Injury risks for on-road farm equipment and horse and buggy crashes in Pennsylvania: 2010–2013

Objective: The purpose of this study was to investigate characteristics associated with farm equipment and horse and buggy roadway crashes in relation to person, incident, and injury characteristics to identify appropriate points for injury incident prevention.

Methods: Information on crashes occurring on public roads during the years 2010–2013 was obtained from the Pennsylvania Department of Transportation (PennDOT) and analyzed.

Results: There were 344 farm equipment and 246 horse and buggy crashes during the 4-year study period. These crashes involved 666 and 504 vehicles and 780 and 838 people, respectively. In incidents with farm equipment, the non-farm equipment drivers had an almost 2 times greater injury risk than farm equipment operators. Horse and buggy crashes were almost 3 times more injurious to the horse and buggy drivers than the drivers of the other vehicles.

Conclusions: The average crash rate for farm equipment was 198.4 crashes per 100,000 farm population and for horse and buggy the crash rate was calculated as 89.4 crashes per 100,000 Amish population per year. This study suggests that road safety and public health programs should focus not only on farm equipment operators and horse and buggy drivers but on other motorists sharing the roadway with them.     

Analysis of risk factors affecting driver injury and crash injury with drivers under the influence of alcohol (DUI) and non-DUI

Objective: The objective of this research was to study risk factors that significantly influence the severity of crashes for drivers both under and not under the influence of alcohol.

Methods: Ordinal logistic regression was applied to analyze a crash data set involving drivers under and not under the influence of alcohol in China from January 2011 to December 2014.

Results: Four risk factors were found to be significantly associated with the severity of driver injury, including crash partner and intersection type. Age group was found to be significantly associated with the severity of crashes involving drivers under the influence of alcohol. Crash partner, intersection type, lighting conditions, gender, and time of day were found to be significantly associated with severe driver injuries, the last of which was also significantly associated with severe crashes involving drivers not under the influence of alcohol.

Conclusions: This study found that pedestrian involvement decreases the odds of severe driver injury when a driver is under the influence of alcohol, with a relative risk of 0.05 compared to the vehicle-to-vehicle group. The odds of severe driver injury at T-intersections were higher than those for traveling along straight roads. Age was shown to be an important factor, with drivers 50–60 years of age having higher odds of being involved in severe crashes compared to 20- to 30-year-olds when the driver was under the influence of alcohol.

When the driver was not under the influence of alcohol, drivers suffered more severe injuries between midnight and early morning compared to early nighttime. The vehicle-to-motorcycle and vehicle-to-pedestrian groups experienced less severe driver injuries, and vehicle collisions with fixed objects exhibited higher odds of severe driver injury than did vehicle-to-vehicle impacts. The odds of severe driver injury at cross intersections were 0.29 compared to travel along straight roads. The odds of severe driver injury when street lighting was not available at night were 3.20 compared to daylight. The study indicated that female drivers are more likely to experience severe injury than male drivers when not under the influence of alcohol. Crashes between midnight and early morning exhibited higher odds of severe injury compared to those occurring at other times of day.

The identification of risk factors and a discussion on the odds ratio between levels of the impact of the driver injury and crash severity may benefit road safety stakeholders when developing initiatives to reduce the severity of crashes.     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes

Objective: It is well known that alcohol and drugs influence driving behavior by affecting the central nervous system, awareness, vision, and perception/reaction times, but the resulting effect on driver injuries in car crashes is not fully understood. The purpose of this study was to identify factors affecting the injury severities of unimpaired, alcohol-impaired, and drug-impaired drivers.

Method: The current article applies a random parameters logit model to study the differences in injury severities among unimpaired, alcohol-impaired, and drug-impaired drivers. Using data from single-vehicle crashes in Cook County, Illinois, over a 9-year period from January 1, 2004, to December 31, 2012, separate models for unimpaired, alcohol-impaired, and drug-impaired drivers were estimated. A wide range of variables potentially affecting driver injury severity was considered, including roadway and environmental conditions, driver attributes, time and location of the crash, and crash-specific factors.

Results: The estimation results show significant differences in the determinants of driver injury severities across groups of unimpaired, alcohol-impaired, and drug-impaired drivers. The findings also show that unimpaired drivers are understandably more responsive to variations in lighting, adverse weather, and road conditions, but these drivers also tend to have much more heterogeneity in their behavioral responses to these conditions, relative to impaired drivers. In addition, age and gender were found to be important determinants of injury severity, but the effects varied significantly across all drivers, particularly among alcohol-impaired drivers.

Conclusions: The model estimation results show that statistically significant differences exist in driver injury severities among the unimpaired, alcohol-impaired, and drug-impaired driver groups considered. Specifically, we find that unimpaired drivers tend to have more heterogeneity in their injury outcomes in the presence potentially adverse weather and road surface conditions. This makes sense because one would expect unimpaired drivers to apply their full knowledge/judgment range to deal with these conditions, and the variability of this range across the driver population (with different driving experiences, etc.) should be great. In contrast, we find, for the most part, that alcohol-impaired and drug-impaired drivers have far less heterogeneity in the factors that affect injury severity, suggesting an equalizing effect resulting from the decision-impairing substance.     

Understanding the context of alcohol impaired driving for fatal crash–involved drivers: A descriptive case analysis

Objective: The objective of this study was to understand the social context and circumstances surrounding alcohol-impaired driving prior to fatal crash involvement for drivers with an illegal blood alcohol concentration (BAC ≥ 0.05 g/100 ml or 0.00 g/100 ml for restricted license holders).

Methods: Coroners' case reports investigating fatal crashes in South Australia over a 3-year period (2008–2010) were examined. The personal and crash characteristics of drivers with an illegal BAC were compared with those who had a legal BAC. For each driver with an illegal BAC, information was recorded including characteristics of last trip, location and social context of alcohol consumption, quantity and type of alcohol consumed, BAC level, presence of drugs, perceived alcohol intoxication, and alcohol dependence. Official traffic offense records were also obtained.

Results: Of the 284 fatal crashes included in the study, 34% (n = 95) involved a driver or rider with an illegal BAC. Prior to the crash, alcohol was most frequently consumed by drivers in rural areas, within private homes, and was part of normal social activities. Drivers recorded a high level of alcohol impairment, with a mean BAC of 0.173 g/100 ml and a level of alcohol dependence that was above the Australian national average (7.4 vs. 3.9%). In addition, 23% of drivers were known to be experiencing psychological stress at the time of the crash. The results also confirm that drink driving recidivism continues to be a significant problem, with 44% of drivers recording at least one prior alcohol driving offense.

Conclusions: Alcohol-impaired driving continues to be a leading cause of fatal crashes. The popularity of drinking at home, particularly in rural areas, has implications for police enforcement strategies and suggests that drink driving interventions that focus on community values and looking after friends might be beneficial. Importantly, the study highlights the need for a broader holistic approach to reduce the high levels of alcohol consumption and alcohol dependence underlying drink driving behavior.     

Road traffic crashes among farm vehicle drivers in southern China: A cross-sectional survey

Objective: The objective of this study was to identify the prevalence and potential risk factors of farm vehicle–related road traffic crashes among farm vehicle drivers in southern China.

Methods: A cross-sectional study was used to interview 1,422 farm vehicle drivers in southern China. Farm vehicle–related road traffic crashes that occurred from December 2013 to November 2014 were investigated. Data on farm vehicle–related road traffic crashes and related factors were collected by face-to-face interviews.

Results: The prevalence of farm vehicle–related road traffic crashes among the investigated drivers was 7.2%. Farm vehicle–related road traffic crashes were significantly associated with self-reported vision problem (adjusted odds ratio [AOR] = 6.48, 95% confidence interval [CI], 3.86–10.87), self-reported sleep disorders (AOR = 10.03, 95% CI, 6.28–15.99), self-reported stress (AOR = 20.47, 95% CI, 9.96–42.08), reported history of crashes (AOR = 5.40, 95% CI, 3.47–8.42), reported history of drunk driving (AOR = 5.07, 95% CI, 2.97–8.65), and reported history of fatigued driving (AOR = 5.72, 95% CI, 3.73–8.78). The number of road traffic crashes was highest in the daytime and during harvest season. In over 96% of farm vehicle–related road traffic crashes, drivers were believed to be responsible for the crash. Major crash-causing factors included improper driving, careless driving, violating of traffic signals or signs, and being in the wrong lane.

Conclusion: Findings of this study suggest that farm vehicle–related road traffic crashes have become a burgeoning public health problem in China. Programs need to be developed to prevent farm vehicle–related road traffic crashes in this emerging country.     

Etiology of fatal thoracic aortic injuries: Secondary data analysis

Objectives: Motor vehicle crashes remain a leading cause of death in the United States (US). Thoracic aortic dissection due to blunt trauma remains a major injury mechanism, and up to 90% of these injuries result in death on the scene. The objective of this study is to understand the modern risk factors and etiology of fatal thoracic aortic injuries in the current US fleet.

Methods: Using a unique, linked, Fatality Analysis Reporting System (FARS) and Multiple Cause of Death (MCOD) database from 2000–2010, 144,169 drivers over 16 years of age who suffered fatal injuries were identified. The merged database provides an unparalleled fidelity for identifying thoracic aortic injuries due to motor vehicle accidents. Thoracic aortic injuries were defined by ICD-10 codes S250. Univariate and multivariate logistic regression models for presence of any thoracic aortic injuries were fitted. Age, gender, BMI weight categories, vehicle class, model year, crash type/direction, severity of crash damage, airbag deployment location, and seatbelt use, fatal injury codes, and location of injury were considered. Odds ratios (OR) and corresponding 95% confidence intervals (95%CI) are calculated.

Results: There were 2953 deaths (2.10%) related to thoracic aortic injuries that met the inclusion criteria. Nearside crashes were associated with an increased odds (OR = 1.42, 1.1-1.83), while rollover crashes (OR =.44,.29-.66) were associated with a reduced odds of fatal thoracic aortic injury. Using backward selection on the full multivariate model, the only significant model effects that remained were vehicle type, crash type, body region, and injury type.

Conclusions: The increased prevalence of fatal thoracic aortic injury in nearside crashes, increasing age, and vehicle type provide some insight into the current US fleet. Important factors, including model year, had significantly lower levels of the injury in univariate analysis, demonstrating the effect of safety improvements in newer model vehicles. Further study of this fatal injury is warranted, including comparisons of those who survive the injury.     

Analysis of naturalistic driving videos of fleet services drivers to estimate driver error and potentially distracting behaviors as risk factors for rear-end versus angle crashes

Objective: The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes.

Methods: Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes.

Results: Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73–5.44) times adjusted higher odds of being potentially distracted than those in angle crashes.

Conclusions: Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.     

Exploratory multinomial logit model–based driver injury severity analyses for teenage and adult drivers in intersection-related crashes

Objective: Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle–infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities.

Methods: Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality.

Results: The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups.

Conclusions: The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.     

Injury risk functions for frontal oblique collisions

Objective: The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set.

Method: Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes―a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured).

Results: IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18–64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes.

Conclusions: The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.     

The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes

Objective: The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes.

Methods: The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems.

Results: The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions).

Conclusions: LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.     

Driver's obesity and road crash risks in the United States

Objective: We assessed obesity trends in U.S. drivers involved in fatal crashes since 1999 and distinguished whether crash risk factors were different between obese and nonobese drivers.

Methods: We included only drivers of passenger cars involved in fatal traffic crashes between January 1, 1999, and December 31, 2012. Obesity was classified according to the World Health Organization guidelines and profiled between 1999 and 2012 using the adjusted prevalence ratio (aPR) from log-binomial regression models. Differences in crash risks (e.g., driver's fatality, drunk driving, seat belt nonuse) between obese and nonobese drivers were estimated as adjusted odds ratios (aORs) using logistic regression models.

Results: A total of 753,024 U.S. drivers were involved in fatal crashes, for which obesity information was available for 534,887. About 56% (n = 299,078) were driving passenger cars. The prevalence of class I obesity increased from 10% in 1999 to 14% in 2012 (aPR = 1.50, 95% confidence interval [CI], 1.42–1.58), class II obesity from 3 to 5% (aPR = 2.22, 95% CI, 2.05–3.01), and class III obesity from 1 to 2% (aPR = 2.65; 95% CI, 2.27–3.10). Compared to nonobese controls, obese drivers had significantly higher risks for fatality (1.10 ≤ aOR ≤ 1.47), seat belt nonuse (1.00 ≤ aOR ≤ 1.21), need for extrication (1.01 ≤ aOR ≤ 1.23), and ambulance transport time ≥30 min (1.01 ≤ aOR ≤ 1.28). Compared to nonobese controls, obese drivers were less likely to drink drive (0.41 ≤ aOR ≤ 0.72) or speed >65 mph (0.78 ≤ aOR ≤ 0.93).

Conclusion: The rising national prevalence of obesity extends to U.S. drivers involved in fatal crashes and indicates the need to improve seat belt use, vehicle design, and postcrash care for this vulnerable population.     

Ankle fracture patterns in drivers are associated with femoral fracture,higher BMI,and advanced age

Objective: Despite advances in vehicle safety systems, motor vehicle crashes continue to cause ankle fractures. This study attempts to provide insight into the mechanisms of injury and to identify the at-risk population groups.

Methods: A study was made of ankle fractures patients treated at an urban level 1 trauma center following motor vehicle crashes, with a concurrent analysis of a nationally representative crash data set. The national data set focused on ankle fractures in drivers involved in frontal crashes. Statistical analysis was applied to the national data set to identify factors associated with fracture risk.

Results: Malleolar fractures occurred most frequently in the driver's right foot due to pedal interaction. The majority of complex/open fractures occurred in the left foot due to interaction with the vehicle floor. These fractures occurred in association with a femoral fracture, but their broad injury pattern suggests a range of fracture causation mechanisms. The statistical analysis indicated that the risk of fracture increased with increasing driver body mass index (BMI) and age.

Conclusions: Efforts to reduce the risk of driver ankle injury should focus on right foot and pedal interaction. The range of injury patterns identified here suggest that efforts to minimize driver ankle fracture risk will likely need to consider injury tolerances for flexion, pronation/supination, and axial loading in order to capture the full range of injury mechanisms. In the clinical environment, physicians examining drivers after a frontal crash should consider those who are older or obese or who have severe femoral injury without concurrent head injury as highly suspicious for an ankle injury.     

Wrong-way driving crashes: A multiple correspondence approach to identify contributing factors

Objective: Wrong-way driving (WWD) crashes result in 1.34 fatalities per fatal crash, whereas for other non-WWD fatal crashes this number drops to 1.10. As such, further in-depth investigation of WWD crashes is necessary. The objective of this study is 2-fold: to identify the characteristics that best describe WWD crashes and to verify the factors associated with WWD occurrence.

Methods: We collected and analyzed 15 years of crash data from the states of Illinois and Alabama. The final data set includes 398 WWD crashes. The rarity of WWD events and the consequently small sample size of the crash database significantly influence the application of conventional log-linear models in analyzing the data, because they use maximum-likelihood estimation. To overcome this issue, in this study, we employ multiple correspondence analysis (MCA) to define the structure of the crash data set and identify the significant contributing factors to WWD crashes on freeways.

Results: The results of the present study specify various factors that characterize and influence the probability of WWD crashes and can thus lead to the development of several safety countermeasures and recommendations. According to the obtained results, factors such as driver age, driver condition, roadway surface conditions, and lighting conditions were among the most significant contributors to WWD crashes.

Conclusions: Despite many other methods that identify only the contributing factors, this method can identify possible associations between various contributing factors. This is an inherent advantage of the MCA method, which can provide a major opportunity for state departments of transportation (DOTs) to select safety countermeasures that are associated with multiple safety benefits.     

Risk of serious injury of occupants involved in frontal crashes of cab-over-type trucks

Objectives: Truck vehicles (TVs) have a different structure and stiffness than non-TVs and are used commercially for transporting goods. This study aimed to analyze whether truck occupants have a greater risk of serious injury than those of other types of vehicles.

Methods: Crash data were obtained from the Korean In-Depth Data Analysis Study (KIDAS) for calendar years 2011–2016. Vehicles involved in frontal crash were included and classified into TVs and non-TVs (passenger cars and sports utility vehicles). We compared the demographic characteristics and serious injuries by body region between the 2 groups and analyzed factors that contributed to the serious injury severity from frontal crashes.

Results: The analysis was based on 884 occupants; 177 (20.0%) were in TVs and 707 (80.0%) were in non-TVs. Non-TVs had more frontal airbags deployments than TVs (50.9% vs. 3.4%, P <.01). TV occupants were 4.8 times more likely to have a serious lower extremity (LE) injury (adjusted odds ratio [AOR] = 4.820; 95% confidence interval [CI], 2.407–9.653) and 2.5 times to have a serious abdominal injury (AOR = 2.465; 95% CI, 1.108–5.487) compared to non-TV occupants.

Conclusions: Truck occupants had more serious LE and abdominal injuries than those of other types of vehicles in frontal crashes. Structural improvement and legislative efforts to develop safety systems are necessary to improve the safety of truck occupants.     

Driver injury severity related to inclement weather at highway–rail grade crossings in the United States

Objective: Previous studies on crash modeling at highway–rail grade crossings were aimed at exploring the factors that are likely to increase the crash frequencies at highway–rail grade crossings. In recent years, modeling driver's injury severity at highway–rail grade crossings has received interest. Because there were substantial differences among different weather conditions for driver's injury severity, this study attempts to explore the impact of weather influence on driver injury at highway–rail grade crossing.

Method: Utilizing the most recent 10 years (2002–2011) of highway–rail grade crossing accident data, this study applied a mixed logit model to explore the determinants of driver injury severity under different weather conditions at highway–rail grade crossing.

Results: Analysis results indicate that drivers' injury severity at highway–rail grade crossings is strongly different for different weather conditions. It was found that the factors significantly impacting driver injury severity at highway–rail grade crossings include motor vehicle speed, train speed, driver's age, gender, area type, lighting condition, highway pavement, traffic volume, and time of day.

Conclusions: The findings of this study indicate that crashes are more prevalent if vehicle drivers are driving at high speed or the oncoming trains are high speed. Hence, a reduction in speed limit during inclement weather conditions could be particularly effective in moderating injury severity, allowing more reaction time for last-minute maneuvering and braking in moments before impacts. In addition, inclement weather-related crashes were more likely to occur in open areas and highway–rail grade crossings without pavement and lighting. Paved highway–rail grade crossings with installation of lights could be particularly effective in moderating injury severity.     

Modeling crash injury severity by road feature to improve safety

Objective: The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature.

Method: Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity.

Results: Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway.

Conclusions: The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.