Understanding traffic crash under-reporting: Linking police and medical records to individual and crash characteristics

Objective: This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both.

Method: This study focuses on road crash injuries that occurred in the province of Funen, Denmark, between 2003 and 2007 and were registered in the police, the hospital, or both authorities. Underreporting rates are computed with the capture–recapture method, and the probability for road crash injuries in police records to appear in hospital records (and vice versa) is estimated with joint binary logit models.

Results: The capture–recapture analysis shows high underreporting rates of road crash injuries in Denmark and the growth of underreporting not only with the decrease in injury severity but also with the involvement of cyclists (reporting rates of about 14% for serious injuries and 7% for slight injuries) and motorcyclists (reporting rates of about 35% for serious injuries and 10% for slight injuries). Model estimates show that the likelihood of appearing in both data sets is positively related to helmet and seat belt use, number of motor vehicles involved, alcohol involvement, higher speed limit, and females being injured.

Conclusions: This study adds significantly to the literature about underreporting by recognizing that understanding the heterogeneity in the reporting rate of road crashes may lead to devising policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend).     

Geo-spatial and log-linear analysis of pedestrian and bicyclist crashes involving school-aged children

PROBLEM: There is a growing concern with the safety of school-aged children. This study identifies the locations of pedestrian/bicyclist crashes involving school-aged children and examines the conditions when these crashes are more likely to occur. METHOD: The 5-year records of crashes in Orange County, Florida where school-aged children were involved were used. The spatial distribution of these crashes was investigated using the Geographic Information Systems (GIS) and the likelihoods of crash occurrence under different conditions were estimated using log-linear models. RESULTS: A majority of school-aged children crashes occurred in the areas near schools. Although elementary school children were generally very involved, middle and high school children were more involved in crashes, particularly on high-speed multi-lane roadways. Driver's age, gender, and alcohol use, pedestrian's/bicyclist's age, number of lanes, median type, speed limits, and speed ratio were also found to be correlated with the frequency of crashes. DISCUSSION: The result confirms that school-aged children are exposed to high crash risk near schools. High crash involvement of middle and high school children reflects that middle and high schools tend to be located near multi-lane high-speed roads. IMPACT ON INDUSTRY: The pedestrian's/bicyclist's demographic factors and geometric characteristics of the roads adjacent to schools associated with school children's crash involvement are of interest to school districts.     

Understanding the context of alcohol impaired driving for fatal crash–involved drivers: A descriptive case analysis

Objective: The objective of this study was to understand the social context and circumstances surrounding alcohol-impaired driving prior to fatal crash involvement for drivers with an illegal blood alcohol concentration (BAC ≥ 0.05 g/100 ml or 0.00 g/100 ml for restricted license holders).

Methods: Coroners' case reports investigating fatal crashes in South Australia over a 3-year period (2008–2010) were examined. The personal and crash characteristics of drivers with an illegal BAC were compared with those who had a legal BAC. For each driver with an illegal BAC, information was recorded including characteristics of last trip, location and social context of alcohol consumption, quantity and type of alcohol consumed, BAC level, presence of drugs, perceived alcohol intoxication, and alcohol dependence. Official traffic offense records were also obtained.

Results: Of the 284 fatal crashes included in the study, 34% (n = 95) involved a driver or rider with an illegal BAC. Prior to the crash, alcohol was most frequently consumed by drivers in rural areas, within private homes, and was part of normal social activities. Drivers recorded a high level of alcohol impairment, with a mean BAC of 0.173 g/100 ml and a level of alcohol dependence that was above the Australian national average (7.4 vs. 3.9%). In addition, 23% of drivers were known to be experiencing psychological stress at the time of the crash. The results also confirm that drink driving recidivism continues to be a significant problem, with 44% of drivers recording at least one prior alcohol driving offense.

Conclusions: Alcohol-impaired driving continues to be a leading cause of fatal crashes. The popularity of drinking at home, particularly in rural areas, has implications for police enforcement strategies and suggests that drink driving interventions that focus on community values and looking after friends might be beneficial. Importantly, the study highlights the need for a broader holistic approach to reduce the high levels of alcohol consumption and alcohol dependence underlying drink driving behavior.     

Analysis of risk factors affecting driver injury and crash injury with drivers under the influence of alcohol (DUI) and non-DUI

Objective: The objective of this research was to study risk factors that significantly influence the severity of crashes for drivers both under and not under the influence of alcohol.

Methods: Ordinal logistic regression was applied to analyze a crash data set involving drivers under and not under the influence of alcohol in China from January 2011 to December 2014.

Results: Four risk factors were found to be significantly associated with the severity of driver injury, including crash partner and intersection type. Age group was found to be significantly associated with the severity of crashes involving drivers under the influence of alcohol. Crash partner, intersection type, lighting conditions, gender, and time of day were found to be significantly associated with severe driver injuries, the last of which was also significantly associated with severe crashes involving drivers not under the influence of alcohol.

Conclusions: This study found that pedestrian involvement decreases the odds of severe driver injury when a driver is under the influence of alcohol, with a relative risk of 0.05 compared to the vehicle-to-vehicle group. The odds of severe driver injury at T-intersections were higher than those for traveling along straight roads. Age was shown to be an important factor, with drivers 50–60 years of age having higher odds of being involved in severe crashes compared to 20- to 30-year-olds when the driver was under the influence of alcohol.

When the driver was not under the influence of alcohol, drivers suffered more severe injuries between midnight and early morning compared to early nighttime. The vehicle-to-motorcycle and vehicle-to-pedestrian groups experienced less severe driver injuries, and vehicle collisions with fixed objects exhibited higher odds of severe driver injury than did vehicle-to-vehicle impacts. The odds of severe driver injury at cross intersections were 0.29 compared to travel along straight roads. The odds of severe driver injury when street lighting was not available at night were 3.20 compared to daylight. The study indicated that female drivers are more likely to experience severe injury than male drivers when not under the influence of alcohol. Crashes between midnight and early morning exhibited higher odds of severe injury compared to those occurring at other times of day.

The identification of risk factors and a discussion on the odds ratio between levels of the impact of the driver injury and crash severity may benefit road safety stakeholders when developing initiatives to reduce the severity of crashes.     

Modelling the relationship of driver license and offense history with fatal and serious injury (FSI) crash involvement

Introduction: Previous research has indicated that increases in traffic offenses are linked to increased crash involvement rates, making reductions in offending an appropriate measure for evaluating road safety interventions in the short-term. However, the extent to which traffic offending predicts fatal and serious injury (FSI) crash involvement risk is not well established, prompting this new Victorian (Australia) study. Method: A preliminary cluster analysis was performed to describe the offense data and assess FSI crash involvement risk for each cluster. While controlling demographic and licensing variables, the key traffic offenses that predict future FSI crash involvement were then identified. The large sample size allowed the use of machine learning methods such as random forests, gradient boosting, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. This was done for the ‘all driver’ sample and five sometimes overlapping groups of drivers; the young, the elderly, and those with a motorcycle license, a heavy vehicle license endorsement and/or a history of license bans. Results: With the exception of the group of drivers who had a history of bans, offense history significantly improved the accuracy of models predicting future FSI crash involvement using demographic and licensing data, suggesting that traffic offenses may be an important factor to consider when analyzing FSI crash involvement risk and the effects of road safety countermeasures. Conclusions: The results are helpful for identifying driver groups to target with further road safety countermeasures, and for showing that machine learning methods have an important role to play in research of this nature. Practical Application: This research indicates with whom road safety interventions should particularly be applied. Changes to driver demerit policies to better target offenses related to FSI crash involvement and repeat traffic offenders, who are at greater risk of FSI crash involvement, are recommended.     

The relationship between blood alcohol concentration (BAC), age, and crash risk

PROBLEM: The role of age (youth and driving inexperience) and alcohol as major risk factors in traffic crash causation has been firmly established by numerous studies over the past 50 years. Less well established is how the two variables interrelate to influence crash risk. Some investigations have hypothesized an interactive or synergistic effect in which young drivers with less experience and a greater tendency to take risks are more adversely affected at lower blood alcohol concentrations (BACs) than are older drivers. The evidence for this hypothesis is mixed. Resolution of this issue has important implication for developing countermeasures directed at the young driver crash problem. METHOD: Case control data previously collected in Long Beach and Fort Lauderdale were reanalyzed using a more sensitive method for detecting interaction effects than used in the original analysis. A conditional logistic regression analyses found a highly significant agexBAC interaction (P<.0001) involving differences between drivers under 21 and those 21 and older. DISCUSSION: The results clearly indicate that positive BACs in drivers under 21 are associated with higher relative crash risks than would be predicted from the additive effect of BAC and age. It is likely that two mechanisms are operating to cause the interaction. First, it seems likely that the crash avoidance skill of young novice drivers would be more adversely affected by alcohol due to their driving inexperience, immaturity, and less experience with alcohol. Second, drivers under 21 who choose to drink and to drive after drinking probably have pre-existing characteristics that predisposed them to risk taking and crash involvement apart from any increased vulnerability to alcohol impairment. IMPACT ON INDUSTRY: The results support increased enforcement of zero-tolerance BAC laws for minors.     

Mobile phone use while riding a motorcycle and crashes among university students

Objective: Motorcycle crashes are a significant road safety challenge, particularly in many low- and middle-income countries where motorcycles represent the vast majority of their vehicle fleet. Though risky riding behaviors, such as speeding and riding under the influence of alcohol, have been identified as important contributors to motorcycle crashes, little is understood about the effect of using a mobile phone while riding on motorcycle crash involvement. This article investigates crash involvement among motorcycle riders with risky riding behaviors, particularly using a mobile phone while riding.

Methods: Data were obtained from an online survey of university students’ risky riding behaviors in Vietnam administered between March and May 2016 (n?=?665).

Results: Results show that 40% of motorcycle riders reported to have experienced a crash/fall and nearly 24% of motorcycle riders indicated that they had been injured in a crash/fall. Effects of mobile phone use while riding on safety of motorcycle riders are highlighted. Specifically, more frequent use of a mobile phone for texting or searching for information while riding is associated with a higher chance of being involved in a crash/fall. The results also show that drink riding is associated with a higher chance of being injured.

Conclusions: Overall this article reveals significant safety issues of using a mobile phone while riding a motorcycle, providing valuable insight for designing education and publicity campaigns.     

Personality of young drivers in Oman: Relationship to risky driving behaviors and crash involvement among Sultan Qaboos University students

Objective: Drivers’ behaviors such as violations and errors have been demonstrated to predict crash involvement among young Omani drivers. However, there is a dearth of studies linking risky driving behaviors to the personality of young drivers. The aim of the present study was to assess such traits within a sample of young Omani drivers (as measured through the behavioral inhibition system [BIS] and the behavioral activation system [BAS]) and determine links with aberrant driving behaviors and self-reported crash involvement.

Methods: A cross-sectional study was conducted at the Sultan Qaboos University that targeted all licensed Omani's undergraduate students. A total of 529 randomly selected students completed the self-reported questionnaire that included an assessment of driving behaviors (e.g., Driver Behaviour Questionnaire, DBQ) as well as the BIS/BAS measures.

Results: A total of 237 participants (44.8%) reported involvement in at least one crash since being licensed. Young drivers with lower BIS–Anxiety scores and higher BAS–Fun Seeking tendencies as well as male drivers were more likely to report driving violations. Statistically significant gender differences were observed on all BIS and BAS subscales (except for BAS–Fun) and the DBQ subscales, because males reported higher trait scores. Though personality traits were related to aberrant driving behaviors at the bivariate level, the constructs were not predictive of engaging in violations or errors. Furthermore, consistent with previous research, a supplementary multivariate logistic regression analysis revealed that only driving experience was predictive of crash involvement.

Conclusions: The findings highlight that though personality traits influence self-reported driving styles (and differ between the genders), the relationship with crash involvement is not as clear. This article further outlines the key findings of the study in regards to understanding core psychological constructs that increase crash risk.     

Examining motor vehicle crash involvement and readiness to change on drinking and driving behaviors among injured emergency department patients

Objective: To measure the effect of motor vehicle crash (MVC) involvement and readiness to change drinking and driving behaviors on subsequent driving and drinking behaviors among injured emergency department (ED) patients who use alcohol at harmful levels.

Methods: This was a secondary analysis of a randomized controlled trial of injured ED patients who screened positive for harmful alcohol use, who at recruitment reported driving in the past 12 months and received at least one of the intended intervention sessions (brief behavioral intervention versus attention placebo control; N = 407). Outcome variables were as follows: (1) change in 6 impaired driving behaviors and (2) report of MVCs and traffic violations in the 12 months following recruitment; predictor variables were as follows: (1) treatment assignment, (2) MVC involvement at recruitment, and (3) baseline readiness to change alcohol use and drinking and driving.

Results: Modeling of change in the 6 impaired driving variables indicated that neither the recruitment visits being MVC related nor baseline readiness to change alcohol use and drinking and driving behaviors predicted greater changes in impaired driving over time. Baseline reports of past moving traffic violations and the ED visit being MVC related predicted a greater likelihood of each behavior at 12 months following study recruitment.

Conclusions: This study and others have demonstrated that ED patients with harmful alcohol use are willing to engage in behavioral interventions directed at changing risky behaviors. However, this study did not demonstrate that patients considered having the potential to be more engaged with the intervention because their ED visit was MVC related and/or they had expressed intent to change their risky alcohol use and drinking and driving behaviors were more likely to change these risky behaviors.     

Assessing the impacts of signal coordination on the crash risks of various driving cohorts

Introduction: Signal coordination has been wildly implemented on urban arterials to improve traffic efficiency. The impacts of signal coordination on traffic safety, however, are largely overlooked, particularly on crash propensities of driver–vehicle cohorts, which will vary due to changing traffic flow patterns. Method: The paper aims to compare crash risks of various driving cohorts (measured by relative crash involvement ratio) on arterials with and without signal coordination with quasi-induced exposure technique, which has been well developed in estimating crash risks for driver–vehicle characteristics (i.e., driver age, gender, and vehicle type). Michigan traffic crash data (2000–2014) are retrieved for the case study. Results: The results indicate that: (a) when signal coordination is implemented, young, male drivers, and pickups are associated with more crash responsibilities; (b) crash propensities vary for different disaggregated situations, e.g., young drivers may experience the rapid increase in crash risks during the peak hours; and (c) more hazardous actions (e.g., failing to stop in assured clear distance) are witnessed for the high-risk driving cohorts on the coordinated arterials than non-coordinated ones. Conclusions and practical applications: The findings highlight the importance of safety impact analysis of signal coordination, and serve to guide the potential improvements of safety operation and management of signal coordinated arterials.     

Regional economic conditions and crash fatality rates--a cross-county analysis

INTRODUCTION: Most studies that evaluate the relationship between economic conditions and traffic fatalities focus on the time-series relationship between the two factors. This analysis considers the cross-sectional perspective by estimating the cross-county correlation between per capita income and fatalities per vehicle mile traveled (VMT) in Ohio. METHOD: The empirical model employed in this analysis allows for interaction effects between per capita income and highway usage, in the determination of fatality rates. RESULTS: The resultant least squares estimates indicate that a significant interaction effect exists between per capita income and the percentage of highway VMT, indicating a nonlinear correlation between per capita income and fatality rates. This correlation rises as the proportion of VMT on highways rises, such that there is an inverse relationship with fatality rates when the highway share of county VMT is low and a direct relationship with fatality rates when the highway share of county VMT is high. Additionally, population density, the presence of interstate highways in rural counties, the prior prevalence of severe alcohol abuse, and the proportion of teen drivers all proved to be significant correlates with county fatality rates. CONCLUSIONS: These observations suggest factors that state and federal policy makers should consider when allocating resources that impact (whether directly or indirectly) traffic fatalities.     

Factors affecting the severity of injuries among young motorcyclists--a Swedish nationwide cohort study

OBJECTIVES: To determine factors affecting the severity of motorcycle injuries, considering variables related to the individual, the environment, the vehicle, and the crash. METHODS: This is a register-based retrospective cohort study. All individuals born in 1970-1972 (n = 334,070) were extracted from the Swedish Population and Housing Census of 1985 and followed up from 1988 to 2000, when aged 16-30. All subjects whose records indicated an injury as a motorcycle driver in the Swedish National Road Administration Accident Database were selected, and constituted the study population (n = 1,748). Factors related to the individual, the environment, the vehicle, and the crash were considered as exposure measures, whereas the outcome measure was the level of injury severity, based on assessments made on-site by police officers, in two categories: fatal/severe and minor. Associations between individual, environmental, vehicle and crash factors and injury severity were measured, using Chi-square, and through univariate and multivariate stepwise logistic regression. RESULTS: Factors such as alcohol consumption, traffic environment, speed limit, and type of crash were significantly associated (p < 0.0001) with injury severity. More specifically, a positive suspicion of alcohol consumption, driving in a rural area, and a posted speed limit over 50 km/hour were all factors positively associated (OR > 1.0) with the likelihood of being severely injured. On modeling all the variables together through stepwise logistic regression, positive suspicion of alcohol emerged as the strongest determinant (adjusted OR = 2.7) of a severe outcome. CONCLUSIONS. Motorcycle crashes still place a heavy burden on young drivers. Increased efforts are needed to prevent alcohol-related crashes-through law enforcement and a multiplicity of policies at local and national levels.     

Factors associated with motorcycle traffic crash fatalities among active duty U.S. Army personnel

Objective: Research on factors associated with motorcycle fatalities among active duty U.S. Army personnel is limited. This analysis describes motorcycle crash–related injuries from 1995 through 2014 and assesses the effect of alcohol use and helmet use on the risk of fatal injury among active duty U.S. Army motorcycle operators involved in a traffic crash, controlling for other factors shown to be potentially associated with fatality in this population.

Methods: Demographics, crash information, and injury data were obtained from safety reports maintained in the Army Safety Management Information System. Traffic crashes were defined as crashes occurring on a paved public or private roadway or parking area, including those on a U.S. Army installation. Analysis was limited to motorcycle operators. Odds ratios (ORs) and 95% confidence intervals (95% CIs) from a multivariable analysis estimated the effect of alcohol use and helmet use on the risk of a fatal injury given a crash occurred, controlling for operator and crash characteristics.

Results: Of the 2,852 motorcycle traffic crashes, most involved men (97%), operators aged 20–29 years of age (60%), and operators who wore helmets (95%) and did not use alcohol (92%). Two thirds of reported crashes resulted in injuries requiring a lost workday; 17% resulted in fatality. Controlling for operator and crash characteristics, motorcycle traffic crashes involving operators who had used alcohol had a 3.1 times higher odds of fatality than those who did not use alcohol (OR =3.14; 95% CI, 2.17–4.53). Operators who did not wear a helmet had 1.9 times higher odds of fatality than those who did wear a helmet (OR =1.89; 95% CI, 1.24–2.89).

Conclusions: Among U.S. Army motorcycle operators, alcohol use and not wearing a helmet increased the odds of fatality, given that a crash occurred, and additional modifiable risk factors were identified. Results will help inform U.S. Army motorcycle policies and training.     

Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

Patterns of drinking four weeks prior to an alcohol-related vehicular crash

OBJECTIVE: The primary objective of the study was to determine if drinking patterns on the days immediately prior to an alcohol-related motor vehicle crash (ARMVC) were significantly different than drinking patterns in the weeks prior to the crash. METHODS: Following ARMVC, 187 hospitalized non-alcohol dependent young-adults (43 females, 144 males) were enrolled. Mean age was 29.03 years, mean blood alcohol level was 165.18 mg/dL, and mean injury severity score was 10.50. When alcohol-free, subjects were interviewed by nurse clinicians to determine the quantity/frequency of alcohol consumption during the 28 days prior to the crash. Subjects reported the number of standard drinks using the Timeline Followback procedure. Total drinks/day were determined, with day 1 considered 4 weeks prior to the crash and day 28 the day of the crash. A random-intercepts general linear mixed model (GLMM) was used to test the effect of several covariates (segment 1 [days 1-26], segment 2 [days 27-28], age, sex, race, holiday/non-holiday period, driver/passenger status, and weekend/weekday crash) on the amount of standard drinks/day. RESULTS: There was no significant interaction among the covariates. The only significant predictors of drinks/day were segment 2 (b = .322, p < .0001) and gender (b = -.221, p = .016). The positive, statistically significant slope for segment 2 indicated an increase in consumption of drinks/day in the two-day period prior to the ARMVC and the negative slope for gender indicated greater consumption of drinks/day for men than women. CONCLUSION: Persons injured in an ARMVC had a significant increase in alcohol consumption on the day before and the day of vehicular crashes (days 27 and 28) as compared to the first 26 days in the 28-day period preceding the crash. When non-alcohol-dependent subjects are counseled to reduce their risk of traffic crashes, they should be alerted that when their patterns of drinking change, they are at higher risk than usual for a crash.     

MaryPODS revisited: updated crash analysis and implications for screening program implementation

PROBLEM: Due to the relative scarcity of crashes, there has consistently been a problem with analyses that use crashes as a criterion measure in their analyses. METHOD: Previous analyses of the relationships between functional capacity measures and at-fault crash involvement for older drivers as reported in the NHTSA Model Driver Screening and Evaluation Program Final Technical Report have been updated to include one additional year of driving experience. Eighteen new at-fault crashes involving drivers who previously had no crash involvement were recorded for the Maryland Motor Vehicle Administration (MVA) test sample during this interval. The method of odds ratio (OR) calculation was used to examine the relationships between functional status predictors and the most salient among the safety outcome measures identified in the Maryland research. Peak valid OR values for the prior and current analyses were contrasted, and the stability of candidate pass-fail cut-points for each predictor relative to values identified in the Final Technical Report was examined. RESULTS: Results indicate that the predictive value of functional tests appears to decrease over time, particularly for the perceptual-cognitive measures. IMPACT ON INDUSTRY: The impact of these findings on programs and policies is to underscore a need for periodic reevaluation, spaced at the shortest practical intervals but not more than 2 years apart, in order for functional capacity screening to be applied effectively by licensing authorities, health care professionals, and others to reduce personal risk and enhance public safety.     

Are automatic systems the future of motorcycle safety? A novel methodology to prioritize potential safety solutions based on their projected effectiveness

Objective: Motorcycle riders are involved in significantly more crashes per kilometer driven than passenger car drivers. Nonetheless, the development and implementation of motorcycle safety systems lags far behind that of passenger cars. This research addresses the identification of the most effective motorcycle safety solutions in the context of different countries.

Methods: A knowledge-based system of motorcycle safety (KBMS) was developed to assess the potential for various safety solutions to mitigate or avoid motorcycle crashes. First, a set of 26 common crash scenarios was identified from the analysis of multiple crash databases. Second, the relative effectiveness of 10 safety solutions was assessed for the 26 crash scenarios by a panel of experts. Third, relevant information about crashes was used to weigh the importance of each crash scenario in the region studied. The KBMS method was applied with an Italian database, with a total of more than 1 million motorcycle crashes in the period 2000–2012.

Results: When applied to the Italian context, the KBMS suggested that automatic systems designed to compensate for riders' or drivers' errors of commission or omission are the potentially most effective safety solution. The KBMS method showed an effective way to compare the potential of various safety solutions, through a scored list with the expected effectiveness of each safety solution for the region to which the crash data belong. A comparison of our results with a previous study that attempted a systematic prioritization of safety systems for motorcycles (PISa project) showed an encouraging agreement.

Conclusions: Current results revealed that automatic systems have the greatest potential to improve motorcycle safety. Accumulating and encoding expertise in crash analysis from a range of disciplines into a scalable and reusable analytical tool, as proposed with the use of KBMS, has the potential to guide research and development of effective safety systems. As the expert assessment of the crash scenarios is decoupled from the regional crash database, the expert assessment may be reutilized, thereby allowing rapid reanalysis when new crash data become available. In addition, the KBMS methodology has potential application to injury forecasting, driver/rider training strategies, and redesign of existing road infrastructure.     

Effects of electronic stability control: an update

OBJECTIVE: An earlier study reported that electronic stability control (ESC) in passenger vehicles reduced single-vehicle crash involvement risk by 41% and single-vehicle fatal crash involvement risk by 56%. The purpose of the present study was to update these effectiveness estimates using an additional year of crash data and a larger set of vehicle models. METHODS: The amount of data increased by half, allowing for separate effectiveness estimates for cars and sport utility vehicles (SUVs) and a more detailed examination of multiple-vehicle crash types. Crash involvement rates per registered vehicle were compared for otherwise identical vehicle models with and without ESC. RESULTS: Based on all police-reported crashes in 10 states during three years, ESC reduced single-vehicle crash involvement risk by approximately 41%. Effects were significantly higher for SUVs than for cars. ESC reduced single-vehicle crash involvement risk by 49% for SUVs and 33% for cars. Based on all fatal crashes in the United States during four years, ESC was found to have reduced single-vehicle fatal crash involvement risk by 56%. Again, effectiveness estimates were higher for SUVs than for cars--59% for SUVs and 53% for cars, but these differences were not statistically significant. Multiple-vehicle fatal crash involvement risk was reduced by 32%-37% for SUVs and 25% for cars. CONCLUSIONS: The present study confirms the results of the earlier study. There are significant reductions in single-vehicle crash rates when passenger vehicles are equipped with ESC. In addition, ESC leads to reductions in severe multiple-vehicle crashes.     

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.