Traffic environment and demographic factors affecting impaired driving and crashes

IntroductionData availability has forced researchers to examine separately the role of alcohol among drivers who crashed and drivers who did not crash. Such a separation fails to account fully for the transition from impaired driving to an alcohol-related crash.MethodIn this study, we analyzed recent data to investigate how traffic-related environments, conditions, and drivers’ demographics shape the likelihood of a driver being either involved in a crash (alcohol impaired or not) or not involved in a crash (alcohol impaired or not). Our data, from a recent case–control study, included a comprehensive sampling of the drivers in nonfatal crashes and a matched set of comparison drivers in two U.S. locations. Multinomial logistic regression was applied to investigate the likelihood that a driver would crash or would not crash, either with a blood alcohol concentration (BAC) = .00 or with a BAC ≥ .05.ConclusionsTo our knowledge, this study is the first to examine how different driver characteristics and environmental factors simultaneously contribute to alcohol use by crash-involved and non-crash-involved drivers. This effort calls attention to the need for research on the simultaneous roles played by all the factors that may contribute to motor vehicle crashes.     

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.     

Analysis of Driver Evasive Maneuvering Prior to Intersection Crashes Using Event Data Recorders

Objective: Intersection crashes account for over 4,500 fatalities in the United States each year. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that have the potential to help drivers safely navigate across intersections and prevent intersection crashes and injuries. The performance of an I-ADAS is expected to be highly dependent upon driver evasive maneuvering prior to an intersection crash. Little has been published, however, on the detailed evasive kinematics followed by drivers prior to real-world intersection crashes. The objective of this study was to characterize the frequency, timing, and kinematics of driver evasive maneuvers prior to intersection crashes.

Methods: Event data recorders (EDRs) downloaded from vehicles involved in intersection crashes were investigated as part of NASS-CDS years 2001 to 2013. A total of 135 EDRs with precrash vehicle speed and braking application were downloaded to investigate evasive braking. A smaller subset of 59 EDRs that collected vehicle yaw rate was additionally analyzed to investigate evasive steering. Each vehicle was assigned to one of 3 precrash movement classifiers (traveling through the intersection, completely stopped, or rolling stop) based on the vehicle's calculated acceleration and observed velocity profile. To ensure that any significant steering input observed was an attempted evasive maneuver, the analysis excluded vehicles at intersections that were turning, driving on a curved road, or performing a lane change. Braking application at the last EDR-recorded time point was assumed to indicate evasive braking. A vehicle yaw rate greater than 4° per second was assumed to indicate an evasive steering maneuver.

Results: Drivers executed crash avoidance maneuvers in four-fifths of intersection crashes. A more detailed analysis of evasive braking frequency by precrash maneuver revealed that drivers performing complete or rolling stops (61.3%) braked less often than drivers traveling through the intersection without yielding (79.0%). After accounting for uncertainty in the timing of braking and steering data, the median evasive braking time was found to be between 0.5 to 1.5 s prior to impact, and the median initial evasive steering time was found to occur between 0.5 and 0.9 s prior to impact. The median average evasive braking deceleration for all cases was found to be 0.58 g. The median of the maximum evasive vehicle yaw rates was found to be 8.2° per second. Evasive steering direction was found to be most frequently in the direction of travel of the approaching vehicle.

Conclusions: The majority of drivers involved in intersection crashes were alert enough to perform an evasive action. Most drivers used a combination of steering and braking to avoid a crash. The average driver attempted to steer and brake at approximately the same time prior to the crash.     

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.     

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.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Preventing highway crashes by raising the legal minimum age for drinking: The Michigan experience 6 years later

Results of a 6-year follow-up of previous research evaluating the effects of Michigan's December 1978 increase in the legal drinking age from 18 to 21 are reported. Earlier research demonstrated the immediate effect of Michigan's raised legal age in reducing motor vehicle crash involvement among young drivers. The current study examined 6 years of post-law traffic crash data, using Box-Jenkins intervention analysis methods to assess the long-term effects of the raised drinking age. Results revealed long-term ef- fects of the law similar to the initial effects identified earlier. Over the 6-year follow-up period, the rate of involvement in injury-producing single-vehicle nighttime crashes among drivers age 18–20 was 16 % lower than the level ex- pected, had the drinking age law not changed. Police-reported drinking driver crash involvement was down 19%. In contrast to many alcohol-im- paired driving countermeasures, the raised legal drinking age appears to have a long-term effect in reducing motor vehicle crash involvement among young drivers.     

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.     

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.     

Validation of quasi-induced exposure representativeness assumption among young drivers

Objective: Young driver studies have applied quasi-induced exposure (QIE) methods to assess relationships between demographic and behavioral factors and at-fault crash involvement, but QIE's primary assumption of representativeness has not yet been validated among young drivers. Determining whether nonresponsible young drivers in clean (i.e., only one driver is responsible) 2-vehicle crashes are reasonably representative of the general young driving population is an important step toward ensuring valid QIE use in young driver studies. We applied previously established validation methods to conduct the first study, to our knowledge, focused on validating the QIE representativeness assumption in a young driver population.

Methods: We utilized New Jersey's state crash and licensing databases (2008–2012) to examine the representativeness assumption among 17- to 20-year-old nonresponsible drivers involved in clean multivehicle crashes. It has been hypothesized that if not-at-fault drivers in clean 2-vehicle crashes are a true representation of the driving population, it would be expected that nonresponsible drivers in clean 3-or-more-vehicle crashes also represent this same driving population (Jiang and Lyles 2010 Jiang XG, Lyles RW. A review of the validity of the underlying assumptions of quasi-induced exposure. Accid Anal Prev. 2010;42:1352–1358.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). Thus, we compared distributions of age, gender, and vehicle type among (1) nonresponsible young drivers in clean 2-vehicle crashes and (2) the first nonresponsible young driver in clean crashes involving 3 or more vehicles to (3) all other nonresponsible young drivers in clean crashes involving 3 or more vehicles. Distributions were compared using chi-square tests and conditional logistic regression; analyses were conducted for all young drivers and stratified by license status (intermediate vs. fully licensed drivers), crash location, and time of day of the crash.

Results: There were 41,323 nonresponsible drivers in clean 2-vehicle crashes and 6,464 nonresponsible drivers in clean 3-or-more-vehicle crashes. Overall, we found that the distributions of age, gender, and vehicle type were not statistically significantly different between the 3 groups; in each group, approximately one fourth of drivers were represented in each age from age 17 through 20, half were males, and approximately 80% were driving a car/station wagon/minivan. In general, conclusions held when we evaluated the assumption within intermediate and fully licensed young drivers separately and by crash location and time.

Conclusions: It appears that the representativeness assumption holds among the population of young NJ drivers. We encourage young driver studies utilizing QIE methods to conduct internal validation studies to ensure appropriate application of these methods and we propose utilization of QIE methods to address broader foundational and applied questions in young driver safety.     

Risk of motor vehicle crash for older adults after receiving a traffic charge: A case–crossover study

Objective: After the age of 65, the number of motor vehicle crashes per mile driven increases. Traffic-related charges issued by law enforcement can help identify drivers who are at a higher risk of having a crash. This study examines the relationship between motor vehicle crashes and traffic-related charges among older adult drivers.

Methods: Iowa Department of Transportation crash data from 2011–2012 were linked with Iowa Court Information System data for moving violations that occurred during 2009–2012 for drivers over the age of 50. A time-stratified case–crossover design was used matching on time periods 1 year apart. Case exposure was defined as having a traffic-related charge 30 days before the crash. Control exposure was the same 30-day time period 1 year before the crash for each individual. Conditional logistic regression was used to analyze the self-matched pairs. Additional time periods of 31–60, 61–90, 91–120, 121–150, 151–180, and 181–210 days before the crash were also assessed.

Results: There were 38,171 adults at least 50 years of age with an Iowa driver's license who were involved in a crash in Iowa between 2011 and 2012. In addition, 13,129 adults over the age of 50 received a charge during 2009–2012. Relative to the control time period, experiencing a traffic-related charge in the 30-day time period before the crash increased the risk of a crash by 21% (odds ration [OR] = 1.21, 95% confidence interval [CI], 1.03–1.42) for all drivers included in the study. This crash risk was similar for adults aged 50–64 (OR = 1.20, 95% CI, 1.00–1.45) and adults 65 and older (OR = 1.24, 95% CI, 0.90–1.72). In the 30 days after receiving a traffic-related charge, the risk of a crash was also increased for crashes occurring in adverse weather (OR = 1.79, 95% CI, 1.12–2.84) or during night, dawn, or twilight (OR = 1.89, 95% CI, 1.31–2.72).

Conclusions: A traffic-related charge for an adult over the age of 50 indicates an increased risk of experiencing a crash in the 30 days following the charge. The risk for crashes occurring in adverse conditions or outside of daylight hours was also increased in the 30 days after receiving a traffic-related charge. The risk of experiencing a crash decreases as time passes after receiving a charge. Measures to restrict or increase driving safety during these conditions could help reduce the crash risk for older adults who receive a traffic-related charge.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Crashes and near-crashes on horizontal curves along rural two-lane highways: Analysis of naturalistic driving data

IntroductionPrior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves.MethodsThe second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions.ResultsLogistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions.ConclusionsThis paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data.Practical ApplicationsThis paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit future researchers who work with similar type of data.     

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.     

Older drivers’ involvement in fatal RTCs. Do crashes fatal to them differ from crashes involving them but fatal to others?

In several countries, older drivers are disproportionately involved in fatal road traffic crashes (RTCs) for various reasons. This study maps the circumstances of occurrence of crashes involving older drivers that are fatal to either them or other road users and highlights differences between them. Sweden’s national in-depth studies of fatal RTCs archive was used and focus was placed on crashes in which a driver aged 65 years or older was involved between 2002 and 2004 (n = 197). Thirteen driver and crash characteristics were analyzed simultaneously and typical crash patterns (classes) were highlighted. For each pattern, the proportions of crashes fatal to the older driver vs. to someone else were compared. Four patterns were identified: (1) crashes on low-speed stretches, involving left turn and intersections; (2) crashes involving very old drivers and older vehicles, (3) rear-end collisions on high-speed stretches; and (4) head-on and single-vehicle crashes in rural areas. Older drivers dying in the crash were over-represented in classes 2 and 4. The study shows that when older drivers are involved in fatal RTCs, they are often the ones who die (60%). Typical circumstances surrounding their involvement include manoeuvring difficulties, fast-moving traffic, and colliding in an old vehicle. Preventing fatal RTCs involving older drivers requires not only age-specific but also general measures.     

Assessing driver behavior using shrp2 adverse weather data

IntroductionThis study explored how drivers adapt to inclement weather in terms of driving speed, situational awareness, and visibility as road surface conditions change from dry to slippery and visibility decreases. The proposed work mined existing data from the SHRP 2 NDS for drivers who were involved in weather-related crash and near-crash events. Baseline events were also mined to create related metadata necessary for behavioral comparisons. Methods: Researchers attempted, to the greatest extent possible, to match non-adverse-weather driving scenarios that are similar to the crash and near-crash event for each driver. The ideal match scenario would be at a day prior to the crash during non-adverse weather conditions having the same driver, at the same time of day, with the same traffic level on the same road on which the crash or near-crash occurred. Once the matched scenarios have been identified, a detailed analysis will be performed to determine how a driver’s behavior changed from normal driving to inclement-weather driving. Results: Data collected indicated that, irrespective of site location (i.e., state), most crashes and near-crashes occurred in rain, with only about 12% occurring in snowy conditions. Also, the number of near-crashes was almost double the number of crashes showing that many drivers were able to avoid a crash by executing an evasive maneuver such as braking or steering. Conclusions: Most types of near crashes were rear-end and sideswipe avoidance epochs, as the drivers may have had a difficult time merging or trying to change lanes due to low visibility or traffic. Hard braking combined with swerving were the most commonly used evasive maneuvers, occurring when drivers did not adjust their speeds accordingly for specific situations. Practical applications: Results from this study are expected to be utilized to educate and guide drivers toward more confident and strategic driving behavior in adverse weather.     

Examining teen driver crashes and the prevalence of distraction: Recent trends, 2007–2015

IntroductionTeen drivers crash at a much higher rate than adult drivers, with distractions found as a factor in nearly 6 out of 10 moderate-to-severe teen crashes. As the driving environment continues to rapidly evolve, it is important to examine the effect these changes may be having on our youngest and most vulnerable drivers.MethodThe purpose of this study was to identify types of vehicle crashes teens are most frequently involved in, as well as the distracting activities being engaged in leading up to these crashes, with a focus on identifying changes or trends over time. We examined 2,229 naturalistic driving videos involving drivers ages 16–19. These videos captured crashes occurring between 2007 and 2015. The data of interest for this study included crash type, behaviors drivers engaged in leading up to the collision, total duration of time the driver's eyes were off the forward roadway, and duration of the longest glance away from forward.ResultsRear-end crashes increased significantly (annual % change = 3.23 [2.40–4.05]), corresponding with national data trends. Among cell phone related crashes, a significant shift occurred, from talking/listening to operating/looking (annual % change = 4.22 [1.15–7.29]). Among rear-end crashes, there was an increase in the time drivers' eyes were off the road (β = 0.1527, P = 0.0004) and durations of longest glances away (β = 0.1020, P = 0.0014).ConclusionsFindings suggest that shifts in the way cell phones are being used, from talking/listening to operating/looking, may be a cause of the increasing number of rear-end crashes for teen drivers.Practical applicationsUnderstanding the role that cell phone use plays in teen driver crashes is extremely important. Knowing how and when teens are engaging in this behavior is the only way effective technologies can be developed for mitigating these crashes.     

Driver's alcohol and passenger's death in motor vehicle crashes

OBJECTIVE: Previous studies on alcohol involvement associated with fatal injury in traffic crashes have focused on the drivers, but the passenger's view is not well known. This study (1) analyzes the relationship between passenger's death and alcohol inebriation of the driver and (2) estimates the role of alcohol as the cause of a crash by examining who was at fault, sober, or inebriated. METHOD: The study includes all motor vehicle passengers (n = 420) who died in crashes in Sweden 1993 through 1996 and were medicolegally autopsied. Autopsy reports from the Departments of Forensic Medicine, including toxicological analyses, and police reports were studied. Presence of alcohol among drivers was based on blood and breath tests. RESULTS: One-fifth of the fatally injured passengers and one-fifth of the tested drivers were under the influence of alcohol. The youngest drivers had the highest prevalence of drunken driving. Drivers at fault were alcohol positive in 21% of these crashes and drivers were not at fault in 2% of these crashes. In 53% of the crashes where both the passenger and driver were alcohol positive, the passenger had a lower alcohol concentration than the driver. Children (<16 years) comprised 15% of the killed passengers. Notably, the children were riding with a driver who was under influence of alcohol in 13% of these crashes. Alcohol involvement was not tested in half of the surviving drivers. CONCLUSIONS: The data show that 20% of both passengers and drivers were under the influence of alcohol. Increased testing of surviving drivers regarding alcohol and other drugs is recommended.