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.     

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.     

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.     

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.     

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.     

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.     

Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects

Objective: Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR.

Methods: This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model.

Results: Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime.

Conclusions: This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.     

Exposure factors of Victoria's active motorcycle fleet related to serious injury crash risk

Objective: The purpose of this study was to describe the nature and extent of current powered 2-wheeler (PTW) risk exposures in order to support future efforts to improve safety for this mode of transport.

Methods: A cross-sectional analysis of the control arm of a population-based case-control study was conducted. The control sample was selected from 204 sites on public roads within 150 km of the city of Melbourne that were locations of recent serious injury motorcycle crashes. Traffic observations and measurements at each site were sampled for a mean of 2 h on the same type of day (weekday, Saturday, or Sunday) and within 1 h of the crash time. Photographs of passing riders during this observation period recorded data relating to characteristics of PTWs, age of riders, travel speed of PTWs and all vehicles, time gaps between vehicles, visibility, and protective clothing use.

Results: Motorcycles and scooters represented 0.6% of all traffic (compared with 4% of all vehicle registrations). Riders were significantly more likely to have larger time gaps in front and behind when compared to other vehicles. The average travel speed of motorcycles was not significantly different than the traffic, but a significantly greater proportion were exceeding the speed limit when compared to other vehicles (6 vs. 3%, respectively). The age of registered owners of passing motorcycles was 42 years. Over half of riders were wearing dark clothing with no fluorescent or reflective surfaces. One third of motorcyclists had maximum coverage of motorcycle-specific protective clothing.

Conclusions: A very low prevalence of motorcyclists combined with relatively higher rates of larger time gaps to other vehicles around motorcycles may help explain their overrepresentation in injury crashes where another vehicle fails to give way. An increased risk of injury in the event of a crash exists for a small but greater proportion of motorcyclists (compared to other vehicle types) who were exceeding the speed limit. An apparent shift toward older age of the active rider population may be reducing injury crash risk relative to exposure time. There is significant scope to improve the physical conspicuity of motorcyclists and the frequency of motorcycle specific protective clothing use. These results can be used to inform policy development and monitor progress of current and future road safety initiatives.     

Understanding traffic crash under-reporting: Linking police and medical records to individual and crash characteristics

Objective: This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both.

Method: This study focuses on road crash injuries that occurred in the province of Funen, Denmark, between 2003 and 2007 and were registered in the police, the hospital, or both authorities. Underreporting rates are computed with the capture–recapture method, and the probability for road crash injuries in police records to appear in hospital records (and vice versa) is estimated with joint binary logit models.

Results: The capture–recapture analysis shows high underreporting rates of road crash injuries in Denmark and the growth of underreporting not only with the decrease in injury severity but also with the involvement of cyclists (reporting rates of about 14% for serious injuries and 7% for slight injuries) and motorcyclists (reporting rates of about 35% for serious injuries and 10% for slight injuries). Model estimates show that the likelihood of appearing in both data sets is positively related to helmet and seat belt use, number of motor vehicles involved, alcohol involvement, higher speed limit, and females being injured.

Conclusions: This study adds significantly to the literature about underreporting by recognizing that understanding the heterogeneity in the reporting rate of road crashes may lead to devising policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend).     

Analyzing pedestrian crash injury severity under different weather conditions

Objective: Pedestrians are the most vulnerable road users due to the lack of mass, speed, and protection compared to other types of road users. Adverse weather conditions may reduce road friction and visibility and thus increase crash risk. There is limited evidence and considerable discrepancy with regard to impacts of weather conditions on injury severity in the literature. This article investigated factors affecting pedestrian injury severity level under different weather conditions based on a publicly available accident database in Great Britain.

Method: Accident data from Great Britain that are publicly available through the STATS19 database were analyzed. Factors associated with pedestrian, driver, and environment were investigated using a novel approach that combines a classification and regression tree with random forest approach.

Results: Significant severity predictors under fine weather conditions from the models included speed limits, pedestrian age, light conditions, and vehicle maneuver. Under adverse weather conditions, the significant predictors were pedestrian age, vehicle maneuver, and speed limit.

Conclusions: Elderly pedestrians are associated with higher pedestrian injury severities. Higher speed limits increase pedestrian injury severity. Based on the research findings, recommendations are provided to improve pedestrian safety.     

The combined benefits of motorcycle antilock braking systems (ABS) in preventing crashes and reducing crash severity

Objective: Several studies have reported the benefits of motorcycle antilock braking systems (ABS) in reducing injury crashes, due to improved stability and braking performance. Both aspects may prevent crashes but may also reduce the crash severity when a collision occurs. However, it is still unknown to what extent the reductions in injury crashes with ABS may be due to a combination of these mechanisms.

Methods: Swedish hospital and police reports (2003–2012) were used. The risk for permanent medical impairment (RPMI) was calculated, showing the risk of at least 1 or 10% permanent medical impairment. In total, 165 crashes involving ABS-equipped motorcycles were compared with 500 crashes with similar motorcycles without ABS.

The analysis was performed in 3 steps. First, the reduction in emergency care visits with ABS was calculated using an induced exposure approach. Secondly, the injury mitigating effects of ABS were investigated. The mean RPMI 1+ and RPMI 10+ were analyzed for different crash types. The distributions of impairing injuries (PMI 1+) and severely impairing injuries (PMI 10+) were also analyzed. In the third step, the total reduction of PMI 1+ and PMI 10+ injured motorcyclists was calculated by combining the reductions found in the previous steps. An additional analysis of combined braking systems (CBS) together with ABS was also performed.

Results: The results showed that emergency care visits were reduced by 47% with ABS. In the second step, it was found that the mean RPMI 1+ and RPMI 10+ with ABS were 15 and 37% lower, respectively. Finally, the third step showed that the total reductions in terms of crash avoidance and mitigation of PMI 1+ and PMI 10+ injured motorcyclists with ABS were 67 and 55%, respectively. However, PMI 1+ and PMI 10+ leg injuries were not reduced by ABS to the same extent. Indications were found suggesting that the benefits of ABS together with CBS may be greater than ABS alone.

Conclusions: This article indicated that motorcycle ABS reduced impairing injuries, mostly due to fewer emergency care visits but also due to a reduction in crash severity. This may seem reasonable as the improved stability and braking performance provided by ABS could prevent some crashes but would also decrease crash severity if a collision still occurs. As suggested by previous studies, however, the lower extremities would be more exposed in a crash with ABS. It is recommended that future research should follow up these results with additional data.     

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.     

Pedestrian fatality and impact speed squared: Cloglog modeling from French national data

Objective: The present study estimates pedestrians' risk of death according to impact speed when hit by a passenger car in a frontal collision.

Methods: Data were coded for all fatal crashes in France in 2011 and for a random sample of 1/20th of all road injuries for the same year and weighted to take into account police underreporting of mild injury. A cloglog model was used to optimize risk adjustment for high collision speeds. The fit of the model on the data was also improved by using the square of the impact speed, which best matches the energy dissipated in the collision.

Results: Modeling clearly demonstrated that the risk of death was very close to 1 when impact speeds exceeded 80 km/h. For speeds less than 40 km/h, because data representative of all crashes resulting in injury were used, the estimated risk of death was fairly low. However, although the curve seemed deceptively flat below 50 km/h, the risk of death in fact rose 2-fold between 30 and 40 km/h and 6-fold between 30 and 50 km/h. For any given speed, the risk of death was much higher for more elderly subjects, especially those over 75 years of age. These results concern frontal crashes involving a passenger car. Collisions involving trucks are far less frequent, but half result in the pedestrian being run over, incurring greater mortality.

Conclusions: For impact speeds below 60 km/h, the shape of the curve relating probability of death to impact speed was very similar to those reported in recent rigorous studies. For higher impact speeds, the present model allows the curve to rise ever more steeply, giving a much better fit to observed data. The present results confirm that, when a pedestrian is struck by a car, impact speed is a major risk factor, thus providing a supplementary argument for strict speed limits in areas where pedestrians are highly exposed.     

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.     

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.     

Risk factors for motorcycle loss-of-control crashes

Objective: The present article identifies and assesses the effect of critical factors on the risk of motorcycle loss-of-control (LOC) crashes.

Method: Data come from a French project on road crashes, which include all fatal road crashes and a random sample of 1/20th of nonfatal crashes in France in 2011, based on police reports. A case–control study was carried out on a sample of 903 crashes for 444 LOC motorcycle riders (case) and 470 non-LOC and nonresponsible motorcycle riders (control). The sample was weighted due to the randomization of nonfatal crashes. Missing values were imputed using multiple imputation.

Results: Road alignment and surface conditions, human factors, and motorcycle type played important roles in motorcycle LOC crashes. Riding in a curve was associated with a 3-fold greater risk of losing control of motorcycle than riding in a straight line. Poor road adhesion significantly increased the risk of losing control; the risk increased more than 20-fold when deteriorated road adhesion was encountered unexpectedly, due to loose gravel, ice, oil, bumps, road marking, metal plates, etc. For motorcyclists, riding with a positive blood alcohol concentration (over or equal to the legal limit of 0.5 g/L) was very dangerous, often resulting in losing control. The risk of LOC crash varied for different types of motorcycle: Riders of roadsters and sports bikes were more likely to have an LOC crash greater than that of riders of basic or touring motorcycles. In addition, LOC risk increased with speed; a model using the square of the traveling speed showed better fit than one using speed itself.

Conclusion: The LOC crash factors related to riders, vehicles, and road infrastructure identified here were expected but were rarely identified and taken simultaneously into account in previous studies. They could be targeted by countermeasures to improve motorcyclist safety.     

Prevalence of alcohol impairment and odds of a driver injury or fatality in on-road farm equipment crashes

Objective: The objective of this article was to estimate the prevalence of alcohol impairment in crashes involving farm equipment on public roadways and the effect of alcohol impairment on the odds of crash injury or fatality.

Methods: On-road farm equipment crashes were collected from 4 Great Plains state departments of transportation during 2005–2010. Alcohol impairment was defined as an involved driver having blood alcohol content of ≥0.08 g/100 ml or a finding of alcohol impairment as a driver contributing circumstance recorded on the police crash report. Injury or fatality was categorized as (a) no injury (no and possible injury combined), (b) injury (nonincapacitating or incapacitating injury), and (c) fatality. Hierarchical multivariable logistic regression modeling, clustered on crash, was used to estimate the odds of an injury/fatality in crashes involving an alcohol-impaired driver.

Results: During the 5 years under study, 3.1% (61 of 1971) of on-road farm equipment crashes involved an alcohol-impaired driver. One in 20 (5.6%) injury crashes and 1 in 6 (17.8%) fatality crashes involved an alcohol-impaired driver. The non-farm equipment driver was significantly more likely to be alcohol impaired than the farm equipment driver (2.4% versus 1.1% respectively, P = .0012). After controlling for covariates, crashes involving an alcohol-impaired driver had 4.10 (95% confidence interval [CI], 2.30–7.28) times the odds of an injury or fatality. In addition, the non-farm vehicle driver was at 2.28 (95% CI, 1.92–2.71) times higher odds of an injury or fatality than the farm vehicle driver. No differences in rurality of the crash site were found in the multivariable model.

Conclusion: On-road farm equipment crashes involving alcohol result in greater odds of an injury or fatality. The risk of injury or fatality is higher among the non-farm equipment vehicle drivers who are also more likely to be alcohol impaired. Further studies are needed to measure the impact of alcohol impairment in on-road farm equipment crashes.     

An empirical bayes safety evaluation of tram/streetcar signal and lane priority measures in Melbourne

Objective: Streetcars/tram systems are growing worldwide, and many are given priority to increase speed and reliability performance in mixed traffic conditions. Research related to the road safety impact of tram priority is limited. This study explores the road safety impacts of tram priority measures including lane and intersection/signal priority measures.

Method: A before–after crash study was conducted using the empirical Bayes (EB) method to provide more accurate crash impact estimates by accounting for wider crash trends and regression to the mean effects. Before–after crash data for 29 intersections with tram signal priority and 23 arterials with tram lane priority in Melbourne, Australia, were analyzed to evaluate the road safety impact of tram priority.

Results: The EB before–after analysis results indicated a statistically significant adjusted crash reduction rate of 16.4% after implementation of tram priority measures. Signal priority measures were found to reduce crashes by 13.9% and lane priority by 19.4%. A disaggregate level simple before–after analysis indicated reductions in total and serious crashes as well as vehicle-, pedestrian-, and motorcycle-involved crashes. In addition, reductions in on-path crashes, pedestrian-involved crashes, and collisions among vehicles moving in the same and opposite directions and all other specific crash types were found after tram priority implementation.

Conclusions: Results suggest that streetcar/tram priority measures result in safety benefits for all road users, including vehicles, pedestrians, and cyclists. Policy implications and areas for future research are discussed.     

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.     

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.