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.     

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

Aims: Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

Methods: A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004–2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

Results: Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

Conclusions: Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.     

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.     

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.     

Investigating factors influencing pedestrian injury severity at intersections

Objective: Vehicle crashes that involve pedestrians at intersections have been reported occasionally. Pedestrian injury severity in these crashes is significantly related to driver and pedestrian attributes, vehicle characteristics, and the geometry of intersections. Identifying factors associated with pedestrian injury severity (PIS) is critical for reducing crashes and improving safety. For developing the proposed probit models, drivers involved in crashes are classified into 3 groups: young drivers (16 ≤ age ≤ 24), middle-aged drivers (25 ≤ age ≤ 64), and older drivers (age ≥ 65). This study determines that PIS is significantly but differently affected by these grouped drivers with different sets of explanatory variables.

Methods: A total of 2,614 crash records (2011–2012) at intersections in Cook County, Illinois, were collected. An ordered probit modeling approach was employed to develop the proposed model and examine factors influencing PIS. The likelihood ratio test was used to assess model performance. Elasticity analysis was conducted to interpret the marginal effect of contributing factors on PIS associated with different driver groups by age.

Results: The results show that 4 independent variables, including pedestrian age, vehicle type, point of first contact, and weather condition, significantly affect PIS at intersections for all drivers. Two additional independent variables (i.e., number of vehicles and traffic type) affect PIS for young and middle-aged drivers, and 2 other variables (i.e., divided type and hit-and-run related) are significant to PIS for both young and older drivers.

Conclusions: The independent variables significant to PIS at intersections for young, middle-aged, and older driver groups were identified and the marginal effect of each variable to the likelihood of PIS were assessed.     

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.     

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.     

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.     

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.     

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.     

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 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.     

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.     

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.     

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.     

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.     

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.     

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.