Characteristics of animal-related motor vehicle crashes in select National Park Service units—United States, 1990–2013

Objectives: Nationally, animal–motor vehicle crashes (AVCs) account for 4.4% of all types of motor vehicle crashes (MVCs). AVCs are a safety risk for drivers and animals and many National Park Service (NPS) units (e.g., national park, national monument, or national parkway) have known AVC risk factors, including rural locations and substantial animal densities. We sought to describe conditions and circumstances involving AVCs to guide traffic and wildlife management for prevention of AVCs in select NPS units.

Methods: We conducted an analysis using NPS law enforcement MVC data. An MVC is a collision involving an in-transit motor vehicle that occurred or began on a public roadway. An AVC is characterized as a collision between a motor vehicle and an animal. A non-AVC is a crash between a motor vehicle and any object other than an animal or noncollision event (e.g., rollover crash). The final data for analysis included 54,068 records from 51 NPS units during 1990–2013. Counts and proportions were calculated for categorical variables and medians and ranges were calculated for continuous variables. We used Pearson’s chi-square to compare circumstances of AVCs and non-AVCs. Data were compiled at the park regional level; NPS parks are assigned to 1 of 7 regions based on the park’s location.

Results: AVCs accounted for 10.4% (5,643 of 54,068) of all MVCs from 51 NPS units. The Northeast (2,021 of 5,643; 35.8%) and Intermountain (1,180 of 5,643; 20.9%) regions had the largest percentage of the total AVC burden. November was the peak month for AVCs across all regions (881 of 5,643; 15.6%); however, seasonality varied by park geographic regions. The highest counts of AVCs were reported during fall for the National Capital, Northeast/Southeast, and Northeast regions; winter for the Southeast region; and summer for Intermountain and Pacific West regions.

Conclusions: AVCs represent a public health and wildlife safety concern for NPS units. AVCs in select NPS units were approximately 2-fold higher than the national percentage for AVCs. The peak season for AVCs varied by NPS region. Knowledge of region-specific seasonality patterns for AVCs can help NPS staff develop mitigation strategies for use primarily during peak AVC months. Improving AVC data collection might provide NPS with a more complete understanding of risk factors and seasonal trends for specific NPS units. By collecting information concerning the animal species hit, park managers can better understand the impacts of AVC to wildlife population health.     

Trends and characteristics of animal-vehicle collisions in the United States

Introduction

Since 1990, fatal animal-vehicle collisions (AVCs) in the United States have more than doubled. This paper examines annual AVC trends in the United States over a 19-year period, seasonal and diurnal patterns of AVC risk, the geographic distribution of crash risk by state, and the association between posted speed limit and AVC crash risk in darkness.

Method

AVCs were compiled from the Fatality Analysis Reporting System (FARS) and the General Estimates System (GES) for the years 1990-2008 to examine annual crash trends for fatal and nonfatal crashes. Seasonal trends for fatal AVCs were examined with the aggregated FARS dataset; seasonal trends for fatal and nonfatal AVCs were also examined by aggregating four years of Michigan crash data. State-by-state distributions of fatal AVCs were also described with the aggregated FARS dataset. Finally, the relationship between posted speed limit and the odds that a fatal or nonfatal AVC occurred in darkness were examined with logistic regressions using the aggregated FARS and Michigan datasets.

Results

Between 1990 and 2008, fatal AVCs increased by 104% and by 1.3 crashes per trillion vehicle miles travelled per year. Although not all AVCs involve deer, daily and seasonal AVC crash trends follow the general activity pattern of deer populations, consistent with prior reports. The odds that a fatal AVC occurred in darkness were also found to increase by 2.3% for each mile-per-hour increase in speed; a similar, albeit smaller, effect was also observed in the aggregated Michigan dataset, among nonfatal crashes.

Conclusion

AVCs represent a small but increasing share of crashes in the United States. Seasonal and daily variation in the pattern of AVCs seem to follow variation in deer exposure and ambient light level. Finally, the relative risk that a fatal and nonfatal AVC occurred in darkness is influenced by posted speed limit, suggesting that a driver's limited forward vision at night plays a role in AVCs, as it does in pedestrian collisions.

Impact on Industry

The association between speed limit and crash risk in darkness suggests that AVC risk might be reduced with countermeasures that improve a driver's forward view of the road.     

Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study

Problem: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. Methods: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. Results: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. Summary: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.     

Crash risk by driver age,gender, and time of day using a new exposure methodology

Introduction: Concerns have been raised that the nonlinear relation between crashes and travel exposure invalidates the conventional use of crash rates to control for exposure. A new metric of exposure that bears a linear association to crashes was used as basis for calculating unbiased crash risks. This study compared the two methods – conventional crash rates and new adjusted crash risk – for assessing the effect of driver age, gender, and time of day on the risk of crash involvement and crash fatality. Method: We used police reports of single-car and multi-car crashes with fatal and nonfatal driver injuries that occurred during 2002–2012 in Great Britain. Results: Conventional crash rates were highest in the youngest age group and declined steeply until age 60–69 years. The adjusted crash risk instead peaked at age 21–29 years and reduced gradually with age. The risk of nighttime driving, especially among teenage drivers, was much smaller when based on adjusted crash risks. Finally, the adjusted fatality risk incurred by elderly drivers remained constant across time of day, suggesting that their risk of sustaining a fatal injury due to a crash is more attributable to excess fragility than to crash seriousness. Conclusions: Our findings demonstrate a biasing effect of low travel exposure on conventional crash rates. This implies that conventional methods do not yield meaningful comparisons of crash risk between driver groups and driving conditions of varying exposure to risk. The excess crash rates typically associated with teenage and elderly drivers as well as nighttime driving are attributed in part to overestimation of risk at low travel exposure. Practical Applications: Greater attention should be directed toward crash involvement among drivers in their 20s and 30s as well as younger drivers. Countermeasures should focus on the role of physical vulnerability in fatality risk of elderly drivers.     

First year as a licensed car driver: Gender differences in crash experience

Objective: To explore the crash experience and crash consequences of newly licensed male and female drivers aged 18–29 years.Methodology: A national register-based population cohort of persons born between 1970 and 1972 was followed for the period 1988–2000 on the basis of crash data in Swedish police records. The analyses focused on two crash categories regardless of consequences: single car (SC) and car-to-motor vehicle (CMV).Results: Crash incidence for men was nearly double that of women in all age groups in both crash categories. Age had a protective effect for both sexes, especially for SC crashes. Males, but not females, showed a lag in time from driving license issue date to first crash for SC crashes, which increased with age of obtaining a license. Men’s crash fatality rate was five times higher than that of women for SC crashes (32.2 and 6.1 per 1000, respectively), but the rate was comparable for CMV crashes (16.1 and 15.7, respectively). The crash morbidity rate was 25–30% higher for male drivers in both crash categories.Conclusions: Both young age and male sex emerge as important determinants of crash risk and crash consequences among young Swedish drivers.     

An Analysis of Young Driver Crash Types and the Associated Lifetime Care Cost in Victoria,Australia

Objective: The elevated crash involvement rate of young drivers is well documented. Given the higher crash risk of young drivers and the need for innovative policy and programs, it remains important to fully understand the type of crashes young drivers are involved in, and knowledge of the lifetime care cost of crashes can support effective policy development. The aim of this article is to document the number and type of young driver crashes, as well as the associated lifetime care cost over a 9-year period (2005–2013) in Victoria, Australia.

Methods: In Victoria, Australia, the Transport Accident Commission (TAC) has legislated responsibility for road safety and the care of persons injured in road crashes, irrespective of fault. TAC claims data for the period 2005–2013 were used to document the number and type of young driver crashes. Lifetime care costs (past and future payment liabilities) were calculated by Taylor Fry actuarial consultancy. License and population data were used to define the crash involvement rate of young drivers.

Results: Over the 9-year period, 16,817 claims were lodged to the TAC by drivers 18–25 years of age following a crash. There were 646 fewer drivers aged 18–25 killed and injured in 2013, compared to 2005, representing an unadjusted change of ?28.7% (?29.8% males; ?28.4% females). The total lifetime care cost of young drivers killed and injured in Victoria for the period 2005–2013 was estimated to be AU$634 million (US$493 million). Differences between males and females, single- and multivehicle crashes, and fatalities and injuries were found to be statistically significant. Run-off-road crashes and crashes from opposing direction were overrepresented in the lifetime care costs for young driver claimants. Twenty-eight injured drivers were classified as high-severity claims. These 28 claimants require additional long-term care, which was estimated to be AU$219 million; of these 28, 24 were male (85.7%). The long-term care costs for these 28 drivers (0.16%) accounts for 34.5% of the total lifetime care cost of all 18- to 25-year-old injured drivers.

Conclusions: By using no-fault lifetime care costs that account for medical and like expenses, rehabilitation, and social reintegration costs, a more accurate understanding of the cost of young driver crashes can be determined. Application of these costs to specific crash types highlights new priorities and opportunities for developing programs to reduce young driver crashes.     

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.     

Ability to monitor driving under the influence of marijuana among non-fatal motor-vehicle crashes: An evaluation of the Colorado electronic accident reporting system

Introduction: As more states legalize medical/recreational marijuana use, it is important to determine if state motor-vehicle surveillance systems can effectively monitor and track driving under the influence (DUI) of marijuana. This study assessed Colorado's Department of Revenue motor-vehicle crash data system, Electronic Accident Reporting System (EARS), to monitor non-fatal crashes involving driving under the influence (DUI) of marijuana. Methods: Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to assess EARS' usefulness, flexibility, timeliness, simplicity, acceptability, and data quality. We assessed system components, interviewed key stakeholders, and analyzed completeness of Colorado statewide 2014 motor-vehicle crash records. Results: EARS contains timely and complete data, but does not effectively monitor non-fatal motor-vehicle crashes related to DUI of marijuana. Information on biological sample type collected from drivers and toxicology results were not recorded into EARS; however, EARS is a flexible system that can incorporate new data without increasing surveillance system burden. Conclusions: States, including Colorado, could consider standardization of drug testing and mandatory reporting policies for drivers involved in motor-vehicle crashes and proactively address the narrow window of time for sample collection to improve DUI of marijuana surveillance. Practical applications: The evaluation of state motor-vehicle crash systems' ability to capture crashes involving drug impaired driving (DUID) is a critical first step for identifying frequency and risk factors for crashes related to DUID.     

Continued trends in older driver crash involvement rates in the United States: Data through 2017–2018

Introduction: With the growing older adult population due to the aging baby-boom cohort, there was concern that increases in fatal motor-vehicle crashes would follow. Yet, previous analyses showed this to be untrue. The purpose of this study was to examine current trends to determine if previous declines have persisted or risen with the recent increase in fatalities nationwide. Methods: Trends among drivers ages 70 and older were compared with drivers 35–54 for U.S. passenger vehicle fatal crash involvements per 100,000 licensed drivers from 1997 to 2018, fatal and all police-reported crash involvements per vehicle miles traveled using the 1995, 2001, 2009, and 2017 National Household Travel Surveys, and driver deaths per 1,000 crashes. Results: Since the mid-1990s, fatal crashes per licensed driver trended downward, with greater declines for drivers ages 70 and older than for middle-aged drivers (43% vs. 21%). Fatal crash rates per 100,000 licensed drivers and police-reported crash rates per mile traveled for drivers ages 70–79 are now less than those for drivers ages 35–54, but their fatal crash rates per mile traveled and risk of dying in a crash remain higher as they drive fewer miles. As the economy improved over the past decade, fatal crash rates increased substantially for middle-aged drivers but decreased or remained stable among older driver age groups. Conclusions: Fatal crash involvements for adults ages 70 and older has recently increased, but they remain down from their 1997 peak, even as the number of licensed older drivers and the miles they drive have increased. Health improvements likely contributed to long-term reductions in fatal crash rates. As older drivers adopt vehicles with improved crashworthiness and safety features, crash survivability will improve. Practical Application: Older adults should feel confident that their independent mobility needs pose less risk than previously expected.     

Investigation of crashes at pedestrian hybrid beacons: Results of a large-scale study in Arizona

Introduction: The pedestrian hybrid beacon (PHB) is a traffic control device used at pedestrian crossings. A recent Arizona Department of Transportation research effort investigated changes in crashes for different severity levels and crash types (e.g., rear-end crashes) due to the PHB presence, as well as for crashes involving pedestrians and bicycles. Method: Two types of methodologies were used to evaluate the safety of PHBs: (a) an Empirical Bayes (EB) before-after study, and (b) a long-term cross-sectional observational study. For the EB before-after evaluation, the research team considered three reference groups: unsignalized intersections, signalized intersections, and both unsignalized and signalized intersections combined. Results: For the signalized and combined unsignalized and signalized intersection groups, all crash types considered showed statistically significant reductions in crashes (e.g., total crashes, fatal and injury crashes, rear-end crashes, fatal and injury rear-end crashes, angle crashes, fatal and injury angle crashes, pedestrian-related crashes, and fatal and injury pedestrian-related crashes). A cross-sectional study was conducted with a larger number of PHBs (186) to identify relationships between roadway characteristics and crashes at PHBs, especially with respect to the distance to an adjacent traffic control signal. The distance to an adjacent traffic signal was found to be significant only at the α = 0.1 level, and only for rear-end and fatal and injury rear-end crashes. Conclusions: This analysis represents the largest known study to date on the safety impacts of PHBs, along with a focus on how crossing and geometric characteristics affect crash patterns. The study showed the safety benefits of PHBs for both pedestrians and vehicles. Practical Applications: The findings from this study clearly support the installation of PHBs at midblock or intersection crossings, as well as at crossings on higher-speed roads.     

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.     

Prediction of responsibility for drivers and riders involved in injury road crashes

Introduction: Responsibility analysis allows the evaluation of crash risk factors from crash data only, but requires a reliable responsibility assessment. The aim of the present study is to predict expert responsibility attribution (considered as a gold-standard) from explanatory variables available in crash data routinely recorded by the police, according to a data-driven process with explicit rules. Method: Driver responsibility was assessed by experts using all information contained in police reports for a sample of about 5000 injury crashes that occurred in France in 2011. Three statistical methods were used to predict expert responsibility attribution: logistic regression with L1 penalty, random forests, and boosting. Potential predictors of expert attribution referred to inappropriate driver actions and to external conditions at the time of the crash. Logistic regression was chosen to construct a score to assess responsibility for drivers and riders in crashes involving one or more motor vehicles, or involving a cyclist or pedestrian. Results: Cross-validation showed that our tool can predict expert responsibility assessments on new data sets. In addition, responsibility analyses performed using either the expert responsibility or our predicted responsibility return similar odds ratios. Our scoring process can then be used to reliably assess responsibility based on national police report databases, provided that they include the information needed to construct the score.     

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.     

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.     

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.     

The interactive effect on injury severity of driver-vehicle units in two-vehicle crashes

IntroductionThis study sets out to investigate the interactive effect on injury severity of driver-vehicle units in two-vehicle crashes.MethodA Bayesian hierarchical ordered logit model is proposed to relate the variation and correlation of injury severity of drivers involved in two-vehicle crashes to the factors of both driver-vehicle units and the crash configurations. A total of 6417 crash records with 12,834 vehicles involved in Florida are used for model calibration.ResultsThe results show that older, female and not-at-fault drivers and those without use of safety equipment are more likely to be injured but less likely to injure the drivers in the other vehicles. New vehicles and lower speed ratios are associated with lower injury degree of both drivers involved. Compared with automobiles, vans, pick-ups, light trucks, median trucks, and heavy trucks possess better self-protection and stronger aggressivity. The points of impact closer to the driver's seat in general indicate a higher risk to the own drivers while engine cover and vehicle rear are the least hazardous to other drivers. Head-on crashes are significantly more severe than angle and rear-end crashes. We found that more severe crashes occurred on roadways than on shoulders or safety zones.ConclusionsBased on these results, some suggestions for traffic safety education, enforcement and engineering are made. Moreover, significant within-crash correlation is found in the crash data, which demonstrates the applicability of the proposed model.     

Fatal pedestrian crashes on interstates and other freeways in the United States

Introduction: More than 800 pedestrians die annually in crashes on interstates and other freeways in the United States, but few studies have examined their characteristics. Method: Data from the Fatality Analysis Reporting System on pedestrians fatally injured during 2015–2017 were analyzed. Chi-square tests compared characteristics of pedestrians killed on interstates and other freeways with those that died on other roads, and across crash types among freeway deaths. Land use characteristics of locations where pedestrians were killed while crossing freeways in a large state (California) were identified using Google Earth. Results: A larger proportion of pedestrians killed on freeways died on dark and unlit roads (48% vs. 32%), were male (78% vs. 68%), or were ages 20–44 (55% vs. 32%) compared with pedestrians killed on other roads. Crossing (42%) was the most common crash type among pedestrian deaths on freeways, followed by disabled-vehicle-related crashes (18%). Pedestrians who died while crossing more often had blood alcohol concentrations ≥ 0.08 g/dL (40%) than those in disabled-vehicle-related (22%) or other crashes (34%). Deaths in crossing crashes were more likely than other freeway deaths to occur on urban roads (81%), at speed limits ≤50 mph (13%), or between 18:00 and 23:59 (49%), and 58% of crossing crashes analyzed for land use were located between residential and other (e.g., commercial, recreational) uses. Over a third (37%) of deaths in disabled-vehicle-related crashes occurred at speed limits ≥70 mph. Conclusions: A surprising proportion of pedestrian deaths occur on controlled-access roads not designed for walking. Countermeasures for these crashes need to be implemented to see meaningful reductions in pedestrian fatalities overall. Practical applications: Improving roadway and vehicle lighting, requiring reflective warning devices for marking disabled vehicles, constructing pedestrian overpasses and underpasses in areas frequently crossed, and promoting alternative means of traveling between residential and commercial areas could help.     

Understanding crash potential associated with teen driving: Survey analysis using multivariate graphical method

Introduction: Teen crash involvement is usually higher than other age groups, and they are typically overrepresented in car crashes. To infer teen drivers' understanding of crash potentials (factors that are associated with crash occurrence), two sources of data are generally used: retrospective data and prospective data. Retrospective data sources contain historical crash data, which have limitations in determining teen drivers' knowledge of crash potentials. Prospective data sources, like surveys, have more potential to minimize the research gap. Prior studies have shown that teen drivers are more likely to be involved in crashes during their early driving years. Thus, there is a benefit in examining how teen drivers' understanding of crash potentials change during their transition through licensing stages (i.e., no licensure to unrestricted licensure). Method: This study used a large set of teen driver survey data (a dataset from approximately 88,000 respondents) of Texas teens to answer the research question. Researchers provided rankings of the crash potentials by gender and licensure stages using a multivariate graphical method named taxicab correspondence analysis (TCA). Results: The findings show that driving behavior and understanding of crash potentials differ among teens based upon various licensing stages. Practical applications: Findings from this study can help government authorities to refine policies of teen driver licensing and implement potential countermeasures for safety improvement.