Risk factors for the severity of injury incurred in crashes involving on-duty police cars

Objective: This article explores the risk factors associated with police cars on routine patrol and/or on an emergency run and their effects on the severity of injuries in crashes.

Methods: The binary probit model is used to examine the effects of important factors on the risk of injuries sustained in crashes involving on-duty police cars.

Results: Several factors significantly increase the probability of crashes that cause severe injuries. Among those causes are police officers who drive at excessive speeds, traffic violations during emergency responses or pursuits, and driving during the evening (6 to 12 p.m.) or in rainy weather. Findings also indicate some potential issues associated with an increase in the probability of crashes that cause injuries. Younger police drivers were found to be more likely to be involved in crashes causing injuries than middle-aged drivers were. Distracted driving by on-duty police officers as well as civilian drivers who did not pull over to let a police car pass in emergency situations also caused serious crashes.

Conclusions: Police cars are exempted from certain traffic laws under emergency circumstances. However, to reduce the probability of being involved in a crash resulting in severe injuries, officers are still obligated to drive safely and follow safety procedures when responding to emergencies or pursuing a car. Enhancement of training techniques for emergency situations or driving in pursuit of an offender and following the safety procedures are essential for safety in driving during an emergency run by police.     

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.     

Motorcycle crashes potentially preventable by three crash avoidance technologies on passenger vehicles

Objective: The objective of this study was to identify and quantify the motorcycle crash population that would be potential beneficiaries of 3 crash avoidance technologies recently available on passenger vehicles.

Methods: Two-vehicle crashes between a motorcycle and a passenger vehicle that occurred in the United States during 2011–2015 were classified by type, with consideration of the functionality of 3 classes of passenger vehicle crash avoidance technologies: frontal crash prevention, lane maintenance, and blind spot detection. Results were expressed as the percentage of crashes potentially preventable by each type of technology, based on all known types of 2-vehicle crashes and based on all crashes involving motorcycles.

Results: Frontal crash prevention had the largest potential to prevent 2-vehicle motorcycle crashes with passenger vehicles. The 3 technologies in sum had the potential to prevent 10% of fatal 2-vehicle crashes and 23% of police-reported crashes. However, because 2-vehicle crashes with a passenger vehicle represent fewer than half of all motorcycle crashes, these technologies represent a potential to avoid 4% of all fatal motorcycle crashes and 10% of all police-reported motorcycle crashes.

Discussion: Refining the ability of passenger vehicle crash avoidance systems to detect motorcycles represents an opportunity to improve motorcycle safety. Expanding the capabilities of these technologies represents an even greater opportunity. However, even fully realizing these opportunities can affect only a minority of motorcycle crashes and does not change the need for other motorcycle safety countermeasures such as helmets, universal helmet laws, and antilock braking systems.     

Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

Powered two-wheeler riders' risk of crashes associated with filtering on urban roads

Objective: The objective of this study is to estimate the crash risk per kilometer traveled by powered two-wheeler (PTW) riders filtering through traffic on urban roads.

Methods: Using the traffic injury crashes recorded by the police over a period of 3 years on 14 sections of urban roads in the city of Marseille, France, and a campaign of observations of PTWs, the crash risk per kilometer traveled by PTWs filtering was estimated and compared to the risk of PTWs that did not filter.

Results: The results show that the risk of PTW riders being involved in injury crashes while filtering is significantly higher than the risk for riders who do not filter. For the 14 sections studied, it is 3.94 times greater (95% confidence interval [CI], 2.63, 5.89). This excess risk occurred for all PTW categories. Furthermore, no space appears to be safer than the others for filtering. Riders filtering forward along the axis of the carriageway, along bus lanes, or between traffic lanes (lane-splitting) all have a crash risk greater than the risk of those who do not filter.

Conclusions: All measures limiting the practice of filtering by PTWs on urban roads would probably contribute to improving the safety of their users.     

Spatial patterns of off-the-system traffic crashes in Miami–Dade County,Florida, during 2005–2010

Objective: The objective of this study is to analyze the spatial distribution of the vehicles involved in crashes in Miami–Dade County. In addition, we analyzed the role of time of day, day of the week, seasonality, drivers’ age in the distribution of traffic crashes.

Method: Off-the-system crash data acquired from the Florida Department of Transportation during 2005–2010 were divided into subcategories according to the risk factors age, time of day, day of the week, and travel season. Various spatial statistics methods, including nearest neighbor analysis, Getis-Ord hot spot analysis, and kernel density analysis revealed substantial spatial variations, depending on the subcategory in question.

Results: Downtown Miami and South Beach showed up consistently as hotspots of traffic crashes in all subcategories except fatal crashes. However, fatal crashes were concentrated in residential areas in inland areas.

Conclusion: This understanding of patterns can help the county target high-risk areas and help to reduce crash fatalities to create a safer environment for motorists and pedestrians.     

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.     

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.     

Undercounting of large trucks in federal and state crash databases: Extent of problem and how to improve accuracy of truck classifications

Objective: Prior research suggested that single-unit trucks are undercounted when using vehicle body codes in the Fatality Analysis Reporting System (FARS). This study explored the extent of the misclassification and undercounting problem for crashes in FARS and state crash databases.

Methods: Truck misclassifications for fatal crashes were explored by comparing the Trucks Involved in Fatal Accidents (TIFA) database with FARS. TIFA used vehicle identification numbers (VINs) and survey information to classify large trucks. This study used VINs to improve the accuracy of large truck classifications in state crash databases from 5 states (Delaware, Maryland, Minnesota, Nebraska, and Utah).

Results: The vehicle body type codes resulted in a 19% undercount of single-unit trucks in FARS and a 23% undercount of single-unit trucks in state databases. Tractor-trailers were misclassified less often. Misclassifications occurred most frequently among single-unit trucks in the weight classes of 10,001–14,000 pounds.

Conclusions: The amount of misclassification of large trucks is large enough to potentially affect federal and state decisions on traffic safety. Using information from VINs results in more complete and accurate counts of large trucks involved in crashes. The National Transportation Safety Board recommended actions to improve federal and state crash data.     

Effects of vehicle power on passenger vehicle speeds

Objectives: During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to–vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight.

Methods: Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit.

Results: After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant.

Conclusions: Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash risk and crash severity, this is cause for concern.     

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.     

Influence of pedestrian age and gender on spatial and temporal distribution of pedestrian crashes

Objectives: Every year, about 1.24 million people are killed in traffic crashes worldwide and more than 22% of these deaths are pedestrians. Therefore, pedestrian safety has become a significant traffic safety issue worldwide. In order to develop effective and targeted safety programs, the location- and time-specific influences on vehicle–pedestrian crashes must be assessed. The main purpose of this research is to explore the influence of pedestrian age and gender on the temporal and spatial distribution of vehicle–pedestrian crashes to identify the hotspots and hot times.

Methods: Data for all vehicle–pedestrian crashes on public roadways in the Melbourne metropolitan area from 2004 to 2013 are used in this research. Spatial autocorrelation is applied in examining the vehicle–pedestrian crashes in geographic information systems (GIS) to identify any dependency between time and location of these crashes. Spider plots and kernel density estimation (KDE) are then used to determine the temporal and spatial patterns of vehicle–pedestrian crashes for different age groups and genders.

Results: Temporal analysis shows that pedestrian age has a significant influence on the temporal distribution of vehicle–pedestrian crashes. Furthermore, men and women have different crash patterns. In addition, results of the spatial analysis shows that areas with high risk of vehicle–pedestrian crashes can vary during different times of the day for different age groups and genders. For example, for those between ages 18 and 65, most vehicle–pedestrian crashes occur in the central business district (CBD) during the day, but between 7:00 p.m. and 6:00 a.m., crashes among this age group occur mostly around hotels, clubs, and bars.

Conclusions: This research reveals that temporal and spatial distributions of vehicle–pedestrian crashes vary for different pedestrian age groups and genders. Therefore, specific safety measures should be in place during high crash times at different locations for different age groups and genders to increase the effectiveness of the countermeasures in preventing and reducing vehicle–pedestrian crashes.     

Road traffic injuries among riders of electric bike/electric moped in southern China

Objective: Electric bike/moped-related road traffic injuries have become a burgeoning public health problem in China. The objective of this study was to identify the prevalence and potential risk factors of electric bike/moped-related road traffic injuries among electric bike/moped riders in southern China.

Methods: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017.

Results: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01–1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13–2.78), history of crashes (AOR = 6.14, 95% CI, 4.68–8.07), running red lights (AOR = 3.57, 95% CI, 2.42–5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37–2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23–2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05–3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13–2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane.

Conclusion: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country.     

Importance of awareness in improving performance of emergency medical services (EMS) systems in enhancing traffic safety: A lesson from India

Objective: India has been slow in implementing a central emergency medical services (EMS) system across the country. “108 services” is one of the most popular services that is functional under the public–private partnership model. Limited available literature shows that despite access to services, many traffic crash victims are transported using private vehicles. The objective of this study is to understand the effectiveness of 108 services from a traffic safety perspective.

Method: A questionnaire survey is conducted to understand the awareness of EMS and their function. Using traffic-related fatalities as the dependent variable, a fixed effect panel data model is developed to analyze the effectiveness of the 108 services in improving the traffic safety.

Results: The results from the survey show that, in general, people are not aware of the 108 services. A majority of the population prefers taking victims to the hospital using their personal vehicles or any other vehicles available compared to calling an ambulance. Results from panel data analysis show that despite having an efficient system, these services failed to make significant improvement in the safety of road users in the states in which their services were subscribed.

Discussion: The lack of awareness of an important safety service is alarming. This could be a major reason for lower utilization of 108 services for transporting victims of traffic crashes. This article shows the importance of having efficient awareness campaigns to improve the efficiency of any similar programs that are aimed to enhance the safety of a region.     

An evaluation scheme for assessing the effectiveness of intersection movement assist (IMA) on improving traffic safety

Objective: Intersection movement assist (IMA) has been recognized as one of the prominent countermeasures to reduce angle crashes at intersections, which constitute 22% of total crashes in the United States. Utilizing vehicle-based sensors, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communications, IMA offers extended vision to provide early warning for an imminent crash. However, most of IMA-related research implements their methods and strategies only in simulations, test tracks, or driving simulator studies that have quite a few assumptions and limitations and hence the effectiveness evaluations reported may not be transferable or comparable.

Methods: This study seeks to develop a generalized evaluation scheme that can be used not only to assess the effectiveness of IMA on improving traffic safety at intersections but to facilitate comparisons across similar studies. The proposed evaluation scheme utilizes the concepts of traffic conflict in terms of time-to-collision (TTC) as a crash surrogate. This approach avoids the issue of having insufficient crash frequency data for system evaluation. To measure the effectiveness of IMA on reducing traffic conflicts, a relative risk is calculated for comparing the risk of with/without using the IMA. As a proof-of-concept study, this study applied the proposed evaluation scheme and reported the effectiveness of IMA on improving traffic safety in a field operation test (FOT). Seven test scenarios were conducted at 4 intersections, and a total of 40 participants were recruited to use the IMA for 6 months.

Results: It was estimated that IMA users have 26% fewer conflicts with TTC less than 5 s and have 15% fewer conflicts with TTC less than 4 s. However, the results vary across different sites and different definitions of conflicts in terms of TTC.

Conclusions: Overall, IMA is promising to effectively reduce angle crashes related to sight obstruction and has potential to reduce not only crash frequency but crash severity.     

A study of fatal pedestrian crashes at rural low-volume road intersections in southwest China

Objective: Although intersections correspond to a small proportion of the entire roadway system, they account for a disproportionally high number of fatal pedestrian crashes, especially on rural roads situated in low- and middle-income countries. This article examines pedestrian safety at rural intersections and suggests applicable accident prevention treatments by providing an in-depth analysis of 28 fatal pedestrian crashes from 8 low-volume roads in southwest China.

Methods: The driving reliability and error analysis method (DREAM) is a method to support a systematic classification of accident causation information and to facilitate aggregation of that information into patterns of contributing factors. This is the first time that DREAM was used to analyze pedestrian–vehicle crashes and provide suggestions for road improvements in China.

Results: The key issues adversely affecting pedestrian safety can be organized in 4 distinctive thematic categories, namely, deficient intersection safety infrastructure, lack of pedestrian safety education, inadequate driver training, and insufficient traffic law enforcement. Given that resources for traffic safety investments in rural areas are limited, it is determined that the potential countermeasures should focus on low-cost, easily implementable, and long-lasting measures increasing the visibility and predictability of pedestrian movement and reducing speeding and irresponsible driving among drivers and risk-taking behaviors among pedestrians.

Conclusions: Accident prevention treatments are suggested based on their suitability for rural areas in southwest China. These countermeasures include introducing better access management and traffic calming treatments, providing more opportunities for pedestrian education, and enhancing the quality of driver training and traffic law enforcement.     

Motorcycle safety among motorcycle taxi drivers and nonoccupational motorcyclists in developing countries: A case study of Maoming,South China

Objective: An increasing number of motorcycle taxis have been involved in traffic crashes in many developing countries. This study examines the characteristics of both motorcycle taxi drivers and nonoccupational motorcyclists, investigates the risks they pose to road safety, and provides recommendations to minimize their risks.

Methods: Based on the data collected from a questionnaire survey of 867 motorcycle taxi drivers and 2,029 nonoccupational motorcyclists in Maoming, South China, comparisons were made to analyze differences of personal attributes, attitudes toward road safety, and self-reported behavior of the 2 groups.

Results: Results of the chi-square tests show that not only motorcycle taxi drivers but also nonoccupational motorcyclists in Maoming held poor attitudes toward road safety and both groups reported unsafe driving behavior. There is much room for improving local road safety education among all motorcyclists in Maoming. Yet, motorcycle taxi drivers were more likely to pose road safety risks than nonoccupational motorcyclists under some circumstances, such as speeding late at night or early in the morning, not requiring passengers to wear helmets, and running a red light. The results of the binary logistic regression model show that possessing a vehicle license for a motorcycle or not was the common significant predictor for unsafe driving behavior of motorcycle taxi drivers and nonoccupational motorcyclists. Therefore, enforcement against all motorcyclists not showing vehicle licenses for their motorcycles should be stepped up.

Conclusion: Motorcycle safety is largely poor in Maoming. Therefore, efforts to improve motorcycle safety should be strengthened by targeting not only motorcycle taxi drivers but also nonoccupational motorcyclists.     

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.