Analysis of Haul Truck- Related Fatalities and Injuries in Surface Coal Mining in West Virginia

Trucks are the primary means of haulage in surface coal, metal, and nonmetal mining operations. The number of fatal accidents involving trucks is higher when compared to all other mining equipment. The Mine Safety and Health Administration (MSHA) reports that 137 fatalities were haul truck- related in the United States between 1995 and 2011. A total of 12 truck-related accidents, including 13 fatalities, were recorded in surface coal mining operations in West Virginia (WV) during this period. The objectives of this research were to (i) analyze the root causes of these accidents, and (ii) develop effective intervention strategies to eliminate these fatalities. The Fault Tree Analysis (FTA) technique was used to systematically analyze truck related fatalities. Data on truck-related injury accidents in West Virginia surface coal mines during 2012 and 2013 were also analyzed in this study. Results of the study indicate that inadequate or improper pre-operational check and poor maintenance of trucks were the two most common root causes of these accidents. A total of eight accidents occurred on haul roads, while 10 accidents occurred while the trucks were moving forward. The two most violated provisions of Code of Federal Regulations were 30 CFR§77.404 - Machinery and equipment; operation and maintenance (six times), and 30 CFR§77.1606 - Loading and haulage equipment; inspection and maintenance (five times).;A total of 223 reported injuries were recorded at West Virginia surface coal mines. With the exception of two missing data, a total of 178 accidents were equipment-related and 43 accidents occurred without equipment being involved. The equipment categories accounting for the most number of injuries were: truck (57 times) and bulldozer/dozer/crawler tractor (43 times). The majority of the truck-related injuries occurred within the worker\u27s first five years at the mine and within the first five years at their current job title. Workers between ages 25 and 39 had the greatest percentage of injuries. Most injuries were recorded during Section I (6:00 a.m. - 2:00 p.m.), and the fall season has the greatest number of truck-related injuries of all four seasons. Regarding the nature of injury, sprains and strains made up about 32%, topping all other types of injuries. The most commonly injured body part in truck-related injuries was the Multiple parts. .;A two-pronged approach to accident prevention was used: one that is fundamental and traditional (safety regulations, training and education, and engineering of the work environment); and one that is innovative and creative (e.g., applying technological advances to better control and eliminate the root causes of accidents). Suggestions for improving current training and education system were proposed, and recommendations were provided on improving the safety of mine working conditions, specifically safety conditions on haul roads, dump sites, and loading areas. Currently available technologies that can help prevent haul truck-related fatal accidents were also discussed. The results of this research may be used by mine personnel to help create safer working conditions and decrease truck-related fatalities and injuries in surface coal mining

Designing Auditory Warning Signals to Improve the Safety of Commercial Vehicles

Based on four studies, this thesis aims to explore how to design auditory warning signals that can facilitate safer driving by operators of heavy goods vehicles. The first three studies focus on the relationships between certain characteristics of auditory warnings and various indicators of traffic safety. A deeper understanding of these relationships would allow system developers to design auditory signals that are better optimised for safety. The fourth study examines the opinions of both vehicle developers and professional drivers regarding warning attributes. One major conclusion is that meaningful warning sounds that are related to the critical event can improve safety. As compared with arbitrarily mapped sounds, meaningful sounds are easier to learn, can improve drivers’ situation awareness, and generate less interference and less annoyance. The present thesis also supports the view that commercial drivers’ initial acceptance of these sounds may be very high. Annoyance is an especially important aspect of warning design to consider; it can negatively influence driving performance and may lead drivers to turn off their warning systems. This research supports the notion that drivers do not consider that negative experience is an appropriate attribute of auditory warnings designed to increase their situation awareness. Also, commercial drivers seem to report, significantly more than vehicle developers, that having less-annoying auditory warnings is important in high-urgency driving situations. Furthermore, the studies presented in this thesis indicate that annoyance cannot be predicted based on the physical properties of the warning alone. Learned meaning, appropriateness of the mapping between a warning and a critical event, and individual differences between drivers may also significantly influence levels of annoyance. Arousal has been identified as an important component of driver reactions to auditory warnings. However, high levels of arousal can lead to a narrowing of attention, which would be suboptimal for critical situations during which drivers need to focus on several ongoing traffic events. The present work supports the notion that high-urgency warnings can influence commercial drivers’ responses to unexpected peripheral events (i.e., those that are unrelated to the warning) in terms of response force, but not necessarily in terms of response time. The types of auditory warnings that will be developed for future vehicles depend not only on advances in research, but also on the opinions of developers and drivers. The present research shows that both vehicle developers and drivers are aware of several of the potentially important characteristics of auditory warnings. For example, they both recognise that warnings should be easy to understand. However, they do disagree regarding certain attributes of warnings, and, furthermore, developers may tend to employ a “better safe than sorry” strategy (by neglecting factors concerning annoyance and the elicitation of severe startled responses) when designing high-urgency warnings. Developers’ recognition of the potentially important attributes of auditory warnings should positively influence the future development of in-vehicle systems. However, considering the current state of research regarding in-vehicle warnings, it remains challenging to predict the most suitable sounds for specific warning functions. One recommendation is to develop a design process that examines the appropriateness of in-vehicle auditory warnings. This thesis suggests an initial version of such a process, which in this case was produced in collaboration with system designers working in the automotive industry

Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones

This research project used the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study(NDS) to improve highway safety by using statistical descriptions of normal driving behavior to identify abnormal driving behaviors in work zones. SHRP2 data used in these analyses included 50 safety-critical events (SCEs) from work zones and 444 baseline events selected on a matched case-control design.Principal components analysis (PCA) was used to summarize kinematic data into “normal” and “abnormal”driving. Each second of driving is described by one point in three-dimensional principal component (PC) space;an ellipse containing the bulk of baseline points is considered “normal” driving. Driving segments without-of-ellipse points have a higher probability of being an SCE. Matched case-control analysis indicates that thespecific individual and traffic flow made approximately equal contributions to predicting out-of-ellipse driving.Structural Topics Modeling (STM) was used to analyze complex categorical data obtained from annotated videos.The STM method finds “words” representing categorical data variables that occur together in many events and describes these associations as “topics.” STM then associates topics with either baselines or SCEs. The STM produced 10 topics: 3 associated with SCEs, 5 associated with baselines, and 2 that were neutral. Distractionoccurs in both baselines and SCEs.Both approaches identify the role of individual drivers in producing situations where SCEs might arise. A countermeasure could use the PC calculation to indicate impending issues or specific drivers who may havehigher crash risk, but not to employ significant interventions such as automatically braking a vehicle without-of-ellipse driving patterns. STM results suggest communication to drivers or placing compliant vehicles in thetraffic stream would be effective. Finally, driver distraction in work zones should be discouraged

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

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

Importance of Proactive Safety Analysis for Corridor Planning

A proactive safety analysis approach assists decision makers in addressing high-risk crash elements, particularly on low-volume roadways. Using corridor planning best practices and lessons learned, this presentation will explore creative and proactive approaches for holistic planning solutions. It will also validate 2020 pandemic crash data accuracy and highlight prioritization methodologies and AASHTO and FHWA guided countermeasures applied to at-risk locations

EFFECT OF SHORT-STORAGE HRGCs ON DRIVER DECISION BEHAVIOR AND SAFETY CONCERNS: REAL-WORLD ANALYSIS AND EXPERIMENTAL EVIDENCE

Vehicle-train collisions at highway-rail grade crossings (HRGCs) continue to be a safety concern, and despite improvements in warnings, many of these incidents are attributed to human error. In some cases, distractions other than railroad traffic, such as HRGCs with limited space between the railroad tracks and the highway intersection, may create additional cognitive burdens for drivers. We investigated the effect of HRGC type (short-storage vs. non-short storage) on driver attention and decision-making in two studies. In Study 1, we systematically analyzed 996 incidents from 2017-2019 from the Federal Railroad Administration’s Safety database. Driver decision making and outcomes were different depending on HRGC type, with more train strikes in short storage incidents, as opposed to vehicle strikes. Study 2 was a controlled lab experiment in which drivers identified safety concerns in driving images. Drivers reported more safety concerns, and rated them more important in images of short-storage HRGCs than non-short storage HRGCs. This pattern did not depend on their rural or urban driving experience. Eye-tracking analysis found some differences in search behavior depending on the type of HRGC. This research contributes to a new area of research in rail safety, as studies comparing the two types of HRGCs have previously not been done. Interventions for non-short-storage HRGCs may not apply to short-storage HRGCs if it is found that drivers approach them differently

AN INVESTIGATION OF MOTOR VEHICLE DRIVER INATTENTION AND ITS EFFECTS AT HIGHWAY-RAIL GRADE CROSSINGS

The relationship between accident injury severity and drivers’ inattentive behavior requires an in-depth investigation – this is especially needed in the case of motor vehicle drivers at highway-rail grade crossings (HRGCs). The relationship between drivers’ personality/ socioeconomic characteristics and inattentive behavior at HRGCs is another topic requiring research. Past educational programs about safe driving at HRGCs have often not been designed to target people who may be in urgent need of such information, which may limit the effectiveness of those programs. This dissertation thus focuses on the following four objectives: to investigate the association between motor vehicle inattentive driving and the severity of drivers’ injuries sustained in crashes reported at or near HRGCs; to investigate the association between drivers’ self-reported inattentive driving experience and a series of factors such as drivers’ knowledge of safe driving, attitudes towards safe driving, etc.; to identify driver groups that have lower or higher levels of knowledge of correct rail crossing negotiation; and to investigate the direct and indirect effects between drivers’ characteristics and their knowledge level as well as their involvement with inattentive driving behavior at HRGCs. The research obtained 12 years of police-reported crash data from the Nebraska Department of Roads and collected data in a statewide random-sample mail questionnaire survey. Statistical analysis methods, including random parameters binary logit model, confirmatory factor analysis, robust linear regression, multinomial logit model, and structural equation models were utilized in this research. Conclusions are that inattentive driving plays a significant role in contributing to more severe injuries in accidents reported in proximity of HRGCs in Nebraska; Nebraska motor vehicle drivers’ personality traits, knowledge levels of negotiating HRGCs and driving experience are associated with inattentive driving; drivers with lower levels of knowledge of correct HRGC negotiation are: drivers who drive vehicles other than passenger cars, have received less safety information, have a shorter driving history, are older, have lower household income, and have higher intent to violate rules at rail crossings; inattentive driving behavior at HRGCs is directly and indirectly affected by their personality traits while drivers’ knowledge of correct HRGC negotiation appears to only have an indirect effect. Advisor: Aemal J.Khatta