Tractor-trailer crashes in Indiana: a case-control study of the role of truck configuration

Commercial truck crash injury severity analysis using gradient boosting data mining model

INTRODUCTION

Truck crashes contribute to a large number of injuries and fatalities. This study seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 North Dakota and Colorado crash data provided by the Federal Motor Carrier Safety Administration.

METHOD

To fulfill a gap of previous studies, broad considerations of company and driver characteristics, such as company size and driver's license class, along with vehicle types and crash characteristics are researched. Gradient boosting, a data mining technique, is applied to comprehensively analyze the relationship between crash severities and a set of heterogeneous risk factors.

RESULTS

Twenty five variables were tested and 22 of them are identified as significant variables contributing to injury severities, however, top 11 variables account for more than 80% of injury forecasting. The relative variable importance analysis is conducted and furthermore marginal effects of all contributing factors are also illustrated in this research. Several factors such as trucking company attributes (e.g., company size), safety inspection values, trucking company commerce status (e.g., interstate or intrastate), time of day, driver's age, first harmful events, and registration condition are found to be significantly associated with crash injury severity. Even though most of the identified contributing factors are significant for all four levels of crash severity, their relative importance and marginal effect are all different.

CONCLUSIONS

For the first time, trucking company and driver characteristics are proved to have significant impact on truck crash injury severity. Some of the results in this study reinforce previous studies' conclusions.

PRACTICAL APPLICATIONS

Findings in this study can be helpful for transportation agencies to reduce injury severity, and develop efficient strategies to improve safety.

Livestock transport from the perspective of the pre-slaughter logistic chain: a review

New developments in livestock transport within the pre-slaughter chain are discussed in terms of three logistic nodes: origin, stopovers and slaughterhouse. Factors as transport cost, haulier, truck specifications, micro-environment conditions, loading density, route planning, vehicle accidents and journey length are discussed as well as causes of morbidity, mortality, live weight and carcass damage. Taking into account current trends towards increased transport times, logistics stopovers and mixed transport, there is a need to develop systems of evaluation and decision-making that provide tools and protocols that can minimize the biological cost to animals, which may have been underestimated in the past.

Multi-scale traffic safety and operational performance study of large trucks on mountainous interstate highway

In addition to multi-vehicle accidents, large trucks are also prone to single-vehicle accidents on the mountainous interstate highways due to the complex terrain and fast-changing weather. By integrating both historical data analysis and simulations, a multi-scale approach is developed to evaluate the traffic safety and operational performance of large trucks on mountainous interstate highways in both scales of individual vehicle as well as traffic on the whole highway. A typical mountainous highway in Colorado is studied for demonstration purposes. Firstly, the ten-year historical accident records are analyzed to identify the accident-vulnerable-locations (AVLs) and site-specific critical adverse driving conditions. Secondly, simulation-based single-vehicle assessment is performed for different driving conditions at those AVLs along the whole corridor. Finally, the cellular-automaton (CA)-based simulation is carried out to evaluate the multi-vehicle traffic safety as well as the operational performance of the traffic by considering the actual speed limits, including the differential speed limits (DSL) at some locations. It is found that the multi-scale approach can provide insightful and comprehensive observations of the highway performance, which is especially important for mountainous highways.

Age-related safety in professional heavy vehicle drivers: a literature review

With Australia facing a looming shortage of heavy vehicle drivers the question is raised as to whether it is desirable or prudent to encourage older professional heavy vehicle drivers to remain in the transport sector for longer, particularly those of heavy vehicles or recruit drivers of a younger age.

AIM

To review age-related safety and identify other factors that contribute to accidents experienced by heavy vehicle drivers.

METHODS

A search was conducted of national and international peer-reviewed literature in the following databases: MedLine, Embase, Cinahl, PsychInfo and the Canadian Centre for Occupational Health & Safety. A manual search was performed to obtain relevant articles within selected journals.

RESULTS

A limited number of studies reported age-specific accident rates for heavy vehicles for the spectrum of driver age that included drivers younger than 27 years and those over 60 years of age. Heavy vehicle drivers younger than 27 years of age demonstrated higher rates of accident/fatality involvement which decline and plateau until the age of 63 years where increased rates were again observed. Other contributing factors to heavy vehicle accidents include: long hours and subsequent sleepiness and fatigue, employer safety culture, vehicle configuration particularly multiple trailers, urbanisation and road classification.

CONCLUSIONS

Drivers of heavy vehicles are over-involved until age 27 years however a characteristic 'U' shaped curve indicates a higher risk of accident involvement for both younger and older drivers. More detailed analyses of "at-fault" involvement and inability to avert an accident and other factors that contribute to accidents across the ages of heavy vehicle drivers may give further clarification to the degree of safety of both younger and older commercial heavy vehicle drivers.

Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents

The impact that large trucks have on accident severity has long been a concern in the accident analysis literature. One important measure of accident severity is the most severely injured occupant in the vehicle. Such data are routinely collected in state accident data files in the U.S. Among the many risk factors that determine the most severe level of injury sustained by vehicle occupants, the number of occupants in the vehicle is an important factor. These effects can be significant because vehicles with higher occupancies have an increased likelihood of having someone seriously injured. This paper studies the occupancy/injury severity relationship using Washington State accident data. The effects of large trucks, which are shown to have a significant impact on the most severely injured vehicle occupant, are accounted for by separately estimating nested logit models for truck-involved accidents and for non-truck-involved accidents. The estimation results uncover important relationships between various risk factors and occupant injury. In addition, by comparing the accident characteristics between truck-involved accidents and non-truck-involved accidents, the risk factors unique to large trucks are identified along with the relative importance of such factors. The findings of this study demonstrate that nested logit modeling, which is able to take into account vehicle occupancy effects and identify a broad range of factors that influence occupant injury, is a promising methodological approach.