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.     

Collisions involving senior drivers: high-risk conditions and locations

OBJECTIVES: To better understand the characteristics of crashes involving senior drivers 65 and older, studies of these crashes were reviewed. METHODS: The review focused primarily on North American studies published since 1990. Studies point to important differences between the crashes of senior drivers and those of younger drivers. RESULTS. Numerous studies have found that senior drivers' crashes are much more likely than crashes of younger drivers to occur at intersections. Senior drivers have particularly high rates of involvement in intersection crashes when they are turning, and even more so when they are turning left. Senior drivers are more likely than younger drivers to have been at fault in these situations, typically because they failed to yield the right-of-way, disregarded the traffic signal, or committed some other traffic violation. Studies also suggest that the extent of overinvolvement of senior drivers in certain types of crashes generally increases with advancing age. CONCLUSIONS. The extent to which the distinctive characteristics of senior drivers' crashes may be due to changing travel patterns associated with aging, or physical or cognitive impairments related to the aging process, is unclear. Further research is needed to understand the pre-crash circumstances of older drivers' intersection crashes.     

The impact of environmental, vehicle and driver characteristics on injury severity in older drivers hospitalized as a result of a traffic crash

INTRODUCTION: Compared to younger age groups, older people are more likely to be seriously injured or to die as a result of a traffic crash. METHOD: The aim of the study is to examine the impact of environmental, vehicle, crash, and driver characteristics on injury severity in older drivers involved in traffic crashes by using recently linked police crash records and hospitalization data from New South Wales, Australia. The severity of injury resulting from traffic crashes was measured using the International Classification of Diseases, 10th revision (ICD-10) Injury Severity Score (ICISS). RESULTS: Multivariate analysis identified rurality, presence of complex intersections, road speed limit, driver error, speeding, and seat belt use as independent predictors of injury severity in older people. The type of intersection configuration explained over half of the observed variations in injury severity. IMPACT ON INDUSTRY: Environmental modification such as intersection treatments might contribute to a decrease in the severity of injury in older people involved in road crashes.     

A statistical approach to estimating driver responsibility in two-car crashes

A statistical model is developed relating driver age distributions in one-car and two-car crashes to the probability that both of the drivers in a two-car crash are similarly responsible for the crash as are drivers in a single-car crash. The model is applied to (a) passenger car crashes in the years 1975–1980 involving a driver fatality, compiled in the U.S. Fatal Accident Reporting System (FARS), and (b) all police-reported crashes occurring in North Carolina in 1979, supplied by the North Carolina Highway Safety Research Center. Appropriate national and North Carolina driver license data are used to estimate exposure to potential crashes as a function of driver age. The model is found to provide an adequate fit to observed driver age distribution in two-car crashes for both data sets. The results obtained from this fit to the model equations indicate that for two-car crashes involving a driver fatality, both drivers contribute to the responsibility for the crash in about 40% of cases, but for less severe two-car crashes, only one of the two involved drivers is generally responsible.     

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers

Introduction: This article analyzes the effect of driver’s age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector. Method: We investigate differences in the severity of traffic crashes among two subgroups of older drivers –young-older (65–75) and old-older (75+), and findings are compared with the age interval of drivers under 65. Here, we draw on data for 2016 provided by Spanish Traffic Authority. Parametric and semi-parametric regression models are applied. Results: We identified the factors related to the crash, vehicle, and driver that have a significant impact on the probability of the crash being slight, serious, or fatal for the different age groups. Conclusions: We found that crash severity and the expected costs of crashes significantly increase when the driver is over the age of 75. Practical Applications: Our results have obvious implications for regulators responsible for road safety policies – most specifically as they consider there should be specific driver licensing requirements and driving training for elderly – and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets.     

Aggressive behavior while driving as predictor of self-reported car crashes

PROBLEM: In Greece, there is a lack of scientific evidence on the relationship between aggressive behavior while driving and young drivers' involvement in car crashes; this study examined this potential relationship. METHODS: The randomly selected samples of 356 young drivers (18-24 years old) were interviewed through a questionnaire of self-reported car crash involvement, which mainly focused on their behavior on the road and the number of car crashes in which they had been involved. RESULTS: The statistical methods used were principal components analysis (PCA) and multiple regression analysis. Two factors relevant to aggressive driving emerged: (a) driving violations and (b) irritability while driving. The multivariate model suggested that driving just for fun (joyriding) and irritability were predictors of young drivers' involvement in car crashes. It was found that younger age was negatively associated with young drivers' involvement in car crashes. IMPACT ON GOVERNMENT AND INDUSTRY: The findings of this study can contribute in the formation of public policies aiming to prevent young drivers' car crashes. These findings can also be the starting point of some health promotion interventions trying to reduce car crashes and casualties on the road. Finally, the insurance companies may be interested in applying these findings into their field of interest.     

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.     

Risks older drivers pose to themselves and to other road users

Problem

Studies have shown that older drivers have high death rates and lower rates of involvement in crashes that kill others; but most studies have not considered drivers' responsibility for their crashes, and many have considered only one particular measure of risk.

Method

This study examines risks that drivers of various ages pose to themselves and to others on per-driver, per-trip, and per-mile bases, taking responsibility for crashes into account, using United States fatal crash data from 1999 through 2003 and travel estimates from 2001.

Results

Relative to other age groups, drivers aged 85 and older face the highest risk of their own death, whereas teens pose the greatest risk to passengers, occupants of other vehicles, and non-motorists.

Discussion

The oldest drivers pose more risk to other road users than middle-aged drivers do; the degree of their excess risk depends strongly upon how risk is measured.

Impact on industry

These results demonstrate the importance of keeping clear the meaning and implications of various risk measures.     

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.     

Modeling crash injury severity by road feature to improve safety

Objective: The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature.

Method: Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity.

Results: Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway.

Conclusions: The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.     

Evaluating the impact of passengers on the safety of older drivers

PROBLEM: This study involved a quasi-induced exposure analysis of 4 years of crashes involving older drivers in the state of Kentucky. METHOD: Single- and multivehicle crashes were disaggregated according to the number of passengers: (a) no passenger, (b) one passenger, and (c) two or more passengers. RESULTS: Overall, the presence of two or more passengers was found to negatively impact the probability that drivers 75 years of age or older were at fault in crashes. Several potential factors were studied for interactive effects with passengers: vehicle occupant gender mix, time of the day, road curvature, grade, and number of lanes. The negative impact of passengers increased for some geometric road conditions. However, older drivers were found to be safer at night when carrying two or more passengers. The presence or absence of passengers was not found to affect the 65- to 74-year-old driver group. Groups of male vehicle occupants with a 75+ male driver were found to have high single-vehicle crash rates. IMPACT: These results are among the first to directly consider the effect of passengers on the crash-causing propensity of older drivers and the findings suggest more work is warranted to consider causes for the crash rate differences.     

Factors leading to older drivers' intersection crashes

OBJECTIVES: Older drivers are overinvolved in intersection crashes compared with younger drivers, but the reasons are not clearly understood. The purpose of the present study was to identify the factors that lead to older drivers' intersection crashes. METHOD: Study participants were composed of two groups of older drivers -- ages 70-79 (n = 78) and 80 and older (n = 76) -- and a comparison group of drivers ages 35-54 (n = 73); all were at fault in intersection crashes involving nonfatal injuries. Police crash reports, telephone interviews with at-fault drivers, and photographs of intersections were used to determine the kinds of driver actions and errors that led to the intersection crashes. RESULTS: Drivers 80 and older had fewer rear-end crashes than drivers ages 35-54 and 70-79, and both groups of older drivers had fewer ran-off-road crashes than drivers ages 35-54. Crashes where drivers failed to yield the right-of-way increased with age and occurred mostly at stop sign-controlled intersections, generally when drivers were turning left. The reasons for failure-to-yield crashes tended to vary by age. Compared with drivers ages 35-54 and 80 and older, drivers ages 70-79 made more evaluation errors -- seeing another vehicle but misjudging whether there was adequate time to proceed. In contrast, drivers 80 and older predominantly failed to see or detect the other vehicle. Drivers ages 35-54 also tended to make search errors, but theirs were due more often to distraction. CONCLUSIONS: Factors leading to intersection crashes vary with age, even between two age groups of older drivers. Because the number of older drivers is projected to increase, it is important to identify ways to reduce the frequency and severity of their intersection crashes. Roundabouts and protected left turn lanes at signalized intersections may help to reduce failure-to-yield crashes at intersections, especially among older drivers. Crash avoidance systems may help to reduce crashes for drivers of all ages, but most systems have not been thoroughly investigated using real-world crash data.     

Adjusting for car occupant injury liability in relation to age, speed limit, and gender-specific driver crash involvement risk

It is well established that older drivers' fragility is an important factor associated with higher levels of fatal crash involvement for older drivers. There has been less research on age-related fragility with respect to the sort of minor injuries that are more common in injury crashes. This study estimates a quantity that is related to injury fragility: the probability that a driver or a passenger of that driver will be injured in crashes involving two cars. The effects of other factors apart from drivers' fragility are included in this measure, including the fragility of the passengers, the crashworthiness of cars driven, seatbelt use by the occupants, and characteristics of crashes (including configuration and impact speed). The car occupant injury liability estimates appropriately includes these factors to adjust risk curves by age, gender, and speed limit accounting for overrepresentation in crashes associated with fragility and these other factors.     

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.     

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.     

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.     

Cell phones and driving: review of research

OBJECTIVE: The research literature on drivers' use of cell phones was reviewed to identify trends in drivers' phone use and to determine the state of knowledge about the safety consequences of such use. METHODS: Approximately 125 studies were reviewed with regard to the research questions, type and rigor of the methods, and findings. Reviewed studies included surveys of drivers, experiments, naturalistic studies (continuous recording of everyday driving by drivers in instrumented vehicles), studies of crash risk, and evaluations of laws limiting drivers' phone use. RESULTS: Observational surveys indicate drivers commonly use cell phones and that such use is increasing. Drivers report they usually use hand-held phones. Experimental studies have found that simulated or instrumented driving tasks, or driving while being observed, are compromised by tasks intended to replicate phone conversations, whether using hand-held or hands-free phones, and may be further compromised by the physical distraction of handling phones. Effects of phone use on driving performance when drivers are in their own vehicles are unknown. With representative samples of adequate size, naturalistic studies in the future may provide the means to document the patterns and circumstances of drivers' phone use and their effects on real-world driving. Currently, the best studies of crash risk used cell phone company billing records to verify phone use by crash-involved drivers. Two such studies found a fourfold increase in the risk of a property-damage-only crash and the risk of an injury crash associated with phone use; increased risk was similar for males and females, younger and older drivers, and hands-free and hand-held phones. A number of jurisdictions in the United States and around the world have made it illegal for drivers to use hand-held phones. Studies of these laws show only limited compliance and unclear effects on safety.CONCLUSIONS: Even if total compliance with bans on drivers' hand-held cell phone use can be achieved, crash risk will remain to the extent that drivers continue to use or switch to hands-free phones. Although the enactment of laws limiting drivers' use of all phones is consistent with research findings, it is unclear how such laws could be enforced. At least in the short term, it appears that drivers' phone use will continue to increase, despite the growing evidence of the risk it creates. More effective countermeasures are needed but are not known at this time.     

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.     

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.     

Driver licensing,motor-vehicle crashes,and moving violations among older adults

IntroductionDriving is important for well-being among older adults, but age-related conditions are associated with driving reduction or cessation and increased crash risk for older drivers. Our objectives were to describe population-based rates of older drivers’ licensing and per-driver rates of crashes and moving violations.Methods: We examined individual-level statewide driver licensing, crash, and traffic citation data among all New Jersey drivers aged ≥ 65 and a 35- to 54-year-old comparison group during 2010–2014. Rate ratios (RR) of crashes and moving violations were estimated using Poisson regression.Results: Overall, 86% of males and 71% of females aged ≥ 65 held a valid driver’s license. Older drivers had 27% lower per-driver crash rates than middle-aged drivers (RR: 0.73, 95% CI: 0.73, 0.74)—with appreciable differences by sex—but 40% higher fatal crash rates (RR: 1.40 [1.24, 1.58]). Moving violation rates among older drivers were 72% lower than middle-aged drivers (RR: 0.28 [0.28, 0.28]).Conclusion: The majority of older adults are licensed, with substantial variation by age and sex. Older drivers have higher rates of fatal crashes but lower rates of moving violations compared with middle-aged drivers.Practical applications: Future research is needed to understand the extent to which older adults drive and to identify opportunities to further reduce risk of crashes and resultant injuries among older adults.