Teenage driver crash incidence and factors influencing crash injury by rurality

BackgroundPrevious research has identified teenage drivers as having an increased risk for motor-vehicle crash injury compared with older drivers, and rural roads as having increased crash severity compared with urban roads. Few studies have examined incidence and characteristics of teen driver-involved crashes on rural and urban roads.MethodsAll crashes involving a driver aged 10 through 18 were identified from the Iowa Department of Transportation crash data from 2002 through 2008. Rates of overall crashes and fatal or severe injury crashes were calculated for urban, suburban, rural, and remote rural areas. The distribution of driver and crash characteristics were compared between rural and urban crashes. Logistic regression was used to identify driver and crash characteristics associated with increased odds of fatal or severe injury among urban and rural crashes.ResultsFor younger teen drivers (age 10 through 15), overall crash rates were higher for more rural areas, although for older teen drivers (age 16 through 18) the overall crash rates were lower for rural areas. Rural teen crashes were nearly five times more likely to lead to a fatal or severe injury crash than urban teen crashes. Rural crashes were more likely to involve single vehicles, be late at night, involve a failure to yield the right-of-way and crossing the center divider.ConclusionsIntervention programs to increase safe teen driving in rural areas need to address specific risk factors associated with rural roadways.Impact on IndustryTeen crashes cause lost work time for teen workers as well as their parents. Industries such as safety, health care, and insurance have a vested interest in enhanced vehicle safety, and these efforts should address risks and injury differentials in urban and rural roadways.     

Rage against the machine? Google's self-driving cars versus human drivers

IntroductionAutomated driving represents both challenges and opportunities in highway safety. Google has been developing self-driving cars and testing them under employee supervision on public roads since 2009. These vehicles have been involved in several crashes, and it is of interest how this testing program compares to human drivers in terms of safety.MethodsGoogle car crashes were coded by type and severity based on narratives released by Google. Crash rates per million vehicle miles traveled (VMT) were computed for crashes deemed severe enough to be reportable to police. These were compared with police-reported crash rates for human drivers. Crash types also were compared.ResultsGoogle cars had a much lower rate of police-reportable crashes per million VMT than human drivers in Mountain View, Calif., during 2009–2015 (2.19 vs 6.06), but the difference was not statistically significant. The most common type of collision involving Google cars was when they got rear-ended by another (human-driven) vehicle. Google cars shared responsibility for only one crash.ConclusionsThese results suggest Google self-driving cars, while a test program, are safer than conventional human-driven passenger vehicles; however, currently there is insufficient information to fully examine the extent to which disengagements affected these results.Practical applicationResults suggest that highly-automated vehicles can perform more safely than human drivers in certain conditions, but will continue to be involved in crashes with conventionally-driven vehicles.     

Injury-severity analysis of lane change crashes involving commercial motor vehicles on interstate highways

Introduction: One of the challenging tasks for drivers is the ability to change lanes around large commercial motor vehicles. Lane changing is often characterized by speed, and crashes that occur due to unsafe lane changes can have serious consequences. Considering the economic importance of commercial trucks, ensuring the safety, security, and resilience of freight transportation is of paramount concern to the United States Department of Transportation and other stakeholders. Method: In this study, a mixed (random parameters) logit model was developed to better understand the relationship between crash factors and associated injury severities of commercial vehicle crashes involving lane change on interstate highways. The study was based on 2009–2016 crash data from Alabama. Results: Preliminary data analysis showed that about 4% of the observed crashes were major injury crashes and drivers of commercial motor vehicles were at-fault in more than half of the crashes. Acknowledging potential crash data limitations, the model estimation results reveal that there is increased probability of major injury when lane change crashes occurred on dark unlit portions of interstates and involve older drivers, at-fault commercial vehicle drivers, and female drivers. The results further show that lane change crashes that occurred on interstates with higher number of travel lanes were less likely to have major injury outcomes. Practical Applications: These findings can help policy makers and state transportation agencies increase awareness on the hazards of changing lanes in the immediate vicinity and driving in the blind spots of large commercial motor vehicles. Additionally, law enforcement efforts may be intensified during times and locations of increased unsafe lane changing activities. These findings may also be useful in commercial vehicle driver training and driver licensing programs.     

Gender differences of young drivers on injury severity outcome of highway crashes

ProblemGender differences of young drivers involved in crashes and the associated differences in risk factors have not been fully explored in the United States (U.S.). Accordingly, this study investigated the topic, where the odds ratios (ORs) were used to identify differences in crash involvements between male and female young drivers.MethodLogistic regression models for injury severity of young male drivers and young female drivers were developed. Different driver, environmental, vehicle, and road related factors that have affected young female drivers' and young male drivers' crash involvements were identified using the models.ResultsResults indicated that some variables are significantly related to female drivers' injury risk but not male drivers' injury risk and vice versa. Variables such as driving with valid licenses, driving on weekends, avoidance or slow maneuvers at time of crash, non-collision and overturn crashes, and collision with a pedestrian were significant variables in female driver injury severity model but not in young male driver severity model. Travel on graded roadways, concrete surfaces, and wet road surfaces, collision with another vehicle, and rear-end collisions were variables that were significant in male-driver severity model but not in female-driver severity model.SummaryFactors which increase young female drivers' injury severity and young male drivers' injury severity were identified. This study adds detailed information about gender differences and similarities in injury severity risk of young drivers.Practical applicationsIt is important to note that the findings of this study show that gender differences do exists among young drivers. This sends a message to the industry that the transportation professionals and researchers, who are developing countermeasures to increase the traffic safety, may need to pay attention to the differences. This might be particularly true when developing education materials for driver training for young/inexperienced drivers.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

Responsibility of drivers, by age and gender, for motor-vehicle crash deaths

Problem: Motor-vehicle crash rate comparisons by age and gender usually are based on the extent to which drivers in a particular age/gender category are themselves injured or involved in crashes (e.g., the number of 20-year-old females in crashes). Basing comparisons instead on the extent to which drivers in various age/gender groups are responsible for deaths (including themselves) in their crashes is more revealing of their overall contribution to the problem. Methods: Data from the Fatality Analysis Reporting System (FARS, 1996–2000) were used in the analysis, which was based on crashes that involved one or two vehicles only. Drivers in fatal single-vehicle crashes were assumed to have responsibility for the crash. In fatal two-vehicle crashes, driver operator errors reported by police were used to assign crash responsibility. Results: When all crashes were considered, both the youngest and oldest drivers were most likely to be responsible for deaths in their crashes. In two-vehicle crashes, the oldest drivers were more likely than young drivers to be responsible. Young males were more likely than young females to be responsible for crash deaths, whereas females in their 50s and older were more likely than same-age males to be responsible. In terms of responsibility for deaths per licensed driver, young drivers, especially males, had the highest rates because of their high involvement rates and high responsibility rates. The majority of deaths for which young drivers were responsible occurred to people other than themselves, especially passengers in their vehicles, whereas the bulk of the deaths for which older drivers were responsible were their own. Discussion: The results highlight the contribution of young drivers to the motor-vehicle crash problem, the need for measures such as passenger restrictions in graduated licensing systems, and the need for vehicle modifications to better protect older occupants.     

Weather impacts on single-vehicle truck crash injury severity

IntroductionThe focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes.MethodRandom parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity.Results and conclusionsResults showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity.Practical applicationsThe research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

Do NHTSA vehicle safety ratings affect side impact crash outcomes?

Introduction: Side impact crash injuries tend to be severe, mainly due to the effects of the mechanism of such crashes. This study addresses the relationship between side impact crash injury severities and side impact safety ratings of the passenger cars involved in such crashes. It is motivated by the lack of research on side impact safety ratings in relation to the real-world crash outcomes. Method: Analysis of Crashworthiness Data System’s (CDS) data show the head and thorax are the most common regions of impact of severe injuries, while the neck is the least. Irrespective of body regions, higher-rated vehicles were found to provide better occupant protection to both younger and older driver age groups. Assessment based on injury severity score (ISS) indicates that higher-rated vehicles have an overall lower average ISS compared to lower-rated vehicles. Results: Ultimately, this study shows that vehicles rated with National Highway Traffic Safety Administration’s (NHTSA) new criteria had lower average ISS compared to vehicles rated under the old criteria. The 2011 NHTSA side impact rating criteria being relatively new, it has very few crashes to draw meaningful statistically significant conclusions. However, this paper establishes the fact that vehicles with higher star ratings (under experimental conditions) indeed offer increased occupant protection in the field conditions. Practical applications: Previous studies have found that safety was given priority while buying new vehicles. However, people associated vehicle safety with technologies and specific safety features rather than the vehicle’s crash test results or ratings (Koppel, Charlton, Fildes, & Fitzharris, 2008). The results from this study provide a point of reference for safety advocates to educate the drivers about the importance of considering vehicle safety ratings during a vehicle purchase.     

Hierarchical ordered model for injury severity of pedestrian crashes in South Korea

Introduction: The high percentage of fatalities in pedestrian-involved crashes is a critical social problem. The purpose of this study is to investigate factors influencing injury severity in pedestrian crashes by examining the demographic and socioeconomic characteristics of the regions where crashes occurred. Method: To understand the correlation between the unobserved characteristics of pedestrian crashes in a defined region, we apply a hierarchical ordered model, in which we set crash characteristics as lower-level variables and municipality characteristics as upper-level. Pedestrian crash data were collected and analyzed for a three-year period from 2011 to 2013. The estimation results show the statistically significant factors that increase injury severity of pedestrian crashes. Results: At the crash level, the factors associated with increased severity of pedestrian injury include intoxicated drivers, road-crossing pedestrians, elderly pedestrians, heavy vehicles, wide roads, darkness, and fog. At the municipality level, municipalities with low population density, lower level of financial independence, fewer doctors, and a higher percentage of elderly residents experience more severe pedestrian crashes. Municipalities ranked as having the top 10% pedestrian fatality rate (fatalities per 100,000 residents) have rates 7.4 times higher than municipalities with the lowest 10% rate of fatalities. Their demographic and socioeconomic characteristics also have significant differences. The proposed model accounts for a 7% unexplained variation in injury severity outcomes between the municipalities where crashes occurred. Conclusion: To enhance the safety of vulnerable pedestrians, considerable investments of time and effort in pedestrian safety facilities and zones should be made. More certain and severe punishments should be also given for the traffic violations that increase injury severity of pedestrian crashes. Furthermore, central and local governments should play a cooperative role to reduce pedestrian fatalities. Practical applications: Based on our study results, we suggest policy directions to enhance pedestrian safety.     

Effect of vehicle and crash factors on older occupants

PROBLEM: The expected substantial increase in people aged 65 or older is important for those concerned about transportation injuries. However, much of the previous research concentrates on older drivers and overlooks the fact that vehicle and crash factors may provide significant explanations of older occupant injury rates. METHOD: Differences across age groups are explored using two nationwide travel surveys, crash involvement, fatalities, and injuries from crash databases and an ordered probit model of injury severity. RESULTS AND DISCUSSION: Two noticeable differences that help explain injury risk are that older people are more likely to travel in passenger cars than younger people who frequently use light trucks, and that seriously injured older occupants are more likely to be involved in side-impact crashes than their younger counterparts. IMPACT: Increased attention to vehicle engagement in side-impact crashes and to vehicle technologies that can help drivers avoid side collisions would be particularly helpful for older occupants.     

Assessment of temporal stability in risk factors of crashes at horizontal curves on rural two-lane undivided highways

Introduction: Safety of horizontal curves on rural two-lane, two-way undivided roadways is not fully explored. This study investigates factors that impact injury severity of such crashes. Method: To achieve the aim of this paper, issues associated with police-reported crash data such as unobserved heterogeneity and temporal stability need to be accounted for. Hence, a mixed logit model was estimated, while heterogeneity in means and variances is investigated by considering four injury severity outcomes for drivers: severe injury, moderate injury, possible injury, and no injury. Crash data for the period between 2011 and 2016 for crashes that occurred in the state of Oregon was analyzed. Temporal stability in factors determining the injury severity was investigated by identifying three time periods through splitting crash data into 2011–2012, 2013–2014, and 2015–2016. Results: Despite some factors affecting injuries in all specified time periods, the values of the marginal effects showed relative differences. The estimation results revealed that some factors increased the risk of being involved in severe injury crashes, including head-on collisions, drunk drivers, failure to negotiate curves, older drivers, and exceeding the speed limits. Conclusions: The hypothesis that attributes of injury severity are temporally stable is rejected. For example, young drivers (30 years old and younger) and middle-aged drivers were found to be temporally instable over time. Practical applications: The findings could help transportation authorities and safety professionals to enhance the safety of horizontal curves through appropriate and effective countermeasures.     

Crash histories,safety perceptions,and attitudes among Virginia bicyclists

IntroductionCycling injury and fatality rates are on the rise, yet there exists no comprehensive database for bicycle crash injury data.MethodWidely used for safety analysis, police crash report datasets are automobile-oriented and widely known to under-report bicycle crashes. This research is one attempt to address gaps in bicycle data in sources like police crash reports. A survey was developed and deployed to enhance the quality and quantity of available bicycle safety data in Virginia. The survey captures bicyclist attitudes and perceptions of safety as well as bicycle crash histories of respondents.ResultsThe results of this survey most notably show very high levels of under-reporting of bicycle crashes, with only 12% of the crashes recorded in this survey reported to police. Additionally, the results of this work show that lack of knowledge concerning bicycle laws is associated with lower levels of cycling confidence. Count model results predict that bicyclists who stop completely at traffic signals are 40% less likely to be involved in crashes compared to counterparts who sometimes stop at signals. In this dataset, suburban and urban roads with designated bike lanes had more favorable injury severity profiles, with lower percentages of severe and minor injury crashes compared to similar roads with a shared bike/automobile lane or no designated bike infrastructure.     

Contributing factors of crash injury severity at public highway-railroad grade crossings in the U.S.

IntroductionThe Moving Ahead for Progress in the 21st Century (MAP-21) includes a separate program that supports safety improvements to reduce the number of fatalities and injuries at public highway-railroad grade crossings (HRGCs). This study identifies the significant factors affecting crash injury severity at public HRGCs in the United States.MethodCrashes from 2009 through 2013 on 5,528 public HRGCs, extracted from the Federal Railroad Administration database, were used in the analysis. A comprehensive list of risk factors was explored. Examples include predictors related to geographic region of crash, geometry (e.g., area type and pavement marking type), railroad (e.g., warning device type and railroad class), traffic (e.g., train speed and vehicles annual average daily traffic “AADT”), highway user (e.g., driver age and gender), and environment (e.g., lighting and weather conditions). The study used the mixed logit model to better capture the complex highway user behavior at HRGCs.ResultsFemale highway users were at higher risk of involvement in injuries and fatalities compared to males. Higher train speeds, very old drivers, open areas, concrete road surface types, and railroad equipment striking highway users before crash, were all found to increase the injury likelihood. On the other hand, young and middle-age drivers, non-passing of standing vehicles at HRGCs, industrial areas, and presence of warning bells were found to reduce injuries and fatalities.ConclusionsThe mixed logit model succeeded in identifying contributing factors of crash severity at public HRGCs and potential countermeasures to reduce both fatalities and injuries are suggested.Practical applicationsIt is important to install warning bells at public HRGCs, especially at those with high number of injury and fatality crashes. Enforcement of traffic nearby HRGCs is necessary to prevent vehicles from overtaking of standing vehicles.     

Associations of distraction involvement and age with driver injury severities

IntroductionThis paper investigates the associations between the severity of injuries sustained by a driver who is involved in a two-vehicle crash, the existence and type of driver distraction as well as driver's age. Few studies investigated distraction as it relates to injury severity. Moreover, these studies did not consider driver age which is a significant factor related to driving behavior and the ability to respond in a crash situation.MethodsAn ordered logit model was built to predict injury severity sustained by drivers using data from the U.S. National Automotive Sampling System's General Estimates System (2003 to 2008). Various factors (e.g., weather, gender, and speeding) were statistically controlled for, but the main focus was on the interaction of driver age and distraction type.ResultsThe trends observed for young and mid-age drivers were similar. For these age groups, dialing or texting on the cell phone, passengers, and in-vehicle sources resulted in an increase in a likelihood of more severe injuries. Talking on the cell phone had a similar effect for younger drivers but was not significant for mid-age drivers. Inattention and distractions outside the vehicle decreased the odds of severe injuries. For older drivers, the highest odds of severe injuries were observed with dialing or texting on a cell phone, followed by in-vehicle sources and talking on the cell phone. All these sources were associated with an increased likelihood of injury severity. Similar to young and mid-age drivers, distractions outside the vehicle decreased the odds of severe injuries. Other distraction types did not have a significant effect for the older age group.ConclusionsThe results support previous literature and extend our understanding of crash injury severity.Practical applicationsThe findings have implications for policy making and the design of distraction mitigation systems.     

Fatal crashes involving large numbers of vehicles and weather

IntroductionAdverse weather has been recognized as a significant threat to traffic safety. However, relationships between fatal crashes involving large numbers of vehicles and weather are rarely studied according to the low occurrence of crashes involving large numbers of vehicles.MethodBy using all 1,513,792 fatal crashes in the Fatality Analysis Reporting System (FARS) data, 1975–2014, we successfully described these relationships.ResultsWe found: (a) fatal crashes involving more than 35 vehicles are most likely to occur in snow or fog; (b) fatal crashes in rain are three times as likely to involve 10 or more vehicles as fatal crashes in good weather; (c) fatal crashes in snow [or fog] are 24 times [35 times] as likely to involve 10 or more vehicles as fatal crashes in good weather. If the example had used 20 vehicles, the risk ratios would be 6 for rain, 158 for snow, and 171 for fog.ConclusionsTo reduce the risk of involvement in fatal crashes with large numbers of vehicles, drivers should slow down more than they currently do under adverse weather conditions. Driver deaths per fatal crash increase slowly with increasing numbers of involved vehicles when it is snowing or raining, but more steeply when clear or foggy.Practical applicationsWe conclude that in order to reduce risk of involvement in crashes involving large numbers of vehicles, drivers must reduce speed in fog, and in snow or rain, reduce speed by even more than they already do.     

Injury Outcome in Crashes with Guardrail End Terminals

Objective: The goal of this study is to evaluate the crash performance of guardrail end terminals in real-world crashes. Guardrail end terminals are installed at the ends of guardrail systems to prevent the rail from spearing through the car in an end-on collision. Recently, there has been a great deal of controversy as to the safety of certain widely used end terminal designs, partly because there is surprisingly little real-world crash data for end terminals. Most existing studies of end terminal crashes used data from prior to the mid-1990s. Since then, there have been large improvements to vehicle crashworthiness and seat belt usage rates, as well as new roadside safety hardware compliant with National Cooperative Highway Research Program (NCHRP) Report 350, “Recommended Procedures for the Safety Performance Evaluation of Highway Features.” Additionally, most existing studies of injury in end terminal crashes do not account for factors such as the occurrence of rollover. This analysis uses more recent crash data that represent post-1990s vehicle fleet changes and account for a number of factors that may affect driver injury outcome and rollover occurrence.

Methods: Passenger vehicle crashes coded as involving guardrail end terminals were identified in the set of police-reported crashes in Michigan in 2011 and 2012. End terminal performance was expected to be a function of end terminal system design. State crash databases generally do not identify specific end terminal systems. In this study, the coded crash location was used to obtain photographs of the crash site prior to the crash from Google Street View. These site photographs were manually inspected to identify the particular end terminal system involved in the crash. Multiple logistic regression was used to test for significant differences in the odds of driver injury and rollover between different terminal types while accounting for other factors.

Results: A total of 1,001 end terminal crashes from the 2011–2012 Michigan State crash data were manually inspected to identify the terminal that had been struck. Four hundred fifty-one crashes were found to be suitable for analysis. Serious to fatal driver injury occurred in 3.8% of end terminal crashes, moderate to fatal driver injury occurred in 11.8%, and 72.3% involved property damage only. No significant difference in moderate to fatal driver injury odds was observed between NCHRP 350 compliant end terminals and noncompliant terminals. Car drivers showed odds of moderate to fatal injury 3.6 times greater than LTV drivers in end terminal crashes. Rollover occurrence was not significantly associated with end terminal type.

Conclusions: Car drivers have greater potential for injury in end terminal crashes than light truck/van/sport utility vehicle drivers. End terminal designs compliant with NCHRP 350 did not appear to carry different odds of moderate driver injury than noncompliant end terminals. The findings account for driver seat belt use, rollover occurrence, terminal orientation (leading/trailing), control loss, and the number of impact events. Rollover and nonuse of seat belts carried much larger increases in injury potential than end terminal type. Rollover did not appear to be associated with NCHRP 350 compliance.     

Safety performance evaluation of cable median barriers on freeways in Florida

Objective: This article aims to evaluate the safety performance of cable median barriers on freeways in Florida.

Method: The safety performance evaluation was based on the percentages of barrier and median crossovers by vehicle type, crash severity, and cable median barrier type (Trinity Cable Safety System [CASS] and Gibraltar system). Twenty-three locations with cable median barriers totaling about 101 miles were identified. Police reports of 6,524 crashes from years 2005–2010 at these locations were reviewed to verify and obtain detailed crash information. A total of 549 crashes were determined to be barrier related (i.e., crashes involving vehicles hitting the cable median barrier) and were reviewed in further detail to identify crossover crashes and the manner in which the vehicles crossed the barriers; that is, by either overriding, underriding, or penetrating the barriers.

Results: Overall, 2.6% of vehicles that hit the cable median barrier crossed the median and traversed into the opposite travel lane. Overall, 98.1% of cars and 95.5% of light trucks that hit the barrier were prevented from crossing the median. In other words, 1.9% of cars and 4.5% of light trucks that hit the barrier had crossed the median and encroached on the opposite travel lanes. There is no significant difference in the performance of cable median barrier for cars versus light trucks in terms of crossover crashes. In terms of severity, overrides were more severe compared to underrides and penetrations. The statistics showed that the CASS and Gibraltar systems performed similarly in terms of crossover crashes. However, the Gibraltar system experienced a higher proportion of penetrations compared to the CASS system. The CASS system resulted in a slightly higher percentage of moderate and minor injury crashes compared to the Gibraltar system.

Conclusions: Cable median barriers are successful in preventing median crossover crashes; 97.4% of the cable median barrier crashes were prevented from crossing over the median. Of all of the vehicles that hit the barrier, 83.6% were either redirected or contained by the cable barrier system. Barrier crossover crashes were found to be more severe compared to barrier noncrossover crashes. In addition, overrides were found to be more severe compared to underrides and penetrations.     

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.