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

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

Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting

Introduction: COVID-19 has disrupted daily life and societal flow globally since December 2019; it introduced measures such as lockdown and suspension of all non-essential movements. As a result, driving activity was also significantly affected. Still, to-date, a quantitative assessment of the effect of COVID-19 on driving behavior during the lockdown is yet to be provided. This gap forms the motivation for this paper, which aims at comparing observed values concerning three indicators (average speed, speeding, and harsh braking), with forecasts based on their corresponding observations before the lockdown in Greece. Method: Time series of the three indicators were extracted using a specially developed smartphone application and transmitted to a back-end platform between 01/01/2020 and 09/05/2020, a time period containing normal operations, COVID-19 spreading, and the full lockdown period in Greece. Based on the collected data, XGBoost was employed to identify the most influential COVID-19 indicators, and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models were developed for obtaining forecasts on driving behavior. Results: Results revealed the intensity of the impact of COVID-19 on driving, especially on average speed, speeding, and harsh braking per 100 km. More specifically, speeds were found to increase by 2.27 km/h on average compared to the forecasted evolution, while harsh braking/100 km increased to almost 1.51 on average. On the bright side, road crashes in Greece were reduced by 49% during the months of COVID-19 compared to the non-COVID-19 period.     

Modeling drivers’ reaction when being tailgated: A Random Forests Method

Background: Tailgating is a common aggressive driving behavior that has been identified as one of the leading causes of rear-end crashes. Previous studies have explored the behavior of tailgating drivers and have reported effective solutions to decrease the amount or prevalence of tailgating. This paper tries to fill the research gap by focusing on understanding highway tailgating scenarios and examining the leading vehicles’ reaction using existing naturalistic driving data. Method: A total of 1,255 tailgating events were identified by using the one-second time headway threshold criterion. Four types of reactions from the leading vehicles were identified, including changing lanes, slowing down, speeding up, and making no response. A Random Forests algorithm was employed in this study to predict the leading vehicle’s reaction based on corresponding factors including driver, vehicle, and environmental variables. Results: The analysis of the tailgating scenarios and associated factors showed that male drivers were more frequently involved in tailgating events than female drivers and that tailgating was more prevalent under sunny weather and in daytime conditions. Changing lanes was the most prevalent reaction from the leading vehicle during tailgating, which accounted for more than half of the total events. The results of Random Forests showed that mean time headway, duration of tailgating, and minimum time headway were three main factors, which had the greatest impact on the leading vehicle drivers’ reaction. It was found that in 95% of the events, leading vehicles would change lanes when being tailgated for two minutes or longer. Practical Applications: Results of this study can help to better understand the behavior and decision making of drivers. This understanding can be used in designing countermeasures or assistance systems to reduce tailgating behavior and related negative safety consequences.     

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.     

Policing the drunk driver: measuring law enforcement involvement in reducing alcohol-impaired driving

INTRODUCTION: With many thousands of deaths still annually attributable to driving under the influence (DUI), it remains imperative that we continually address the problem of producing and sustaining effective countermeasures, and that we subject these efforts to empirical scrutiny. This article presents relevant findings from state-wide datasets. RESULTS: A formula generating a potentially useful metric for assessing aspects of the DUI prosecutorial chain is presented, focusing on the rate of proactive DUI arrests. While in need of cautious interpretation due to issues of inherent inaccuracies in large databases, small numbers of crashes and/or arrests in multiple jurisdictions, and the lack of replication in other states, the analyses show no relationship between the level of DUI arrest activity and DUI-related crashes. This finding brings into question the efficacy of the many millions of dollars devoted each year to targeted DUI enforcement, as it is currently being implemented. CONCLUSIONS: Results are discussed in terms of developing adequate disincentives to DUI so as to raise general deterrence via dramatic increases in proactive DUI enforcement and then engaging in pervasive and persistent social marketing of such efforts to maximize the perception that arrest and punishment for DUI is always imminent, that penalties will be swift, certain, and severe. It is echoed that accurate data need to be collected at all levels of the DUI arrest and prosecution process in every jurisdiction within a state, so as to facilitate the empirical assessment of countermeasure efficacy in reducing alcohol-related crashes. IMPACT ON INDUSTRY: Given that this work needs to be replicated, the impact on the traffic safety industry is potentially huge. The present data indicate that law enforcement efforts to further abate DUI-related crashes are apparently ineffective, though likely necessary to maintain reductions achieved in the 80s and early 90s. Thus, to attain additional systematic reductions, a dramatic increase in enforcement will be necessary as will a diversification of abatement efforts, including an increase in aggressive social marketing tactics to positively impact our traffic safety culture by making DUI universally unacceptable (for a discussion of this latter issue and on the use of positive reinforcement to change driver behavior, see Dula & Geller, 2007).     

A review of driving risks and impairments associated with attention-deficit/hyperactivity disorder and the effects of stimulant medication on driving performance

INTRODUCTION: Attention-Deficit/Hyperactivity Disorder (ADHD) may interfere with driving competence, predisposing those with the disorder to impaired driving performance and greater risk for adverse driving outcomes. Effective treatment may minimize the risk in those with ADHD. METHOD: We reviewed the scientific literature on driving risks and impairments associated with ADHD and the effects of stimulants on driving performance. Several lines of evidence were considered, including longitudinal studies and community-derived sample studies. The present review is based on a weekly review (by the first author) of all journals in the behavioral and social sciences indexed in the publication Current Contents spanning the past 15 years, as well as a search of the reference section of all studies found that pertained to driving risks associated with ADHD or to the treatment of ADHD as it relates to driving difficulties. RESULTS: The review of the scientific literature demonstrated well-documented driving risks and impairments associated with ADHD and the positive effects of stimulant medications on driving performance. CONCLUSIONS: Clinicians should educate patients/caregivers about the increased risk of adverse outcomes among untreated individuals with ADHD and the role of medication in potentially improving driving performance. IMPACT ON INDUSTRY: Owing to the significantly higher risk of adverse driving outcomes, the use of stimulant medications to treat people with ADHD who drive may reduce such safety risks.     

A theoretical and methodological framework for studying and modelling drivers’ mental representations

This article provides a synthetic overview of the research programme carried out at INRETS-LESCOT over the last 10 years, in view to studying and modelling the mental representations of car drivers. Theoretically, this research is in line with two complementary scientific traditions: Human Information Processing theories on the one hand, and theories of Operative Activity on the other. As discussed in Section 1 of the article, attention is given to the functional representations of drivers, constructed “by” and “for” the action, such as they are implemented in a driving situation, and taking into account both implicit and explicit dimensions. This aim directly impacts on the methodological approach implemented, in so far as it entails defining an “experimental continuum” ranging from naturalistic observations of the driving activity (on the open road), to setting up more controlled experimental protocols in order to permit in-depth, systematic and reproducible scientific investigations of drivers’ cognition. Section 2 of the article presents a synthetic view of these methods, while Section 3 presents several significant results obtained with them. Lastly, the final part of the article focuses on the computational formalism defined at INRETS-LESCOT (i.e. the driving schemas) designed to model driver knowledge and mental representations, and developed in a COgnitive Simulation MOdel of the DRIVEr called COSMODRIVE.     

In-vehicle workload assessment: effects of traffic situations and cellular telephone use

PROBLEM: Assessment of drivers' on-road workload is an important traffic safety consideration. This study was conducted to examine the effects of cellular phone communication on driving performance, with particular emphasis on variations in task demand in different traffic situations. METHOD: Twelve participants were asked to drive on urban roads and motorways with or without concomitant mathematical-addition tests relayed via cellular phone. Measurements included task and driving performance, physiological responses, and compensatory behavior. RESULTS: Analysis of task performance revealed that mean response time was markedly increased (11.9%) for driving on urban roads compared to motorways. The mean driving speed only decreased 5.8% in the presence of phone tasks in comparison to normal driving without distractions. In addition, overall physiological workload increased through compensatory behavior in response to the phone tasks. CONCLUSIONS: Driving with phone use in different traffic environments induced measurable variations in driver workload. IMPACT ON INDUSTRY: When faced with heavy traffic, a greater safety margin is typically adopted, with more lowered driving speed and restricted phone use, and it can be assumed that there is a general trade-off between tasks to preserve driving safety.     

On-road driving evaluations: a potential tool for helping older adults drive safely longer

PROBLEM: This paper explores the potential use of on-road driving evaluations as a tool for helping older adults extend their safe driving years. METHOD: Three separate research activities were carried out. The first was a national telephone survey of current and former older drivers. The results of this survey provide information relevant to the potential market for on-road driving evaluations. The second was a series of focus groups with potential stakeholders in the process: driver educators, occupational therapists, and physicians. These groups explored the feasibility and requirements of offering on-road driving evaluations to the wider public. Supplemental data were also collected from a mail survey of driving schools nationwide. RESULTS: Based on the results of these efforts, a number of recommendations are presented for expanding the availability of on-road driving evaluations, specifically to help older adults make more responsible decisions about continuing or stopping driving, and more generally to help them drive safely longer.