Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown

PROBLEM: There are no specific indicators for distinguishing insurance claims related to speeding and impaired driving in the information warehouse at the Insurance Corporation of British Columbia. Contributing factors are only recorded for that part of the claim data that is also reported by the police. Most published statistics on crashes that are related to alcohol or speeding are based on police-reported data, but this represents only a fraction of all incidents. METHOD: This paper proposes surrogate models to estimate the counts and the average costs associated with speeding and impaired driving to insurance claims when contributing factors are unknown. Using police-reported data, classification rules and logistic regression models are developed to form such estimates. One approach applies classification rules to categorize insurance claims into those related to speeding, impaired driving, and other factors. The counts and the costs of insurance claims for each of these strata and overall are then estimated. A second method models the probability that an insurance claim is related to speeding or impaired driving using logistic regression and uses this to estimate the overall counts and the average costs of the claims. The two methods are compared and evaluated using simulation studies. RESULTS: The logistic regression model was found to be superior to the classification model for predicting insurance claim counts by category, but less efficient at predicting average claim costs. IMPACT: Having estimates of counts and costs of insurance claims related to impaired driving or speeding for all reported crash events provides a more accurate basis for policy-makers to plan changes and benefits of road safety programs.     

Views of US drivers about driving safety

Problem: To assess how drivers view dangers on the highway, what motivates them to drive safely, how they say they reduce their crash and injury risk, and how they rate their own driving skills. Results: Most drivers rated their skills as better than average. The biggest motivating factor for safe driving was concern for safety of others in their vehicle, followed by negative outcomes such as being in a crash, increased insurance costs, and fines. The greatest threats to their safety were thought to be other drivers' actions that increase crash risk such as alcohol impairment or running red lights. In terms of reducing crashes and injuries, drivers tended to focus on actions they could take such as driving defensively or using seat belts. There was less recognition of the role of vehicles and vehicle features in crash or injury prevention. Impact on research, practice, and policy: Knowing how drivers view themselves and others, their concerns, and their motivations and techniques for staying out of trouble on the roads provides insight into the difficulty of changing driving practices.     

Tracking traffic citations through court adjudications to posting to public driver records

Research has shown that one of the best predictors of a driver's future crash risk is the number of prior moving traffic violations (e.g., speeding). Public driver records are used by government and nongovernment users to assess drivers' future crash risks. However, the adequacy of such records may be compromised by deficient recordkeeping systems and by court-based diversion programs (e.g., probation before judgment, traffic school election) that allow drivers presumed guilty to avoid convictions in court and posting of the violations to their driver records. Using a case study approach in four jurisdictions in three states, citations issued for traffic violations were tracked through court adjudication to placement on driver records. Individual court case records and driver history records were reviewed. The percentages of citations issued that appeared on driver records were 58-87% for moving violations, 30-94% for driving while impaired (DWI), and 67-95% for occupant restraint violations. Diversion programs were a significant factor in two states, where 21% and 35% of moving violation citations resulted in diversions. Almost all court convictions in each jurisdiction were recorded on driver records, but few citations resulting in diversions were recorded. Thus, diversion programs in some jurisdictions substantially reduce the utility of public driver records as reliable indicators of prior traffic violations and future crash risks. Recordkeeping inefficiencies and errors were less important factors in this study.     

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.     

Highway safety assessment and improvement through crash prediction by injury severity and vehicle damage using Multivariate Poisson-Lognormal model and Joint Negative Binomial-Generalized Ordered Probit Fractional Split model

Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to severe highway crashes, and assisting the practitioners in allocating safety improvement resources. Methods: This paper uses urban and suburban intersection data in Connecticut, along with two sophisticated modeling approaches, i.e. a Multivariate Poisson-Lognormal (MVPLN) model and a Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) model to assess the methodological rationality and accuracy by accommodating for the unobserved factors in predicting crash counts by severity level. Furthermore, crash prediction models based on vehicle damage level are estimated using the same two methodologies to supplement the injury severity in estimating crashes by severity when the sample mean of severe injury crashes (e.g., fatal crashes) is very low. Results: The model estimation results highlight the presence of correlations of crash counts among severity levels, as well as the crash counts in total and crash proportions by different severity levels. A comparison of results indicates that injury severity and vehicle damage are highly consistent. Conclusions: Crash severity counts are significantly correlated and should be accommodated in crash prediction models. Practical application: The findings of this research could help select sound and reliable methodologies for predicting highway accidents by injury severity. When crash data samples have challenges associated with the low observed sampling rates for severe injury crashes, this research also confirmed that vehicle damage can be appropriate as an alternative to injury severity in crash prediction by severity.     

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data

IntroductionDriving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction.MethodCrash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models.ResultsModel estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood.ConclusionsThe study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated.     

Young driver risk in relation to parents' retrospective driving record

PROBLEM: Parents are an important potential influence on the driving safety of their children. This study examined the relationship of parental driving record on male and female offspring's at-fault collision risk. METHOD: Drivers aged 16-21 on the date of full licensure were selected from driver records and a matching process was used to identify putative parents in two-parent households. Poisson regression models were developed to predict at-fault collisions of male and female youth in the three years following full licensure from parents' at-fault collisions, speeding offenses, and other moving offenses in the four years prior to children's licensure. One set of models examined the relative risk associated with increasing numbers of maternal and paternal at-fault collisions and offenses. Other models examined the joint versus separate maternal and parental contributions. RESULTS: Controlling for region of residence, both mothers' and fathers' at-fault collisions were associated with an increased risk in both male and female youth at-fault collisions. Mothers' and fathers' speeding offenses were also associated with increased relative risk of at-fault collisions for both sons and daughters, while fathers' other moving offenses increased collision risk for sons but not daughters. DISCUSSION: Further research is required to identify how parental driving risk is transmitted to children. IMPACT ON INDUSTRY: (a) Parents of young children should be informed of their role in influencing their children's future driving risk; (b) The results identify risk factors that could be of interest to licensing authorities and the insurance industry.     

Fewer workers' compensation claims and lower claim costs if employers with high injury rates achieved the rates of their safer peers

Introduction: Employers engaged in similar business activities demonstrate a range of workers' compensation claim rates. Workplace injuries and illnesses could be prevented if employers with high claim rates achieved the claim rates of their safer peers. Methods: We used Washington workers' compensation claims data for years 2013–2015 to calculate rates of compensable claims (eligible for disability or time loss benefits, if unable to work four days after injury) and total accepted claims (compensable plus medical-aid only claims) for each employer. We estimated the number and cost of claims to occur if employers with high claim rates reduced them to the rates of employers at the 25th percentile, adjusted for insurance risk class, employer size, and injury type. To evaluate the impact of setting more or less ambitious goals, we also estimated reductions based on claim rates at the 10th and 50th percentiles. Results: Over 43% of claims and claim costs would be prevented if employers with higher claim rates lowered them to the 25th percentile using either total accepted or compensable claim rates as the benchmark outcome. The estimated claim cost savings from benchmarking to compensable claims was nearly as great as the estimate based on benchmarking to total accepted claims ($308.5 mil annually based on compensable claims vs. $332.4 mil based on total accepted claims). Restaurants and Taverns had the greatest number of potentially prevented compensable claims. Colleges and Universities and Wood Frame and Building Construction had the greatest potential reduction in compensable claim costs among larger and smaller employers, respectively. Conclusion: Substantial reductions in workers' compensation claims and costs are possible if employers achieve the injury rates experienced by their safer peers. Practical application: Evaluating the range of workplace injury rates among employers within industry groups identifies opportunities for injury prevention and offers another approach to resource allocation.     

Role of motorcycle type in fatal motorcycle crashes

IntroductionMotorcycles vary in design and performance capability, and motorcyclists may select certain motorcycle types based on driving preferences. Conversely, motorcycle performance capability may influence the likelihood of risky driving behaviors such as speeding. Both mechanisms may affect fatal crash risk when examined by motorcycle type. Although it was not possible to estimate the effect of each mechanism, the current study analyzed fatal crash data for evidence of motorcycle type differences in risky driving behaviors and risk of driver death.MethodsStreet legal motorcycles were classified into 10 types based on design characteristics and then further grouped as cruiser/standard, touring, sport touring, sport/unclad sport, supersport, and all others. For each motorcycle type, driver death rates per 10,000 registered vehicle years and the prevalence of fatal crash characteristics such as speeding were analyzed. Differences among motorcycle types concerning the effect of engine displacement were examined using Poisson regression.ResultsOverall, driver death rates for supersport motorcycles were four times as high as those for cruiser/standard motorcycles. Fatally injured supersport drivers were most likely to have been speeding and most likely to have worn helmets, but least likely to have been impaired by alcohol compared with drivers of other motorcycle types. The patterns in driver factors held after accounting for the effects of age and gender. Increased engine displacement was associated with higher driver death rates for each motorcycle type.ConclusionStrong effects of motorcycle type were observed on driver death rates and on the likelihood of risky driving behaviors such as speeding and alcohol impairment. Although the current study could not completely disentangle the effects of motorcycle type and rider characteristics such as age on driver death rates, the effects of both motorcycle type and rider age on the likelihood of risky driving behaviors were observed among fatally injured motorcycle drivers.Impact on IndustryCertain motorcycle designs, particularly supersport motorcycles, are associated with increases in risky driving behaviors and higher driver death rates. At present, there are no proven countermeasures for this situation. However, existing countermeasures such as helmet laws and automated speed enforcement could have a substantial benefit.     

Long-term crash trends at single- and double-lane roundabouts in Washington State

Introduction: Despite the proven safety benefits, crashes still occur at roundabouts. This study examined long-term trends in total crash counts, crash severity, and crashes involving common driver errors (failing to yield the right-of-way and speeding) in the period following the completion of single- and double-lane roundabouts in Washington state. Method: Crashes occurring during 2010–2016 at single- and double-lane roundabouts completed between 2009 and 2015 in Washington state were included. Poisson regression examined changes in annual total crash counts over time. Logistic regression estimated average annual changes in the odds that a crash involved an evident/incapacitating/fatal injury and that a crash involved a driver error. Regression models were estimated for single- and double-lane roundabouts separately. Results: Annual total crash counts declined significantly by 8.8% over time at double-lane roundabouts and increased nonsignificantly over time at single-lane roundabouts. The study estimated a significant 32.1% annual reduction in the odds that a crash involved an evident or incapacitating injury at double-lane roundabouts and a nonsignificant 18.9% reduction at single-lane roundabouts. There was a significant 10.6% annual decline in the odds that a crash was right-of-way related at double-lane roundabouts and a significant 19.1% annual decline in the odds that a crash was speeding-related at single-lane roundabouts. Conclusions: The current study demonstrates that safety can improve over time at double-lane roundabouts as drivers gain experience navigating them. At the same time, it is important that roundabouts include design elements that will prevent right-of-way mistakes and reduce speeds. Practical applications: Communities installing double-lane roundabouts may find that their benefits will increase the longer they are in place, even if initial changes in crashes and injuries are underwhelming.     

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

Objective: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding.

Methods: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving.

Results: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk.

Conclusions: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.     

Using a driving simulator to identify older drivers at inflated risk of motor vehicle crashes

PROBLEM: To develop appropriate assessment criteria to measure the performance of older drivers using an interactive PC-based driving simulator, and to determine which measures were associated with the occurrence of motor-vehicle crash. METHOD: One hundred and twenty-nine older drivers residing in a metropolitan city volunteered to participate in this retrospective cohort study. Using the driving simulator, appropriate driving tasks were devised to test the older drivers, whose performances were assessed by 10 reliable assessment criteria. Logistic regression analysis was then undertaken to determine those criteria that influence the self-reported crash outcome. RESULTS: As expected, driving skill of older drivers was found to decline with age. Over 60% of the sample participants reported having at least one motor-vehicle crash during the past year. Adjusting for age in a logistic regression analysis, the cognitive abilities associated with the crash occurrence were working memory, decision making under pressure of time, and confidence in driving at high speed. SUMMARY: The findings of this retrospective study indicated those individuals at inflated risk of vehicle crashes could be identified using the PC-based interactive driving simulator. Prospective studies need to be undertaken to determine whether the driving simulator can predict future crash events. IMPACT ON INDUSTRY: This study demonstrated an economical driving simulator approach to screen out problematic or unsafe older drivers before a more detailed but expensive road test is considered.     

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

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

Aggressive driving behaviour in young drivers (aged 16 through 25) involved in fatal crashes

IntroductionWe wished to determine the extent to which number of passengers, driver age, and sex were associated with aggressive driving actions (ADAs) in young drivers involved in a fatal crash.MethodsWe used U.S. fatal-crash data from Fatality Analysis Reporting System (FARS), 1991 –2008. Proxy measures of aggressive driving included ADA presence and speed differential (posted speed limit minus estimated travel speed). We examined the odds of an ADA and speed differential in young drivers (aged 16 to 25) by passenger status.ResultsCompared to driving alone young drivers (aged 16) had increased odds of an ADA between 14% (OR: 1.14; 95% CI: 1.07; 1.22) and 95% (OR: 1.95; 95% CI: 1.40; 2.74) when accompanied by one and five passengers, respectively. Further, carrying a higher number of passengers was a stronger predictor of speeding in younger drivers.ConclusionsThis study supports the use of graduated licensing approaches. Specifically, developing interventions to reduce aggressive driving appear imperative.Impact on IndustryWhile the results of our study support the use of graduated licensing approaches there is room for improvement. Our study indicates that tackling impaired driving is not sufficient to drastically reduce aggressive driving among the youngest drivers. Further research on young drivers is required to understand the influence of peers and the role of gender on driving behavior. Strategies to reduce aggressive driving behaviors among the youngest drivers may not only prevent crashes during their early driving careers but may also translate into a reduced crash risk over their lifetime.     

A comprehensive examination of U.S. laws enacted to reduce alcohol-related crashes among underage drivers

Introduction: To effectively address concerns associated with alcohol-related traffic laws, communities must apply comprehensive and well-coordinated interventions that account for as many factors as possible. The goal of the current research article is to examine and evaluate the simultaneous contribution of 20 underage drinking laws and 3 general driving safety laws, while accounting for demographic, economic, and environmental variables. Methods: Annual fatal crash data (1982 to 2010), policies, and demographic, economic, and environmental information were collected and applied to each of the 51 jurisdictions (50 states and the District of Columbia). A structural equation model was fit to estimate the relative contribution of the variables of interest to alcohol-related crashes. Results: As expected, economic factors (e.g., unemployment rate, cost of alcohol) and alcohol outlet density were found highly relevant to the amount of alcohol teens consume and therefore to teens' impaired driving. Policies such as those regulating the age of bartenders, sellers, or servers; social host civil liability laws; dram shop laws; internal possession of alcohol laws; and fake identification laws do not appear to have the same impact on teens' alcohol-related crash ratios as other types of policies such as those regulating alcohol consumption or alcohol outlet density. Conclusions: This effort illustrates the need for comprehensive models of teens' impaired driving. After simultaneously accounting for as many factors as possible, we found that in general (for most communities) further reductions in alcohol-related crashes among teens might be more rapidly achieved from efforts focused on reducing teens' drinking rather than on reducing teens' driving. Future efforts should be made to develop models that represent specific communities. Practical applications: Based on this and community-specific models, simulation programs can be developed to help communities understand and visualize the impact of various policy alternatives.     

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

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

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

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

Application of machine learning technique for optimizing roadside design to decrease barrier crash costs,a quantile regression model approach

Introduction: In-transport vehicles often leave the travel lane and encroach onto natural objects on the roadsides. These types of crashes are called run-off the road crashes (ROR). Such crashes accounts for a significant proportion of fatalities and severe crashes. Roadside barrier installation would be warranted if they could reduce the severity of these types of crashes. However, roadside barriers still account for a significant proportion of severe crashes in Wyoming. The impact of the crash severity would be higher if barriers are poorly designed, which could result in override or underride barrier crashes. Several studies have been conducted to identify optimum values of barrier height. However, limited studies have investigated the monetary benefit associated with adjusting the barrier heights to the optimal values. In addition, few studies have been conducted to model barrier crash cost. This is because the crash cost is a heavily skewed distribution, and well-known distributions such as linear or poison models are incapable of capturing the distribution. A semi-parametric distribution such as asymmetric Laplace distribution can be used to account for this type of sparse distribution. Method: Interaction between different predictors were considered in the analysis. Also, to account for exposure effects across various barriers, barrier lengths and traffic volumes were incorporated in the models. This study is conducted by using a novel machine-learning-based cost-benefit optimization to provide an efficient guideline for decision makers. This method was used for predicting barrier crash costs without barrier enhancement. Subsequently the benefit was obtained by optimizing traffic barrier height and recalculating the benefit and cost. The trained model was used for crash cost prediction on barriers with and without crashes. Results: The results of optimization clearly demonstrated the benefit of optimizing the heights of road barriers around the state. Practical Applications: The findings can be utilized by the Wyoming Department of Transportation (WYDOT) to determine the heights of which barriers should be optimized first. Other states can follow the procedure described in this paper to upgrade their roadside barriers.     

Comparative judgements of crash risk and driving ability for speeding behaviours

Introduction: Preliminary research has indicated that numerous drivers perceive their risk of traffic crash to be less than other drivers, while perceiving their driving ability to be better. This phenomenon is referred to as ‘comparative optimism’ (CO) and may prove to inhibit the safe adoption of driving behaviors and/or dilute perceptions of negative outcomes. The objective of this study was to investigate comparative judgments regarding crash risk and driving ability, and how these judgments relate to self-reported speeding. Method: There were 760 Queensland motorists comprised of 51.6% males and 48.2% females, aged 16–85 (M = 39.60). Participants completed either a paper or online version of a survey. Judgments of crash risk and driving ability were compared to two referents: the average same-age, same-sex driver, and the average same-age, same-sex V8 supercar champion. Results: Drivers displayed greater optimism when comparing their crash risk and driving ability to the average same-age, same- sex driver (respectively, 72%, 72.4%), than when comparing to a V8 supercar champion (respectively, 60%, 32.9%). When comparing judgements of crash risk and driving ability to a similar driver, it appears that participants in the present study are just about as optimistic about their risk of crash (i.e. 72%) as they are optimistic about their driving ability (i.e. 74.2%).     

Potential effects of lowering the BAC limit on injuries,fatalities, and costs

IntroductionPotential health and cost impacts of lowering the BAC limit for U.S. drivers below .08% were explored through analyses of reductions in crash incidence, injury severity, and costs based on five scenarios with varying assumptions about how the change to a .05% BAC limit might affect alcohol-impaired driving.MethodsDistribution of crashes by injury level and highest driver or non-occupant BAC levels for 2010, together with unit crash costs provided a base for comparison. Scenario 1 assumed all alcohol-impaired driving ceased; scenario 2 assumed all drivers obeyed the law, and scenario 3 assumed decreases in driver BAC levels would be limited to those who had been driving near the legal limit before the change. Scenario 4 was based on changes in driver BAC levels associated with a 08% to .05% BAC limit change in Australia, and scenario 5 was based on changes in alcohol-related crashes associated with the change to the .08% BAC limit in the United States. The number of casualties prevented in each scenario was estimated using relative risks of crash involvement, and changes in societal costs were estimated using the unit costs.ResultsReductions ranging from 71% to 99% in fatalities, injuries, and costs related to alcohol-impaired driving were estimated in scenarios 1 and 2. Scenarios 3–5 produced smaller reductions ranging from 4% to 16% for alcohol-impaired fatalities, injuries, and costs.ConclusionThe wide difference between the outcomes of the two sets of scenarios reflects the sensitivity of BAC policy benefits to driver compliance behavior.Practical applicationThe quantification of the reduction in the number and costs of traffic crash casualties in the set of behavioral scenarios explored in this research can inform policymakers about the extent and limits of benefits achievable by lowering the BAC limits as they consider strategies to reduce alcohol-impaired driving.