Exploring factors contributing to injury severity at freeway merging and diverging locations in Ohio

Identifying factors that affect crash injury severity and understanding how these factors affect injury severity is critical in planning and implementing highway safety improvement programs. Factors such as driver-related, traffic-related, environment-related and geometric design-related were considered when developing statistical models to predict the effects of these factors on the severity of injuries sustained from motor vehicle crashes at merging and diverging locations. Police-reported crash data at selected freeway merging and diverging areas in the state of Ohio were used for the development of the models. A generalized ordinal logit model also known as partial proportional odds model was applied to identify significant factors increasing the likelihood of one of the five KABCO scale of injury severity: no injuries, possible/invisible injuries, non-incapacitating injuries, incapacitating injuries, or fatal injuries. The results of this study show that semi-truck related crashes, higher number of lanes on freeways, higher number of lanes on ramps, speeding related crashes, and alcohol related crashes tend to increase the likelihood of sustaining severe injuries at freeway merging locations. In addition, females and older persons are more likely to sustain severe injuries especially at freeway merge locations. Alcohol related crashes, speeding related crashes, angle-type collisions, and lane-ramp configuration type D significantly increase the likelihood of severe injury crashes at diverging areas. Poor lighting condition tends to increase non-incapacitating injuries at diverging areas only. Moreover, adverse weather condition increases the likelihood of no-injury and fatal injuries at merging areas only and adverse road conditions tend to increase a range of injury severity levels from possible/invisible injuries to incapacitating injuries at merging areas only.     

Long-term analysis of the impact of longitudinal barriers on motorway safety

The objective of this study was to assess the influence of longitudinal barriers located on the median strips and hard shoulders of toll motorways on crash severity in vehicles running off the roadway. The study was based on crashes involving injury and property damage only, recorded from 1996 to 2010 on a French toll motorway network of about 2000 km.     

Factors influencing injury severity of motor vehicle-crossing pedestrian crashes in rural Connecticut

The ordered probit model was used to evaluate the effect of roadway and area type features on injury severity of pedestrian crashes in rural Connecticut. Injury severity was coded on the KABCO scale and crashes were limited to those in which the pedestrians were attempting to cross two-lane highways that were controlled by neither stop signs nor traffic signals. Variables that significantly influenced pedestrian injury severity were clear roadway width (the distance across the road including lane widths and shoulders, but excluding the area occupied by on-street parking), vehicle type, driver alcohol involvement, pedestrian age 65 years or older, and pedestrian alcohol involvement. Seven area types were identified: downtown, compact residential, village, downtown fringe, medium-density commercial, low-density commercial, and low-density residential. Two groups of these area types were found to experience significantly different injury severities. Downtown, compact residential, and medium- and low-density commercial areas generally experienced lower pedestrian injury severity than village, downtown fringe, and low-density residential areas.     

A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods

Numerous efforts have been devoted to investigating crash occurrence as related to roadway design features, environmental factors and traffic conditions. However, most of the research has relied on univariate count models; that is, traffic crash counts at different levels of severity are estimated separately, which may neglect shared information in unobserved error terms, reduce efficiency in parameter estimates, and lead to potential biases in sample databases. This paper offers a multivariate Poisson-lognormal (MVPLN) specification that simultaneously models crash counts by injury severity. The MVPLN specification allows for a more general correlation structure as well as overdispersion. This approach addresses several questions that are difficult to answer when estimating crash counts separately. Thanks to recent advances in crash modeling and Bayesian statistics, parameter estimation is done within the Bayesian paradigm, using a Gibbs Sampler and the Metropolis–Hastings (M–H) algorithms for crashes on Washington State rural two-lane highways. Estimation results from the MVPLN approach show statistically significant correlations between crash counts at different levels of injury severity. The non-zero diagonal elements suggest overdispersion in crash counts at all levels of severity. The results lend themselves to several recommendations for highway safety treatments and design policies. For example, wide lanes and shoulders are key for reducing crash frequencies, as are longer vertical curves.     

The rising burden of serious thoracic trauma sustained by motorcyclists in road traffic crashes

In many countries increased on-road motorcycling participation has contributed to increased motorcyclist morbidity and mortality over recent decades. Improved helmet technologies and increased helmet wearing rates have contributed to reductions in serious head injuries, to the point where in many regions thoracic injury is now the most frequently occurring serious injury. However, few advances have been made in reducing the severity of motorcyclist thoracic injury. The aim of the present study is to provide needed information regarding serious motorcyclist thoracic trauma, to assist motorcycling groups, road safety advocates and road authorities develop and prioritise counter-measures and ultimately reduce the rising trauma burden. For this purpose, a data collection of linked police-reported and hospital data was established, and considerable attention was given to establishing a weighting procedure to estimate hospital cases not reported to police and fatal cases not admitted to hospital. The resulting data collection of an estimated 19,979 hospitalised motorcyclists is used to provide detailed information on the nature, incidence and risk factors for thoracic trauma. Over the last decade the incidence of motorcyclist serious thoracic injury has more than doubled in the population considered, and by 2011 while motorcycles comprised 3.2% of the registered vehicle fleet, one quarter of road traffic-related serious thoracic trauma cases treated in hospitals were motorcyclists. Motor-vehicle collisions, fixed object collisions and non-collision crashes were fairly evenly represented amongst these cases, while older motorcyclists were over-represented. Several prevention strategies are identified and discussed.     

Head injuries in lateral impact collisions

Individual non-minor injuries (Abbreviated Injury Scale (AIS) ≥ 2) to the head that occurred to belted and unbelted drivers and front seat passengers on the struck side of impacted vehicles were examined. Injury type, injury combination, collision severity in relation to type of injury as well as contact sources were assessed. Forty-eight percent of injuries were moderate in severity (AIS 2). The most common type of injury was the diffuse brain injury, typically marked by a short period of unconsciousness, which occurred in collisions of lower severity than focal brain and skull fracture injuries. One-hundred and five out of 216 (48.6%) of contact sources for all injury types originated from outside the vehicle and such exterior sources were more likely to result in high severity injuries. Thirty percent of injuries resulted from head contacts with other vehicles. The most frequent vehicle interior contact source was the side window glass. Diffuse injuries tended to occur independently of other injury types and were more likely to originate from an interior rather than exterior contact. Preventative measures for head injury reduction in lateral collisions are discussed. Overall, the data show that proposed and present European and U.S. lateral impact test methods do not address many head injury problems such as those included in this study.     

Examining driver injury severity in two vehicle crashes – A copula based approach

A most commonly identified exogenous factor that significantly affects traffic crash injury severity sustained is the collision type variable. Most studies consider collision type only as an explanatory variable in modeling injury. However, it is possible that each collision type has a fundamentally distinct effect on injury severity sustained in the crash. In this paper, we examine the hypothesis that collision type fundamentally alters the injury severity pattern under consideration. Toward this end, we propose a joint modeling framework to study collision type and injury severity sustained as two dimensions of the severity process. We employ a copula based joint framework that ties the collision type (represented as a multinomial logit model) and injury severity (represented as an ordered logit model) through a closed form flexible dependency structure to study the injury severity process. The proposed approach also accommodates the potential heterogeneity (across drivers) in the dependency structure. Further, the study incorporates collision type as a vehicle-level, as opposed to a crash-level variable as hitherto assumed in earlier research, while also examining the impact of a comprehensive set of exogenous factors on driver injury severity. The proposed modeling system is estimated using collision data from the province of Victoria, Australia for the years 2006 through 2010.     

Effects of work zone presence on injury and non-injury crashes.

Work zones in the United States have approximately 700 traffic-related fatalities, 24,000 injury crashes, and 52,000 non-injury crashes every year. Due to future highway reconstruction needs, work zones are likely to increase in number, duration, and length. This study focuses on analyzing the effect of work zone duration mainly due to its policy-sensitivity. To do so, we created a unique dataset of California freeway work zones that included crash data (crash frequency and injury severity), road inventory data (average daily traffic (ADT) and urban/rural character), and work zone related data (duration, length, and location). Then, we investigated crash rates and crash frequencies in the pre-work zone and during-work zone periods. For the freeway work zones investigated in this study, the total crash rate in the during-work zone period was 21.5% higher (0.79 crashes per million vehicle kilometer (MVKM)) than the pre-work zone period (0.65 crashes per MVKM). Compared with the pre-work zone period, the increase in non-injury and injury crash rates in the during-work zone period was 23.8% and 17.3%, respectively. Next, crash frequencies were investigated using negative binomial models, which showed that frequencies increased with increasing work zone duration, length, and average daily traffic. The important finding is that after controlling for various factors, longer work zone duration significantly increases both injury and non-injury crash frequencies. The implications of the study findings are discussed in the paper.     

Traffic accidents involving fatigue driving and their extent of casualties

The rapid progress of motorization has increased the number of traffic-related casualties. Although fatigue driving is a major cause of traffic accidents, the public remains not rather aware of its potential harmfulness. Fatigue driving has been termed as a “silent killer.” Thus, a thorough study of traffic accidents and the risk factors associated with fatigue-related casualties is of utmost importance. In this study, we analyze traffic accident data for the period 2006–2010 in Guangdong Province, China. The study data were extracted from the traffic accident database of China's Public Security Department. A logistic regression model is used to assess the effect of driver characteristics, type of vehicles, road conditions, and environmental factors on fatigue-related traffic accident occurrence and severity. On the one hand, male drivers, trucks, driving during midnight to dawn, and morning rush hours are identified as risk factors of fatigue-related crashes but do not necessarily result in severe casualties. Driving at night without street-lights contributes to fatigue-related crashes and severe casualties. On the other hand, while factors such as less experienced drivers, unsafe vehicle status, slippery roads, driving at night with street-lights, and weekends do not have significant effect on fatigue-related crashes, yet accidents associated with these factors are likely to have severe casualties. The empirical results of the present study have important policy implications on the reduction of fatigue-related crashes as well as their severity.     

Off-highway vehicle parks: Combining environment,knowledge, and enforcement for all-terrain vehicle injury prevention

The number of off-highway vehicle (OHV) parks continues to grow to meet the recreational needs of ATV enthusiasts and the increasing popularity of the vehicle. Little is known about how OHV park regulations and enforcement affect ATV safety among their users. This study was designed to determine whether there were differences in crash mechanisms and/or compliance with ATV safety laws and regulations when comparing off-road ATV crashes inside and outside state OHV parks. Relative to outside the parks, a smaller percentage of park victims were under the age of sixteen, a lower percentage were passengers, and a dramatically higher percentage were helmeted. Mean injury severity scores were not different inside and outside the parks, but 5% of outside victims had severe brain injuries, as compared to no park victims. Overall, park victims exhibited better compliance with ATV safety laws and regulations and suffered less severe brain injury outcomes. However, park crashes involved more jump-related injuries, suggesting that additional approaches are needed to improve park safety. These findings support the hypothesis that riding environments with safety regulations and effective enforcement can promote safe behaviors and may prevent injuries.