Association between driver and child passenger restraint: Analysis of community-based observational survey data from 2005 to 2019

Introduction: Crash data suggest an association between driver seatbelt use and child passenger restraint. However, community-based restraint use is largely unknown. We examined the association between driver seatbelt use and child restraint using data from a state-wide observational study. Methods: Data from Iowa Child Passenger Restraint Survey, a representative state-wide survey of adult seat belt use and child passenger safety, were analyzed. A total of 44,996 child passengers age 0–17 years were observed from 2005 to 2019. Information about driver seatbelt use and child restraint was directly observed by surveyors and driver age was reported. Logistic regression was used to examine the association between driver seatbelt use and child restraint adjusting for vehicle type, community size, child seating position, child passenger age, and year. Results: Over the 15-year study period, 4,114 (9.1%) drivers were unbelted, 3,692 (8.2%) children were completely unrestrained, and another 1,601 (3.6%) children were improperly restrained (analyzed as unrestrained). About half of unbelted drivers had their child passengers unrestrained (51.8%), while nearly all belted drivers had their child passengers properly restrained (92.3%). Compared with belted drivers, unbelted drivers had an 11-fold increased odds of driving an unrestrained child passenger (OR = 11.19, 95%CI = 10.36, 12.09). The association between driver seatbelt use and child restraint was much stronger among teenage drivers. Unbelted teenage drivers were 33-fold more likely (OR = 33.34, 95%CI = 21.11, 52.64) to have an unrestrained child passenger. Conclusion: These data suggest that efforts to increase driver seatbelt use may also have the added benefit of increasing child restraint use. Practical applications: Enforcement of child passenger laws and existing education programs for new drivers could be leveraged to increase awareness of the benefits of seatbelt use for both drivers themselves and their occupants. Interventions aimed at rural parents could emphasize the importance of child safety restraints.     

Analysis of effects of driver’s evasive action time on rear-end collision risk using a driving simulator

Introduction: Driver’s evasive action is closely associated with collision risk in a critical traffic event. To quantify collision risk, surrogate safety measures (SSMs) have been estimated using vehicle trajectories. However, vehicle trajectories cannot clearly capture presence and time of driver’s evasive action. Thus, this study determines the driver’s evasive action based on his/her use of accelerator and brake pedals, and analyzes the effects of the driver’s evasive action time (i.e., duration of evasive action) on rear-end collision risk. Method: Fifty drivers’ car-following behavior on a freeway was observed using a driving simulator. An SSM called “Deceleration Rate to Avoid Crash (DRAC)” and the evasive action time were determined for each driver using the data from the driving simulator. Each driver tested two traffic scenarios – Cars and Trucks scenarios where conflicting vehicles were cars and trucks, respectively. The factors related to DRAC were identified and their effects on DRAC were analyzed using the Generalized Linear Models and random effects models. Results: DRAC decreased with the evasive action time and DRAC was closely related to drivers’ gender and driving experience at the road sections where evasive action to avoid collision was required. DRAC was also significantly different between Cars and Trucks scenarios. The effect of the evasive action time on DRAC varied among different drivers, particularly in the Trucks scenario. Conclusions: Longer evasive action time can significantly reduce crash risk. Driver characteristics are more closely related to effective evasive action in complex driving conditions. Practical Applications: Based on the findings of this study, driver warning information can be developed to alert drivers to take specific evasive action that reduces collision risk in a critical traffic event. The information is likely to reduce the variability of the driver’s evasive action and the speed variations among different drivers.     

Age group differences in collision risk

Introduction

The purpose of the current study was to examine differences in factors associated with self-reported collision involvement of three age groups of drivers based on a large representative sample of Ontario adults. Method: This study was based on data from the CAMH Monitor, an ongoing cross-sectional telephone survey of Ontario adults 18 years and older from 2002 to 2005. Three age groups were examined: 18-34 (n = 1,294), 35-54 (n = 2,428), and 55+ (n = 1,576). For each age group sample, a logistic regression analysis was conducted of self-reported collision involvement in the last 12 months by risk factor measures of driving exposure (kilometers driven in a typical week, driving is stressful, and driving on busy roads), consuming five or more drinks of alcohol on one occasion (past 12 months), cannabis use (lifetime, and past 12 months), and driving after drinking among drinkers (past 12 months), controlling for demographics (gender, region, income, and marital status). Results: The study identified differences in factors associated with self-reported collision involvement of the three age groups of adult drivers. The logistic regression model for the youngest group revealed that drivers who reported that driving was stressful at least some of the time, drank five or more drinks on an occasion, and drove after drinking had an increased risk of collision involvement. For the middle age group, those who reported using cannabis in the last 12 months had significantly increased odds of reporting collision involvement. None of the risk factor measures showed significant associations with collision risk for older drivers (aged 55+). Impact: The results suggest potential areas for intervention and new directions for future research.     

Child passenger injury risk in motor vehicle crashes: a comparison of nighttime and daytime driving by teenage and adult drivers

INTRODUCTION: To examine the association between child passenger injury risk, restraint use, and crash time (day vs. night) for children in crashes of vehicles driven by teenage versus adult drivers. METHODS: Cross-sectional study involving telephone interviews with insured drivers in a probability sample of 6,184 crashes involving 10,028 children. RESULTS: Child passengers in teen nighttime crashes had an increased injury risk and an increased risk of restraint nonuse compared with those in teen daytime crashes. This increased injury risk can be explained by differences in the age of child passengers, collision type, and child passenger's restraint status associated with time of day. CONCLUSIONS: In order to limit the risk of injury to child passengers driven by teens, Graduated Driver Licensing (GDL) laws should include provisions restricting nighttime driving, as well as mandates for age-appropriate restraint for child passengers. Consideration should also be given for education in child passenger safety for novice teen drivers as part of the licensing process. IMPACT ON INDUSTRY: Results of this study can be used to support advocacy efforts by the automotive industry and others to promote nighttime driving restrictions on novice drivers. In addition, given that both driver groups were more likely to be involved in a single-vehicle collision during the night, technologies such as electronic stability control may offer opportunities for protection. Further reseach on specific circumstances of teen nighttime crashes is needed to inform industry efforts to improve visibility or vehicle operation under poor lighting conditions.     

Emergency department visits vs. fatalities among substance-impaired underage youths involved in motor vehicle crashes

IntroductionEmergency department (ED) visits resulting from motor vehicle crashes (MVCs) among individuals younger than 21 impaired by alcohol and/or drugs have been less studied than MVC fatalities.MethodUsing data from 2004 to 2011, we compare the magnitude and pattern of national ED visit and mortality data for alcohol- and drug-impaired youths involved in MVCs.ResultsTemporal patterns of ED visits are similar to those of fatalities, but the two differ in magnitude. The ratio of ED visits to fatalities is 3.5:1; alcohol related events involvement dominates other drugs in both categories.DiscussionThe volume of injuries serious enough to warrant ED visits imposes significant health, social, and financial burdens. In ED visits, alcohol is the prime source of MVC morbidity burden; other drugs consistently contribute less.Practical applicationsThese incidents are persistent and require interventions aimed at multiple levels of prevention, including stricter corrective steps earlier in the impaired driving career to reduce subsequent incidents. ED visits for MVC injuries can be important “teachable moments.” Limitations of the study indicate the need for improved surveillance of underage substance-involved crashes.     

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.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

Characteristics of vehicles driven by teens and adults killed in crashes, 2013–2017

Introduction: Teen drivers experience higher crash risk than their experienced adult counterparts. Legislative and community outreach methods have attempted to reduce this risk; results have been mixed. The increasing presence of vehicle safety features across the fleet has driven fatality numbers down in the past decades, but the disparity between young drivers and others remains. Method: We merged Fatality Analysis Reporting System (FARS) data on fatal crashes with vehicle characteristic data from the Highway Loss Data Institute (HLDI). The analysis compared the vehicle type, size, age, and the presence of select safety features in vehicles driven by teens (ages 15–17 years) and adult drivers (ages 35–50 years) who were killed in crashes from 2013 to 2017. Results were compared with a similar analysis conducted on data from 2007 to 2012. Results: Teen drivers were more likely than their adult counterparts to be killed while driving older, smaller vehicles that were less likely to have the option to be equipped with side airbags. Discussion: Teenage drivers remain more likely to be killed while driving older, smaller vehicles than adult drivers. Parents and guardians are mainly responsible for teen vehicle choice, and should keep vehicle size, weight, and safety features in mind when placing their teen in a vehicle. Practical Application: These findings can help guide safer vehicle choice for new teen drivers.     

The role of drug and alcohol use and the risk of motor vehicle crashes in Shiraz,Iran, 2014: A case–crossover study

Background: Traffic accidents and traffic-related injuries and mortality have become a major public health concern in Iran. This study aimed to examine the role of drug and alcohol use in motor vehicle accidents in Iran.

Methods: This case–crossover study was conducted on 441 drivers who survived a road traffic crash and were taken to the emergency department of Shahid Rajaee trauma hospital in Shiraz, southern Iran. Data were collected using checklists that included demographic characteristics and drug and alcohol use prior to driving. Alcohol and drug use was identified through self-report, and cannabis, morphine, and methamphetamine urine tests were used to confirm drug abuse among drivers.

Results: In total 17.9% of drivers reported using drugs (cannabis, opium, or metamphetamine) and 8.84% of drivers reported consuming alcohol prior to the collision. The crude odds ratios (ORs) for having a crash for opium, cannabis, and metamphetamine were 1.94 (95% interval confidence [CI], 1.11–3.38), 2.37 (95% CI, 1.03–5.42), 5.5 (95% CI, 1.21–24.81), respectively, and for all drugs was 3.83 (95% CI, 2.28–6.43). The OR for alcohol was 3.5 (95% CI, 1.73–7.06) based on self-report.

Conclusion: Drug and alcohol use are increasing the risk of traffic crashes in Iran. Risk-reducing programs must be designed and implemented.     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Decomposition analysis of the effects of vehicle safety technologies on the motor vehicle collision–related mortality rate from 1994 to 2015

Abstract

Objective: Though the mortality rate for motor vehicle collisions (MVCs) has been decreasing since the 1960s with the advent of the first federal seat belt laws in 1968, MVC remains a leading cause of death for individuals aged 1 to 44 years. The purpose of this study is to examine the effects of frontal (FABs) and side airbags (SABs) and electronic stability control (ESC) on the components of the MVC mortality rate.

Methods: The MVC mortality rate from 1994 to 2015 was separated into its components of exposure of vehicles, exposure of travel, collision density, injury incidence, and case fatality rate. Year was categorized on the availability of safety technology in vehicles: 1994–1997 (first-generation FABs mandated), 1998–2001 (sled-certified, second-generation FABs mandated), 2002–2006 (increasing prevalence of SABs and ESC), 2007–2011 (advanced airbags mandated), and 2012–2015 (ESC mandated, SAB in over 90% of vehicles, introduction of advanced safety systems). Relative contributions (RCs) of the components to changes in the MVC-related mortality rate were calculated as the absolute value of the component’s beta coefficient divided by the sum of the absolute values of all components’ beta coefficients. Negative binomial regression–estimated rate ratios (RRs) for the changes in the rate of each component by year category compared to the prior year category.

Results: Significant decreases in the MVC mortality rate were observed for 2007–2011 and 2012–2015. The decrease in 2007–2011 was due in most part to an 18% decrease in the injury incidence (RR?=?0.82, P?<?.0001, RC?=?63%), though there was a noted contribution by the decrease in vehicle miles traveled (RR?=?0.95, P?<?.0001, RC?=?15%). The continued decrease in mortality in 2012–2015 was due is most part to the 10% decreased case fatality rate (RR?=?0.90, P?<?.0001, RC?=?66%) because there was no significant change in the vehicle miles traveled and injury incidence.

Conclusions: The results of this study highlight the effects of vehicle safety technologies on the MVC-related mortality rate and can help direct prevention efforts. Through the study period, there was no meaningful contribution to decreases in the MVC-related mortality rate due to components related to exposure (i.e., vehicles per population and the rate of vehicle miles traveled), suggesting that prevention efforts at decreasing exposure prevalence would have little effect on the MVC-related mortality rate. Instead, prevention efforts should continue to focus on event-phase methods to decrease injury occurrence and mitigate injury severity during the collision.     

The useful field of view assessment predicts simulated commercial motor vehicle driving safety

Objective: The Useful Field of View (UFOV) assessment, a measure of visual speed of processing, has been shown to be a predictive measure of motor vehicle collision (MVC) involvement in an older adult population, but it remains unknown whether UFOV predicts commercial motor vehicle (CMV) driving safety during secondary task engagement. The purpose of this study is to determine whether the UFOV assessment predicts simulated MVCs in long-haul CMV drivers.

Method: Fifty licensed CMV drivers (M_age = 39.80, SD = 8.38, 98% male, 56% Caucasian) were administered the 3-subtest version of the UFOV assessment, where lower scores measured in milliseconds indicated better performance. CMV drivers completed 4 simulated drives, each spanning approximately a 22.50-mile distance. Four secondary tasks were presented to participants in a counterbalanced order during the drives: (a) no secondary task, (b) cell phone conversation, (c) text messaging interaction, and (d) e-mailing interaction with an on-board dispatch device.

Results: The selective attention subtest significantly predicted simulated MVCs regardless of secondary task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC in the simulated drive. The e-mail interaction secondary task significantly predicted simulated MVCs with a 4.14 times greater risk of an MVC compared to the no secondary task condition. Subtest 3, a measure of visual speed of processing, significantly predicted MVCs in the email interaction task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC during the email interaction task.

Conclusions: The UFOV subtest 3 may be a promising measure to identify CMV drivers who may be at risk for MVCs or in need of cognitive training aimed at improving speed of processing. Subtest 3 may also identify CMV drivers who are particularly at risk when engaged in secondary tasks while driving.     

The relationship of beer consumption and state alcohol and motor vehicle policies to fatal accidents

Fatal accident data from 50 states and the District of Columbia were examined in order to determine the relationship between alcohol availability and fatal motor vehicle accidents. This relationship was analyzed for both fatal accidents and motor vehicle fatalities (potentially more than one per accident) using multiple regression. The independent variables were: (1) driving age (percent of drivers under 21); (2) beverage purchase age; (3) average beer consumption; (4) number of outlets per million population selling alcohol for on-premise consumption; (5) percentage of metropolitan residents; (6) percentage of male drivers; and (7) mileage per driver per year. It was found that the regression analyses for fatal accidents and for fatalities were highly similar. Driving age was the strongest predictor of highway mortality. On-premise availability of alcohol was significantly and inversely associated with motor vehicle fatalities. This suggests that when on-premise outlets are fewer and more geographically spread out, the chances of drinking and driving are greater. Finally, average beer consumption was significantly and positively associated with highway fatalities perhaps because many drivers consider it a “soft” alcoholic beverage that will not impair their ability to drive.     

How do drivers avoid collisions? A driving simulator-based study

Introduction: Drivers' collision avoidance performance in an impending collision situation plays a decisive role for safety outcomes. This study explored drivers' collision avoidance performances in three typical collision scenarios that were right-angle collision, head-on collision, and collision with pedestrian. Method: A high-fidelity driving simulator was used to design the scenarios and conduct the experiment. 45 participants took part in the simulator experiment. Drivers' longitudinal/lateral collision avoidance performances and collision result were recorded. Results: Experimental results showed that brake only was the most common response among the three collision scenarios, followed by brake combining swerve in head-on and pedestrian collision scenarios. In right-angle collision scenario with TTC (time to collision) largest among three scenarios, no driver swerved, and meanwhile drivers who showed slow brake reaction tended to compensate the collision risk by taking a larger maximum deceleration rate within a shorter time. Swerve-toward-conflict was a prevalent phenomenon in head-on and pedestrian collision scenarios and significantly associated with collision risk. Drivers that swerved toward the conflict object had a shorter swerve reaction time than drivers that swerved away from conflict. Conclusions: Long brake reaction time and wrong swerve direction were the main factors leading to a high collision likelihood. The swerve-toward-conflict maneuver caused a delay in brake action and degraded subsequent braking performances. The prevalent phenomenon indicated that drivers tended to use an intuitive (heuristic) way to make decisions in critical traffic situations. Practical applications: The study generated a better understanding of collision development and shed lights on the design of future advanced collision avoidance systems for semi-automated vehicles. Manufactures should also engage more efforts in developing active steering assistance systems to assist drivers in collision avoidance.     

The effectiveness of alternative transportation programs in reducing impaired driving: A literature review and synthesis

Introduction: Studies have shown that approximately half of arrested intoxicated drivers had their last alcoholic drink at a licensed bar or restaurant. Current efforts to prevent intoxicated patrons from leaving licensed establishments and driving home have been only partially successful. Since a high proportion of drinkers drive to their drinking destination, promoting the use of alternative transportation (AT) – including safe ride shuttles, free or subsidized taxi and ridesharing services, voluntary or paid designated driver programs, and more accessible public transportation – is an important strategy for preventing impaired driving. The primary goal of this study was to review and synthesize the findings of research studies designed to test the effectiveness of AT programs in reducing alcohol-impaired driving. A secondary goal was to report if using AT has led to any unintended consequences, in particular greater alcohol consumption. Method: We identified relevant academic articles, new articles, government reports, and other documents (English only) through the University of Chicago library, Google Scholar, and Google Search. We also included published articles recommended by peers. Key search terms included: alternative transportation; safe rides; designated driver; alcohol-impaired driving; alcohol consumption, cost effectiveness; and reduce drunk driving. Initially, we identified 168 potentially relevant sources, of which only 57 were academic articles. After a thorough review, we narrowed down the number of relevant articles to 125 including some background articles and government reports. Results: Some AT programs produced reductions in one or more of the following outcomes: (1) impaired driving; (2) impaired driving crashes; (3) driving under the influence (DUI) arrests; and (4) traffic crashes in general, but others were not shown to be effective. A few programs resulted in greater self-reported alcohol use, but there were no significant findings indicating that drinking when using AT led to an increase in alcohol-related harms such as public intoxication, assaults, or other alcohol-related crime. Of the studies that conducted a cost-benefit analysis, most showed that AT programs yielded a positive benefit, but these studies did not include a sufficient number of variables to be considered true cost-benefit analyses. Conclusions: There is mixed evidence regarding the effectiveness of AT programs. Evaluations with more rigorous quasi-experimental and experimental designs are needed to identify which types of AT programs work best for different types of communities and target groups. Practical Applications: The literature review and synthesis revealed that the most successful AT programs typically have some of these attributes: (1) social acceptance; (2) high level of public awareness; (3) low cost; (4) year-round availability; (5) provide rides to and from drinking venues; (6) several sponsors that provide funding); (7) user convenience; and (8) perceived safety.     

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.     

What’s in a name? Drivers’ perceptions of the use of five SAE Level 2 driving automation systems

Introduction: Automobile manufacturers are developing increasingly sophisticated driving automation systems. Currently, the highest level of automation available on the market is SAE Level 2, which provides sustained assistance for both lateral and longitudinal vehicle control. The purpose of this study was to evaluate how drivers’ perceptions of what behaviors secondary to driving are safe while a Level 2 system is operating vary by system name. Methods: A nationally representative telephone survey of 2005 drivers was conducted in 2018 with questions about behaviors respondents perceived as safe while a Level 2 driving automation system is in operation. Each respondent was asked about two out of five system names at random for a balanced study design. Results: The name “Autopilot” was associated with the highest likelihood that drivers believed a behavior was safe while in operation, for every behavior measured. There was less variation observed among the other four SAE Level 2 system names when compared with each other. A limited proportion of drivers had experience with advanced driver assistance systems and fewer of these reported driving a vehicle in which Level 2 systems were available. Drivers reported that they would consult a variety of sources for information on how to use a Level 2 system. Conclusions: The names of SAE Level 2 driving automation systems influence drivers’ perceptions of how to use them, and the name “Autopilot” was associated with the strongest effect. While a name alone cannot properly instruct drivers on how to use a system, it is a piece of information and must be considered so that drivers are not misled about the correct usage of these systems. Practical Applications: Manufacturers, suppliers, and organizations regulating or evaluating SAE Level 2 automated driving systems should ensure that systems are named so as not to mislead drivers about their safe use.