albeit one that is not systemic. These investigations are tailored to each specific domain which seeks to uncover underlying causes without attributing blame. Incident investigations in these transport modalities have facilitated a reduction in rates of serious incidents. Consequently, the adoption of such an approach to heavy vehicle crash investigations should also result in a reduction of serious crashes due to a more comprehensive uncovering and understanding of underlying causative factors.
This research was conducted in three stages. The first stage consisted of a literature review that identified the socio-technical system within which the heavy vehicle transport industry operates, the underlying causes of heavy vehicle crashes identified by academic research, the legislative regimes governing the heavy vehicle transport industry, the actors involved in the heavy vehicle transport system, and what investigation methods are currently being used to conduct heavy vehicle crash investigations. Stage two consisted of two parts: the first part being a survey of heavy vehicle transport industry participants seeking their responses to twenty survey statements, and the second part being semi-structured interviews of investigators who have investigated heavy vehicle crashes. Stage three also consisted of two parts. Part one was a thematic analysis of investigation reports completed by the ATSB of investigations of heavy vehicles crashing with trains at level crossing that occurred between 2000-2019. Part two was a thematic analysis of Coronial report findings of heavy vehicle fatal crashes that occurred in Australia between 2005 and 2020.
This research identified that a number of stakeholders have called for the ATSB to take over investigations of heavy vehicle crashes; however, the ATSB are under resourced to meet their current obligations and may not be best suited to conduct investigations of heavy vehicle fatal crashes. The ATSB have also, in the past, been criticised for not having suitable systemic investigation processes in place.
This research’s original contribution to knowledge is the development of an investigation framework that can be used by investigative agencies to assist with investigations of heavy vehicle crashes. The investigation framework will help direct investigators in their search for answers to identify the underlying causes of a heavy vehicle crash. The framework instructs the investigator to look beyond blame and driver error and motivates the investigator to look at other underlying causes and contributory factors influencing driver behaviour.
This research has obtained evidence to support the need for a dedicated heavy vehicle crash investigation agency which uses a systemic investigation methodology to investigate crashes. Additionally, the research has identified the need for investigators to be trained in the necessary systemic investigation techniques and to gain knowledge and develop skills specific to the heavy vehicle transport industry.
This research has developed an investigation framework that can be used by investigators to conduct investigations of heavy vehicle crashes. This framework is a systemic methodology that when applied will ensure investigators delve deeply to uncover the underlying causes from within the heavy vehicle transport socio-technical system, rather than assigning blame to the driver and ceasing investigations when human error has been identified.
Books on the topic "Heavy vehicle crashes"
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Cofone, Joseph N. Rollover crashes of motor vehicles and heavy trucks. Jacksonville, Fla: Institute of Police Technology and Management, University of North Florida, 2002.
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Armstrong, Christopher, ed. Collision Reconstruction Methodologies Volume 10A: Pedestrian Collisions. SAE International, 2018. http://dx.doi.org/10.4271/9780768095302.
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The last ten years have seen explosive growth in the technology available to the collision analyst, changing the way reconstruction is practiced in fundamental ways. The greatest technological advances for the crash reconstruction community have come in the realms of photogrammetry and digital media analysis. The widespread use of scanning technology has facilitated the implementation of powerful new tools to digitize forensic data, create 3D models and visualize and analyze crash vehicles and environments. The introduction of unmanned aerial systems and standardization of crash data recorders to the crash reconstruction community have enhanced the ability of a crash analyst to visualize and model the components of a crash reconstruction. Because of the technological changes occurring in the industry, many SAE papers have been written to address the validation and use of new tools for collision reconstruction. Collision Reconstruction Methodologies Volumes 1-12 bring together seminal SAE technical papers surrounding advancements in the crash reconstruction field. Topics featured in the series include: • Night Vision Study and Photogrammetry • Vehicle Event Data Recorders • Motorcycle, Heavy Vehicle, Bicycle and Pedestrian Accident Reconstruction The goal is to provide the latest technologies and methodologies being introduced into collision reconstruction - appealing to crash analysts, consultants and safety engineers alike.
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Safety Research: Heavy Vehicles, Information Systems, and Crash Studies and Methods (Transportation Research Record). Transportation Research Board, 1993.
Find full textBook chapters on the topic "Heavy vehicle crashes"
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Kaiser, Susanne, Martin Winkelbauer, Erwin Wannenmacher, Philipp Blass, and Hatun Atasayar. "Road Safety Issues Related to Truck Platooning Deployment." In Energy-Efficient and Semi-automated Truck Platooning, 175–86. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_13.
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AbstractThe benefits of platooning to road safety are oftentimes inferred based on the assumption of positive effects attributed to advanced driver assistance systems (ADAS). However, the potential to significantly reduce car crashes is just one of many aspects to be considered. The Connecting Austria project was committed to examining road safety issues from various perspectives within Austria. The legislative situation in Austria regarding public tests of automated driving systems was reviewed and requirements discussed. Furthermore, an assessment of the readiness of 700 km road infrastructure was assessed by means of an adapted Road Safety Inspection and recent heavy goods vehicle (HGV) accident figures on motor and expressways were discussed. Eventually, the distance at which HGV should operate cooperatively is a road safety issue demanding for consideration of other road users. Car drivers’ subjective tolerance of gap sizes between trucks can serve as an important indicator to answer this question. An on-road study aiming at operationalising the individual gap acceptance is outlined.
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Kaiser, Susanne, Martin Winkelbauer, Erwin Wannenmacher, Philipp Blass, and Hatun Atasayar. "Road Safety Issues Related to Truck Platooning Deployment." In Energy-Efficient and Semi-automated Truck Platooning, 175–86. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_13.
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AbstractThe benefits of platooning to road safety are oftentimes inferred based on the assumption of positive effects attributed to advanced driver assistance systems (ADAS). However, the potential to significantly reduce car crashes is just one of many aspects to be considered. The Connecting Austria project was committed to examining road safety issues from various perspectives within Austria. The legislative situation in Austria regarding public tests of automated driving systems was reviewed and requirements discussed. Furthermore, an assessment of the readiness of 700 km road infrastructure was assessed by means of an adapted Road Safety Inspection and recent heavy goods vehicle (HGV) accident figures on motor and expressways were discussed. Eventually, the distance at which HGV should operate cooperatively is a road safety issue demanding for consideration of other road users. Car drivers’ subjective tolerance of gap sizes between trucks can serve as an important indicator to answer this question. An on-road study aiming at operationalising the individual gap acceptance is outlined.
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Prem, Hans, Luan Mai, Glenn Gorham, Don Hutchinson, and John Long. "Rollover crash analysis of a road tanker with self-steer axles." In International Conference on Heavy Vehicles HVParis 2008, 225–41. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2013. http://dx.doi.org/10.1002/9781118557464.ch18.
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Vishwajit Nandi, Rijita Poddar, Rajesh Saha, and Sahadev Roy. "Low-Cost Crash Protection System for Heavy Motor Vehicles." In Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processing, 353–58. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-2638-3_40.
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"Crash compatibility between heavy goods vehicles and passenger cars." In International Conference on Heavy Vehicles HVParis 2008, 269–80. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2013. http://dx.doi.org/10.1002/9781118557464.ch21.
Full textConference papers on the topic "Heavy vehicle crashes"
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Atahan, Ali O., Abhishek S. Joshi, and Moustafa El-Gindy. "A Rear-End Protection Device for Heavy Vehicles." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42455.
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Rear underride crashes, particularly with heavy vehicles, constitute a serious safety concern for passenger cars. Several solutions to this emerging concern have been proposed by responsible agencies. Recent rear-end crashes with heavy vehicles show that a properly used rear underride guard devices can slow down impacting vehicle in a controlled manner. Moreover, with the use of these devices, the severity of crashes can be reduced and loss of lives can be prevented. In this paper, a special underride guard device is designed for heavy vehicle use. The height of the device from ground and support conditions are varied to evaluate and compare the crash performances. Finite element models of these particular designs are constructed and models are impacted by a passenger car model traveling at two different speeds of 48 km/h and 64 km/h. LS-DYNA, a non-linear finite element code capable of analyzing large deformations is used for the analysis. Vehicle decelerations, energy dissipations and passenger car crush characteristics are compared to determine the acceptability of each design. Based on the simulation study, an optimum height from ground and support condition are determined for acceptable impact performance for heavy vehicle mounted rear -end underride guard devices against passenger vehicle impacts.
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Atahan, Ali O., Guido Bonin, Moustafa El-Gindy, and James Allen. "Development of a Draft Heavy Vehicle Rear Underride Guard Specification." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13330.
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This paper summarizes results of a large research program intended to develop a draft rear underride guard specification for heavy vehicles. Results of a series of laboratory and full-scale crash tests performed at the Transport Canada Research Center were used in the development of these specifications. A total of eleven full-scale crash tests was carried out to evaluate the effectiveness of different underride guards. The first ten of these tests were performed on a simulated trailer attached guard. Four different underride guard designs were used in these ten full-scale crash tests. Three different vehicle models traveling at 48, 56 and 65 km/h speeds were used to impact underride guards head on. Results of the first ten crash tests show that the currently used US FMVSS 223 standard is far from adequate in preventing the occurrance of rear underride. Based on findings obtained from these crash tests, an improved guard design was developed and tested using a 16-meter trailer. This final crash test verified the effectiveness of improved guard design in reducing the undesirable effects of rear underride crashes. Based on the results, a draft heavy vehicle rear underride guard specification was developed.
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Schaudt, William, Darrell Bowman, Walter Wierwille, Richard Hanowski, and Chris Flanigan. "Development of Auditory Warning Signals for Mitigating Heavy Truck Rear-End Crashes." In SAE 2010 Commercial Vehicle Engineering Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2010. http://dx.doi.org/10.4271/2010-01-2019.
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Jawad, Saad A., Hikmat F. Mahmood, and Mohamed R. Baccouche. "Smart Structure for Improving Crashworthiness in Vehicle Frontal Collisions." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-0951.
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Abstract Traditional passive front-end structure is limited by its fixed characteristics. The implication is that it performs well under given crash conditions only. Design compromise is a necessity to cope with both full Frontal and Offset crashes. A trade off between pulse requirements and intrusion injury requirements is also necessary in short front-end design. Energy management in passive structures is thus constrained by the fixed length and stiffness of the structure. Ideally it is required to make the structure longer and stiffer for high speed-high mass crashes, and softer for low speed-low mass crashes. Offset crashes ideally require stiffer structure on the impact side and softer structure on the other side. The way out of this impasse is to introduce the concept “Smart Structures” where the characteristics (length and stiffness) may be intelligently adjusted according to suit the particular crash circumstances. This research is attempting to improve vehicle crashworthiness by introducing a novel system of “Smart Structures” to support the function of the existing passive structure. A ten-degrees of freedom, two-dimensional spring-mass-damper simulation model has been developed to study the dynamics of crash between two vehicles in head-on collisions. The model inputs mass and speed of both colliding vehicles as well as offset overlap ratio of the crash. Masses and stiffness of various parts of the front end are calculated according to the vehicle total mass. The model was shown to be capable of capturing deformation displacement of the front and backup rail separately. For offset crashes the model was shown to capture the rotation of the structure as well as the deformation of the LHS and RHS rails independently. The model assumes that the two colliding structures geometrically interact with each other. Two injury risk criteria have been considered in this study; average dynamic acceleration sustained by the passenger compartment throughout impact (shock injuries), and length of back up deformation (intrusion injuries). The proposed “Smart Structures” consist of two independently controlled hydraulic cylinders integrated with the front-end rails. By applying active control strategy, this structure is characterised by variable crash zone length, variable Stiffness and independent or asymmetric characteristics of the left/right rails in offset crashes. This paper attempts to analyse the performance of “Smart Structures” applying active control to the crash process for the purpose collision mitigation and improvement of compatibility between vehicles of different masses. It is shown that “Smart Structures” employing two hydraulic cylinders, that extend up to 0.35 meter, prior to collision, is capable of absorbing most impact energy at 30mph. The sustained average dynamic acceleration pulse is 15g. The main improvement is in reducing intrusion injuries at high impact speeds and offset crashes. At low impact speed lower acceleration pulse and lower delta V index are obtained. Deployment of “Smart Structures” in heavy vehicles was shown to have considerable improvement in the compatibility of frontal crashes with smaller vehicles. The intrusion injury index was nearly halved upon deploying the “Smart Structures” in a head-on collision with mass ratio of 10.
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Pape, Douglas B., and Jason Holdridge. "The Dynamics of Previously Conducted Full-Scale Heavy Vehicle Rollover Crashes." In International Truck & Bus Meeting & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-3384.
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Hasan, Ahmed Sajid, Md Asif Bin Kabir, and Mohammad Jalayer. "Severity Analysis of Heavy Vehicle Crashes Using Machine Learning Models: A Case Study in New Jersey." In International Conference on Transportation and Development 2021. Reston, VA: American Society of Civil Engineers, 2021. http://dx.doi.org/10.1061/9780784483534.025.
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Schulz, Nathan, Chiara Silvestri Dobrovolny, and Abhinav Mohanakrishnan. "Investigation of Heavy Truck Restraint System Effectiveness Through Finite Element Computer Simulations in Frontal Crashes." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-67356.
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Computer finite element simulations play an important role in reducing the cost and time taken for prediction of a crash scenario. While interior crash protection has received adequate attention for automobiles, very little is known for commercial vehicle such as heavy trucks. The understanding of injury types for heavy trucks occupants in relation to different crash scenarios would help mitigation of the injury severity. Finite element computer models of the heavy truck cabin structure, interior cabin components, anthropomorphic test device (ATD) (also called dummy) and passive restraint systems were developed and assembled to simulate head-on crash of a heavy truck into a rigid barrier. The researchers developed a computer simulation parametric evaluation with respect to specific seat belt restraint system parameters for a speed impact of 56.3 km/h (35 mph). Restraint parameter variations within this research study are seat belt load limiting characteristics, inclusion of seat belt pretensioner, and variation of seat belt D-ring location. Additionally an airbag was included to investigate another restraint system. For each simulated impact characteristic and restraint system variation, the occupant kinematics were observed and occupant risks were assessed. Within the approximations and assumptions included in this study, the results presented in this paper should be considered as preliminary guidance on the effectiveness of the use of seat belt as occupant injury mitigation system.
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Ferrone, Christopher W., and Charles Sinkovits. "Driver Fatigue/Inattention Monitoring Device: An Integrated System for Heavy Trucks." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79033.
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The National Transportation Safety Board has reported statistics which indicate that 31% of all fatal-to-the-truck driver accidents occur due to fatigue/inattention [1] and 58% of all single-vehicle large truck crashes were also fatigue related [2]. If these numbers can be reduced, many lives can be saved. A Driver Fatigue Monitoring System has been designed and built to monitor whether a driver is sleeping or inattentive. This integrated system monitors the steering input behavior of the driver during a specified period of time. If the number of steering inputs is below the expected predetermined threshold, the system activates an audible alarm and light in the cab, waking the driver. Furthermore, this system can deactivate cruise control as well as activate various other preprogrammed truck systems or components to further aid in the control of the truck and to alert nearby motorists.
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Alvick, Mark, Norm Ritchie, Daniel Schmit, Bruce Koepke, Michal Wozniak, James Chinni, Michael Roelleke, and Elvira Diehl. "Heavy Truck Frontal Crash Protection System Development." In SAE 2007 Commercial Vehicle Engineering Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2007. http://dx.doi.org/10.4271/2007-01-4289.
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Wang, Anbo, Yanwen Liu, Xiaofang Liu, Steven W. Kirkpatrick, Virginia Phan, and Robert T. Bocchieri. "Crash Energy Management Design for the LACMTA HR4000 Heavy Rail Vehicle." In 2020 Joint Rail Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/jrc2020-8043.
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Abstract The LACMTA HR4000 heavy rail vehicle was designed to meet the ASME RT-2 Safety Standard for Structural Requirements for Heavy Rail Transit Vehicles. The crash energy management (CEM) structures designed for this vehicle also provide unique performance characteristics through use of a staged combination of CEM technologies. The resulting design, using easily replaceable components, provides reduced repair costs for lower speed collisions, minimizes the number of cars damaged during a collision, while exceeding the RT-2 standard for safety to the operator. None of the CEM technologies used are novel, but their integrated design provides a unique performance in heavy rail vehicle design. This paper provides an overview of the CEM design development. First, a general description of the CEM system function is provided, including the various CEM technologies used and how they interact during a collision. Then the 1-dimensional and 3-dimensional nonlinear dynamic models developed for optimizing the design are discussed. The CEM test program performed to demonstrate the system function and validate the modeling is described. Finally, the performance of the CEM system in train-to-train collision analyses is presented. Underframe testing was conducted for validation of the simulations.