Acceptance of drinking and driving and alcohol-involved driving crashes in California

BackgroundAlcohol-impaired driving accounts for substantial proportion of traffic-related fatalities in the U.S. Risk perceptions for drinking and driving have been associated with various measures of drinking and driving behavior. In an effort to understand how to intervene and to better understand how risk perceptions may be shaped, this study explored whether an objective environmental-level measure (proportion of alcohol-involved driving crashes in one’s residential city) were related to individual-level perceptions and behavior.MethodsUsing data from a 2012 cross-sectional roadside survey of 1147 weekend nighttime drivers in California, individual-level self-reported acceptance of drinking and driving and past-year drinking and driving were merged with traffic crash data using respondent ZIP codes. Population average logistic regression modeling was conducted for the odds of acceptance of drinking and driving and self-reported, past-year drinking and driving.ResultsA non-linear relationship between city-level alcohol-involved traffic crashes and individual-level acceptance of drinking and driving was found. Acceptance of drinking and driving did not mediate the relationship between the proportion of alcohol-involved traffic crashes and self-reported drinking and driving behavior. However, it was directly related to behavior among those most likely to drink outside the home.DiscussionThe present study surveys a particularly relevant population and is one of few drinking and driving studies to evaluate the relationship between an objective environmental-level crash risk measure and individual-level risk perceptions. In communities with both low and high proportions of alcohol-involved traffic crashes there was low acceptance of drinking and driving. This may mean that in communities with low proportions of crashes, citizens have less permissive norms around drinking and driving, whereas in communities with a high proportion of crashes, the incidence of these crashes may serve as an environmental cue which informs drinking and driving perceptions. Perceptual information on traffic safety can be used to identify places where people may be at greater risk for drinking and driving. Community-level traffic fatalities may be a salient cue for tailoring risk communication.     

Fatality risk for belted drivers versus car mass

This study was performed to determine how the likelihood of a belted driver being killed in a single car crash depends on the mass of the car. This was done by applying the pedestrian fatality exposure approach to the subset of fatalities in the Fatal Accident Reporting System (FARS) for which the driver was coded as using a shoulder belt and/or a lap belt. Combining the 1975 through 1982 data provided a sufficiently large population of belted drivers to perform the analysis. In the exposure approach used, the number of car drivers killed in single car crashes is divided by the number of nonoccupant fatalities (pedestrians or motorcyclists) associated with the same group of cars. The ratio is interpreted to reflect the physical effect of car mass, essentially independent of driver behavior effects. In the present application, car mass effects for belted drivers were determined by considering the number of belted drivers killed divided by the number of nonoccupants killed in crashes involving cars whose drivers were coded in the FARS files as being belted. Because the belt use of surviving drivers is, to some extent, self-reported, it is considered that the data given in the report should be not used to estimate the effectiveness of seat belts in preventing fatalities. The results are presented as graphical and analytical comparisons of fatality likelihood versus car mass for belted and unbelted drivers. It is concluded that the effect of car mass on relative driver fatality likelihood is essentially the same for belted and unbelted drivers (for example, the present analysis gives that a belted driver in a 900 kg car is 2.3 times as likely to be killed in a single car crash as is the belted driver in an 1800 kg car. The corresponding ratio determined here for unbelted drivers is 2.4). As a consequence of this conclusion, the relative effectiveness of seat belts in preventing driver fatalities is similar for cars of different masses.     

Older drivers’ crashes in Queensland,Australia

Background

The growing proportion of older adults in Australia is predicted to comprise 23% of the population by 2030. Accordingly, an increasing number of older drivers and fatal crashes of these drivers could also be expected. While the cognitive and physiological limitations of ageing and their road safety implications have been widely documented, research has generally considered older drivers as a homogeneous group. Knowledge of age-related crash trends within the older driver group itself is currently limited.

Objective

The aim of this research was to identify age-related differences in serious road crashes of older drivers. This was achieved by comparing crash characteristics between older and younger drivers and between sub-groups of older drivers. Particular attention was paid to serious crashes (crashes resulting in hospitalisation and fatalities) as they place the greatest burden on the Australian health system.

Method

Using Queensland Crash data, a total of 191,709 crashes of all-aged drivers (17–80+) over a 9-year period were analysed. Crash patterns of drivers’ aged 17–24, 25–39, 40–49, 50–59, 60–69, 70–79 and 80+ were compared in terms of crash severity (e.g., fatal), at fault levels, traffic control measures (e.g., stop signs) and road features (e.g., intersections). Crashes of older driver sub-groups (60–69, 70–79, 80+) were also compared to those of middle-aged drivers (40–49 and 50–59 combined, who were identified as the safest driving cohort) with respect to crash-related traffic control features and other factors (e.g., speed). Confounding factors including speed and crash nature (e.g., sideswipe) were controlled for.

Results and discussion

Results indicated that patterns of serious crashes, as a function of crash severity, at-fault levels, road conditions and traffic control measures, differed significantly between age groups. As a group, older drivers (60+) represented the greatest proportion of crashes resulting in fatalities and hospitalisation, as well as those involving uncontrolled intersections and failure to give way. The opposite was found for middle-aged drivers, although they had the highest proportion of alcohol and speed-related crashes when compared to older drivers. Among all older drivers, those aged 60–69 were least likely to be involved in or the cause of crashes, but most likely to crash at interchanges and as a result of driving while fatigued or after consuming alcohol. Drivers aged 70–79 represented a mid-range level of crash involvement and culpability, and were most likely to crash at stop and give way signs. Drivers aged 80 years and beyond were most likely to be seriously injured or killed in, and at-fault for, crashes, and had the greatest number of crashes at both conventional and circular intersections. Overall, our findings highlight the heterogeneity of older drivers’ crash patterns and suggest that age-related differences must be considered in measures designed to improve older driver safety.     

Serious or fatal driver injury rate versus car mass in head-on crashes between cars of similar mass

This work was performed to determine relations between car mass and driver injuries (serious or fatal) when cars of similar mass crash into each other head-on. This type of crash is examined because it is considered similar in some respects to a barrier crash. Data from the United States Fatal Accident Reporting System (FARS) are used to examine driver fatality likelihood as a function of car mass when cars of similar mass crash into each other. Pedestrian fatalities involving cars of the same mass are used to estimate exposure. Two additional sources of data (State data from North Carolina and New York) are used to generate information on the number of drivers seriously injured or killed per police reported crash when cars of similar mass crash into each other. The present study finds that the likelihood of driver injury (fatal or serious) when cars of similar mass crash into each other increases with decreasing car mass, both for head-on crashes and for crashes in all directions. The study does not address possible mechanisms that might lead to such relations. All the data analyzed reveal a fairly consistent picture--a driver in a 900 kg car crashing head-on into another 900 kg car is about 2.0 times as likely to be seriously injured or killed as is a driver of a 1800 kg car crashing head-on into another 1800 kg car.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Work-related traffic crashes: a record linkage study

AIM: To examine the characteristics of work-related traffic crashes involving drivers in New South Wales (NSW), Australia. METHODS: Probabilistic data record linkage were used to merge police crash records and workers compensation data for the period 1998-2002. RESULTS: The record linkage identified 13,124 drivers who were injured or died as a result of work-related traffic crash in New South Wales over the 5-year period. Approximately three quarters of driver casualties occurred during commuting (74.8%) with the rest occurring in the course of work. Male drivers made up around three quarters of these crashes and 93% of those that resulted in a fatality. Transport workers were the most frequent victims of work-related crashes while on duty (20.8%), with drivers of heavy trucks representing about half (48%) of all fatalities resulting from on duty work-related crashes. Nearly 1 in 6 male drivers were speeding at the time of the crash (15%, 95% CI 14.2-15.7) compared to less than 1 in 10 female drivers (9%, 95% CI 8.3-9.8) of female drivers. Male drivers were also significantly more likely to be fatigued at the time of the crash 7.6% (95% CI 7.0-8.2) compared to females 4.2% (95% CI 3.7-4.8). No significant difference was observed in the proportion of crashes involving fatigue between on duty and commuting traffic crashes. CONCLUSIONS: The study demonstrates the value of record linkage techniques in addressing some of the limitations of work-related data systems and in providing a more complete picture of the circumstances of occupational road crashes.     

Crash involvement of drivers with multiple crashes

A goal for any licensing agency is the ability to identify high-risk drivers. Kentucky data show that a significant number of drivers are repeatedly involved in crashes. The objective of this study is the development of a crash prediction model that can be used to estimate the likelihood of a driver being at fault for a near future crash occurrence. Multiple logistic regression techniques were employed using the available data for the Kentucky licensed drivers. This study considers as crash predictors the driver's total number of previous crashes, citations accumulated, the time gap between the latest two crashes, crash type, and demographic factors. The driver's total number of previous crashes was further disaggregated into the drivers' total number of previous at-fault and not-at-fault crashes. The model can be used to correctly classify at-fault drivers up to 74.56% with an overall efficiency of 63.34%. The total number of previous at-fault crash involvements, and having previous driver license suspensions and traffic school referrals are strongly associated with a driver being responsible for a subsequent crash. In addition, a driver's likelihood to be at fault in a crash is higher for very young or very old, males, drivers with both speeding and non-speeding citations, and drivers that had a recent crash involvement. Thus, the model presented here enables agencies to more actively monitor the likelihood of a driver to be at fault in a crash.     

Effects of enforcement intensity on alcohol impaired driving crashes

Background

Research measuring levels of enforcement has investigated whether increases in police activities (e.g., checkpoints, driving-while-intoxicated [DWI] special patrols) above some baseline level are associated with reduced crashes and fatalities. Little research, however, has attempted to quantitatively measure enforcement efforts and relate different enforcement levels to specific levels of the prevalence of alcohol-impaired driving.

Objective

The objective of this study was to investigate the effects of law-enforcement intensity in a sample of communities on the rate of crashes involving a drinking driver. We analyzed the influence of different enforcement strategies and measures: (1) specific deterrence – annual number of driving-under-the-influence (DUI) arrests per capita; (2) general deterrence – frequency of sobriety checkpoint operations; (3) highly visible traffic enforcement – annual number of traffic stops per capita; (4) enforcement presence – number of sworn officers per capita; and (5) overall traffic enforcement – the number of other traffic enforcement citations per capita (i.e., seat belt citations, speeding tickets, and other moving violations and warnings) in each community.

Methods

We took advantage of nationwide data on the local prevalence of impaired driving from the 2007 National Roadside Survey (NRS), measures of DUI enforcement activity provided by the police departments that participated in the 2007 NRS, and crashes from the General Estimates System (GES) in the same locations as the 2007 NRS. We analyzed the relationship between the intensity of enforcement and the prevalence of impaired driving crashes in 22–26 communities with complete data. Log-linear regressions were used throughout the study.

Results

A higher number of DUI arrests per 10,000 driving-aged population was associated with a lower ratio of drinking-driver crashes to non-drinking-driver crashes (p = 0.035) when controlling for the percentage of legally intoxicated drivers on the roads surveyed in the community from the 2007 NRS. Results indicate that a 10% increase in the DUI arrest rate is associated with a 1% reduction in the drinking driver crash rate. Similar results were obtained for an increase in the number of sworn officers per 10,000 driving-age population.

Discussion

While a higher DUI arrest rate was associated with a lower drinking-driver crash rate, sobriety checkpoints did not have a significant relationship to drinking-driver crashes. This appeared to be due to the fact that only 3% of the on-the-road drivers were exposed to frequent sobriety checkpoints (only 1 of 36 police agencies where we received enforcement data conducted checkpoints weekly). This low-use strategy is symptomatic of the general decline in checkpoint use in the U.S. since the 1980s and 1990s when the greatest declines in alcohol-impaired-driving fatal crashes occurred. The overall findings in this study may help law enforcement agencies around the country adjust their traffic enforcement intensity in order to reduce impaired driving in their community.     

Using naturalistic driving data to explore the association between traffic safety-related events and crash risk at driver level

There has been considerable research conducted over the last 40 years using traffic safety-related events to support road safety analyses. Dating back to traffic conflict studies from the 1960s these observational studies of driver behavior have been criticized due to: poor quality data; lack of available and useful exposure measures linked to the observations; the incomparability of self-reported safety-related events; and, the difficulty in assessing culpability for safety-related events. This study seeks to explore the relationships between driver characteristics and traffic safety-related events, and between traffic safety-related events and crash involvement while mitigating some of those limitations. The Virginia Tech Transportation Institute 100-Car Naturalistic Driving Study dataset, in which the participants’ vehicles were instrumented with various cameras and sensors during the study period, was used for this study. The study data set includes 90 drivers observed for 12–13 months driving. This study focuses on single vehicle run-off-road safety-related events only, including 14 crashes and 182 safety-related events (30 near crashes, and 152 crash-relevant incidents). Among the findings are: (1) drivers under age 25 are significantly more likely to be involved in safety-related events and crashes; and (2) significantly positive correlations exist between crashes, near crashes, and crash-relevant incidents. Although there is still much to learn about the factors affecting the positive correlation between safety-related events and crashes, a Bayesian multivariate Poisson log-normal model is shown to be useful to quantify the associations between safety-related events and crash risk while controlling for driver characteristics.     

Longitudinal jerk and celeration as measures of safety in bus rapid transit drivers in Tehran

Abstract

Traditionally, analysis of individual differences in road traffic crash risk has relied on after the fact crash data. Nowadays with the help of technologies like GPS, new measures are developed to assess driving risk, inferred from naturalistic driving behaviour of drivers. In this study, two main ways of modelling driver behaviour in naturalistic driving research were discussed and compared to each other. For this purpose, 176 Bus Rapid Transit (BRT) drivers were investigated during their normal driving on Tehran BRT routes. Their speed was continuously recorded by a smart phone app from which was derived deceleration, jerk and celeration measures. Analysis showed that all of the proposed measures had positive correlations with culpable crashes and that one of the jerk variables yielded the highest correlation. Measurements of speed derivatives like jerk and celeration can help to identify dangerous driving styles in public transportation and reduce the number of crashes. Although the results of this study are encouraging, further studies for longer periods are needed to improve the reliability of the measures.     

Driver fatalities versus car mass using a new exposure approach

A new approach to estimating exposure is presented and applied to determining relations between car mass and driver fatality likelihood. The new approach considers two groups of fatal crashes in the FARS files. The first group contains crashes in which car drivers are killed in single car crashes or in crashes with trucks. These are both examples of non-two car crashes. It is hypothesized that the likelihood of a car driver fatality in such crashes depends on car mass. The second group of fatal crashes contains crashes in which either pedestrians or motorcyclists are killed in crashes with cars. It is hypothesized that the likelihood of the pedestrian or motorcyclist being killed in such crashes is independent of the mass of the car. The new exposure approach implies that the ratio of the number of people killed in the mass dependent crash to those killed in the mass independent crash gives an estimate of how car mass affects the likelihood of a driver fatality. The approach further implies that the estimate obtained is an estimate of the physical effect of mass, essentially independent of driver behavior. It is found that the new exposure approach yields relationships between driver fatality likelihood and car mass that are more precise and consistent than can normally be obtained in accident research. The effects found, which are attributed to the physical properties of the vehicle, essentially independent of driver behavior, are larger (for example, a driver of a 900 kg car is 2.6 times as likely to be killed as is a driver of a 1800kg car) than those based on fatalities per car.     

Female drinking and driving: recent trends in North Carolina

Data on driver licensing, DWI arrests, crashes, and fatalities in the State of North Carolina from the mid-70s to the mid-80s are analyzed to examine trends in drinking and driving by women. Findings presented are based on rates per licensed driver. Results suggest that more women are driving and are experiencing greater exposure to the hazards of drinking and driving. DWI arrest rates for women increased by 43% while rates for men decreased by 9%. Likewise, the proportion of legally intoxicated drivers among women is increasing. Women account for a growing proportion of alcohol-related (A/R) crashes and their involvement in single vehicle nighttime crashes is increasing. A dramatic decrease was observed in A/R fatalities in the male licensed driving population. This decrease was not paralleled by women. Authors conclude women will make up an increasing proportion of those arrested and convicted for DWI and will have more A/R crashes. Findings have implications for the design and implementation of education, deterrence, enforcement, and rehabilitation programs.     

Prevalence and characteristics of red light running crashes in the United States

About 40% of motor vehicle crashes occur at intersections. In recent years, the number of crashes at traffic signals has increased considerably. A major cause of such crashes is drivers disregarding traffic signals. Despite concerns about the frequent occurrence of red light violations and the significant crash consequences, relatively little is known about the overall prevalence and characteristics of red light running crashes. The present study examines the prevalence of red light running crashes on a national basis and identifies the characteristics of such crashes and the drivers involved. Cities with especially high rates of fatal red light running crashes are identified. Countermeasures to reduce red light running crashes based on collision patterns and characteristics of drivers involved are discussed. It was estimated that about 260 000 red light running crashes occur annually in the United States, of which approximately 750 result in fatalities. Comparisons were made between red light running drivers and drivers deemed not to have run red lights in these same crashes. As a group, red light runners were more likely than other drivers to be younger than age 30, male, have prior moving violations and convictions for driving while intoxicated, have invalid driver’s licenses, and have consumed alcohol prior to the crash. Comparisons also were made between characteristics of red light runners involved in daytime and nighttime crashes. Nighttime red light runners were more likely than daytime runners to be young, male, and have more deviant characteristics, 53% having high blood alcohol concentrations.     

Investigating driver injury severity patterns in rollover crashes using support vector machine models

Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.     

Identification of differences between rural and urban safety cultures

The prevailing risk of traffic fatalities is much larger in rural areas compared to urban areas. A number of explanations have been offered to explain this including road design, emergency medical service proximity, and human factors. This research explored the potential contribution of rural driver attitudes that may underlie the increased fatal crash risk in rural environments. This analysis examined differences between rural and urban drivers in terms of self-reported risk taking for driving behaviors associated with fatal crashes and attitudes toward safety interventions using a large-scale survey. The results suggested that rural drivers engage in riskier behavior, such as not wearing seatbelts, because they have lower perceptions of the risks associated with such behaviors. Results also suggested that vehicle type (e.g., pickup trucks versus passenger vehicles) may be related to seatbelt compliance and frequency of driving under the influence of alcohol. Rural drivers perceived the utility of government-sponsored traffic safety interventions to be lower than their urban counterparts. This study provides insights into the role of the human factor in rural fatal crashes and provides policy suggestions for developing safety interventions that are designed with respect to the psychosocial factors that define the rural culture.     

Prevalence of teen driver errors leading to serious motor vehicle crashes

Objectives

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors.

Methods

The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15–18 year old drivers.

Results

822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors.

Conclusions

Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training.     

Characteristics of traffic crashes in Maryland (1996-1998): differences among the youngest drivers

Motor vehicle crashes (MVCs) are the leading cause of death among teenagers in the US. The present study examines how crash rates and crash characteristics differed among drivers aged 16-21 in the state of Maryland from 1996 to 1998. The results show that, based on police reports. the youngest drivers have the highest rate of MVCs per licensed driver and per annual miles driven. Furthermore, crash characteristics suggest that inexperience rather than risky driving may account for the differing rates. Drivers closer to the age of 16 had their crashes under the safest conditions: during the day in clear weather while drinking less.     

Fatal crash involvement of unlicensed young drivers: County level differences according to material deprivation and urbanicity in the United States

Objectives

This study assessed the association between county level material deprivation and urbanization with fatal road traffic crashes involving young unlicensed drivers in the United States (US).

Background

Road traffic crashes have been positively associated with area deprivation and low population density but thus far few studies have been concerned specifically with young drivers, especially those that are unlicensed.

Methods

A county material deprivation index was derived from the Townsend Material Deprivation Index, with variables extracted from the US Census (2000). An urbanicity scale was adapted from the US Department of Agriculture's Rural–Urban Continuum Codes (2003). Data on fatal crashes involving a young unlicensed driver during a seven-year period (2000–2006; n = 3059) were extracted from the Fatality Analysis Reporting System. The effect of deprivation and urbanicity on the odds of the occurrence of at least one fatal crash at the county level was modeled by conditional and unconditional logistic regression.

Results

The conditional model found a positive association between material deprivation and a fatal crash involving a young unlicensed driver (OR = 1.19, 95% CI 1.17, 1.21). The interaction between urbanicity and material deprivation was negatively associated in suburban counties for fatal crashes (OR = 0.92, 95% CI 0.90, 0.95).

Conclusions

An association with material deprivation and the likelihood of a fatal crash involving a young unlicensed driver is a new finding. It can be used to inform specific county-level interventions and promote state licensing policies to provide equity in young people's mobility regardless of where they live.