Unsafe Driving Research Articles

Identifying Important Roadway Corridor Factors which Affect Crashes Influenced by Unsafe Driving Behaviors to Help Law Enforcement Proactively Reduce Crashes

Effective allocation of traffic law enforcement officers can proactively reduce crashes by stopping unsafe drivers before crashes occur, but this can be difficult because of staffing limitations. Therefore, it is important to identify roadway factors that could encourage unsafe driving behaviors so appropriate proactive enforcement methods can be taken. In this paper, signalized arterial roadway corridors in Florida are modeled to identify the important factors that affect the crash rate for seven unsafe driving behaviors. Using a standardized corridor definition, 406 corridors in seven urban Florida counties were identified. These corridors contained 18,518 crashes, including 5053 fatal and injury (FI) crashes, from 2017 to 2021 involving the studied behaviors. Three random forest regression models were developed to identify the important corridor-level factors that affect the crash rate for all crashes (model 1), FI crashes (model 2), and only FI crashes caused by careless or reckless driving (model 3). Corridors in Pasco County, corridors with greater signalized intersection densities, and corridors with six or more lanes had above average predicted crash rates for all three models. In addition, corridors with speed limits greater than 45 mph (model 1), two lanes (models 1 and 3), no school zones (models 1 and 3), bike lanes (models 2 and 3), and no horizontal curvature (models 2 and 3) were predicted to have higher than average crash rates. By considering these factors when making allocation decisions, law enforcement agencies can likely reduce crashes, injuries, and fatalities caused by these unsafe behaviors.

Higher Prevalence of Hypoglycemia and Unsafe Driving Practices in Adults With Type 1 Diabetes.

Higher Prevalence of Hypoglycemia and Unsafe Driving Practices in Adults With Type 1 Diabetes.

Machine Learning Techniques to Identify Unsafe Driving Behavior by Means of In-Vehicle Sensor Data

Traffic crashes are one of the biggest causes of accidental death in the way where, every year, more than 1.35 million of people die. In most of them, the main cause is related to the driver’s behavior. The driver performs a set of actions on the vehicle commands, such as steering, braking, accelerating or changing gear, which generate a direct response of the vehicle, or other tasks, such as visual, auditory, or haptic related tasks (e.g. looking for items, listening to radio, and using a smartphone), which can still impact on the driving safety. In this work we propose a methodology based on machine learning techniques aimed at recognizing safe and unsafe driving behaviors by means of in-vehicle sensor data. Starting from these signals we compute a set of descriptive features capable to accurately describe the behavior of the driver. Two different classification tools, namely Support Vector Machines and feed-forward neural networks, have been trained and tested on a publicly available dataset containing more than 26 hours of total driving time. The classification results report an average accuracy above 90% for both classifiers and the McNemar test shows no performance difference between the models at the 0.05 significance level, demonstrating a concrete possibility of identifying unsafe driving using in-vehicle sensor data.

Are Double-Lane Roundabouts Safe Enough? A CHAID Analysis of Unsafe Driving Behaviors

This study investigated the nature and causes of unsafe driving behavior at roundabouts through an on-road study. Four urban double-lane roundabouts with different layouts were selected for an on-road study. Sixty-six drivers (41 males and 25 females) aged 18–65 years took part in the study. Unsafe behaviors observed during the in situ survey were divided into three different categories: entry unsafe behaviors, circulation unsafe behaviors, and exit unsafe behaviors. Three chi-square automatic interaction detection (CHAID) analyses were developed in order to analyze the influence of roundabout characteristics and maneuvers on unsafe behaviors at double-lane roundabouts. The results confirmed the awareness that double-lane roundabouts are unsafe and inadvisable. More than half of unsafe driving behaviors were found to be entry unsafe behaviors. Moreover, the entry radius was found to be the geometric variable most influencing unsafe driving behaviors.

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People.

In developed countries, the number of traffic accidents caused by older drivers is increasing. Approximately half of the older drivers who cause fatal accidents are cognitively normal. Thus, it is important to identify older drivers who are cognitively normal but at high risk of causing fatal traffic accidents. However, no standardized method for assessing the driving ability of older drivers has been established. We aimed to establish an objective assessment of driving ability and to clarify the neural basis of unsafe driving in healthy older people. We enrolled 32 healthy older individuals aged over 65 years and classified unsafe drivers using an on-road driving test. We then utilized a machine learning approach to distinguish unsafe drivers from safe drivers based on clinical features and gray matter volume data. Twenty-one participants were classified as safe drivers and 11 participants as unsafe drivers. A linear support vector machine classifier successfully distinguished unsafe drivers from safe drivers with 87.5% accuracy (sensitivity of 63.6% and specificity of 100%). Five parameters (age and gray matter volume in four cortical regions, including the left superior part of the precentral sulcus, the left sulcus intermedius primus [of Jensen], the right orbital part of the inferior frontal gyrus, and the right superior frontal sulcus), were consistently selected as features for the final classification model. Our findings indicate that the cortical regions implicated in voluntary orienting of attention, decision making, and working memory may constitute the essential neural basis of driving behavior.

Relation between the Anxiety while Driving and Unsafe Driving Tendency

Relation between the Anxiety while Driving and Unsafe Driving Tendency

Understanding public transport needs in Cape Town's informal settlements: a Best-Worst-Scaling approach

A poor understanding of the needs of people living in informal settlements has often resulted in these needs being assumed and misunderstood due to the lack of proper public consultation or participation. Because of this, South Africa's transport sector, and by extension many other public sectors, faces various challenges. Knowing that public transport is the dominant mode of transport in informal settlements, a better understanding of its challenges as experienced by its commuters is essential for the development of informal settlement upgrading policies. The research in this paper uses Best-Worst-Scaling (BWS) - part of the family of discrete choice models - as a survey and analysis tool for rating and ranking public transport-related challenges of 290 randomly selected commuters from six different informal settlements in Cape Town. The most important features deduced from the public transport experience (PTE) study include (1) Walking Safety, (2) Personal Safety, (3) Unsafe Driving, (4) Overcrowding and (5) Walking Distance. There is no apparent trend in the variance between the choices of men and women. However, there is a significant variance of choices across the respective locations, and - for most attributes - between mode users. This suggests that, with respect to public transport infrastructure upgrading, contextual factors, determined by one's environment, dominate experiences and perceptions, rather than socio-demographic factors.

소명의식이 불안전운전행동에 미치는 영향: 자부심의 매개효과와 통제소재의 조절된 매개효과

직업운전자의 교통사고는 일반 운전자의 교통사고보다 발생빈도가 높고 다수의 생명과 관련되어 있기에 특별히 관심을 기울여 관리해야한다. 본 연구는 직업운전자의 불안전운전행동에 영향을 미치는 요인으로 소명의식을 상정하고, 직업운전자의 소명의식이 자부심을 증가시켜 불안전운전행동에 미치는 영향을 미치는지, 그리고 운전자의 통제소재가 이를 조절하는지를 살펴보았다. 총 195명의 버스 운전자들이 연구에 참여하였다. 연구결과, 직업운전자들의 자부심은 소명의식과 불안전운전행동의 관계를 매개하는 것으로 나타났으며, 운전자의 통제소재가 자부심과 불안전운전행동 간의 관계를 조절하는 것으로 나타났다. 구체적으로 외적 통제소재가 높은 운전자의 경우에는 자부심이 불안전운전행동이 유의미하게 낮추지만 내적 통제소재가 높은 운전자에게는 이러한 관계가 관찰되지 않았다. 아울러 전체적인 조절된 매개모델도 유의미하였다. 본 연구의 결과는 직업운전자들의 안전운전 교육에 직업 소명의식과 자부심, 통제소재 등 고려할 필요가 있음을 시사한다.

Risks of Unsafe Driving in the Oldest-old With Medical Conditions: A Comparative Analysis

Risks of Unsafe Driving in the Oldest-old With Medical Conditions: A Comparative Analysis

The Impact of Demographics, Driving Stress, Driving Behaviors Related to Stress, and Unsafe Driving Behaviors on Accident Involvement among Professional Drivers in Myanmar

The Impact of Demographics, Driving Stress, Driving Behaviors Related to Stress, and Unsafe Driving Behaviors on Accident Involvement among Professional Drivers in Myanmar

A Time-Series Analysis of Motor Carrier Safety Behaviors

Multiple stakeholders are impacted by motor carrier operating safety, including truck drivers, motor carriers, insurance companies, shippers, and the general public. I develop and test theory in this article about motor carriers' longitudinal performance on three categories of safety behaviors associated with accident rates—Unsafe Driving, Hours-of-Service Compliance, and Vehicle Maintenance—as tracked by the Federal Motor Carrier Safety Administration as part of the Compliance, Safety, and Accountability (CSA) program. I specifically draw on fundamental concepts from sociological agency theory and resource dependency theory to develop a middle-range theory that generates previously untested hypotheses about carriers' longitudinal safety performance for these classes of safety behaviors following the CSA program's inception. The hypotheses are investigated by fitting a series of multivariate latent curve models to four years of panel data for 484 big for-hire vehicle carriers operating in the United States. The empirical findings confirm the theoretical expectations and persist during robustness testing. These findings have significant consequences for academics, motor carrier executives, purchasers of motor carrier transportation services, and policymakers.

高齢運転者の日常運転における不安全行動と 速度見越反応検査及びTrail Making Testの関係性の検討

高齢運転者の日常運転における不安全行動と 速度見越反応検査及びTrail Making Testの関係性の検討

Comparative Analysis of Unsafe Driving Risk in Medical Conditions

The objective of this study was to compare different driving safety measures acorss medical condition and to compare agreements between fitness-to-drive recommendation made by referring physician and comprehensive fitness-to-drive decision by driving evaluation center

A Multivariate Time‐Series Examination of Motor Carrier Safety Behaviors

Motor carriers’ operational safety affects multiple stakeholders including truck drivers, motor carriers, insurance companies, shippers, and the general public. In this article, I devise and test theory regarding motor carriers’ longitudinal performance for three classes of safety behaviors linked to carriers’ accident rates—Unsafe Driving, Hours‐of‐Service Compliance, and Vehicle Maintenance—tracked by the Federal Motor Carrier Safety Administration as part of the Compliance, Safety, and Accountability (CSA) program. Specifically, I draw on core concepts from sociological agency theory and resource dependency theory to devise middle‐range theory that generates never‐before‐tested hypotheses regarding carriers’ longitudinal safety performance for these classes of safety behaviors after the start of the CSA program. The hypothesized predictions are tested by fitting a series of multivariate latent curve models to four years of panel data for a random sample of 484 large, for‐hire motor carriers operating in the United States. The empirical findings corroborate the theoretical predictions and remain after robustness testing. These findings have important implications for scholars, motor carrier managers, procurers of motor carrier transportation services, and public policy makers.

Comparison of Unsafe Driving Across Medical Conditions

ObjectiveTo compare risks of unsafe driving in patients with medical conditions. MethodsThis large population-based study included all patients who were referred for a fitness-to-drive evaluation at an official driving evaluation center in 2013 and 2014. Risks of unsafe driving included physician’s fitness-to-drive recommendation, comprehensive fitness-to-drive decision, motor vehicle crash history, and traffic violation history. ResultsA total of 6584 patients were included in the study. Risks of unsafe driving were significantly different across medical conditions (P<.001 for all outcome measures). Patients with neurological conditions comprised the majority of the database (4837; 74%), but were not at the highest risk for unsafe driving. Patients with psychiatric conditions or substance abuse did worse on most driving safety outcomes, despite their low representation in the total sample (359 [6%] and 46 [1%], respectively). ConclusionThe risk of unsafe driving varied greatly across medical conditions. Sensitization campaigns, education, and medical guidelines for physicians and driver licensing authorities are warranted to identify patients at risk, especially for those with psychiatric conditions and substance abuse problems.

Analysis of Truck Accidents Using Structural Equation Models

Abstract Many researchers and practitioners in the trucking industry have expressed concerns with the implementation of Compliance, Safety and Accountability (CSA), which is a safety management initiative created by the Federal Motor Carrier Safety Administration (FMCSA). CSA assigns Behavior Analysis Safety Improvement Categories (BASIC) scores to carriers, based on driver and vehicle performance. This technique of assigning BASIC scores to carriers is a cause of concern for many stakeholders in the industry. This article presents a structural equation model (SEM) to understand the relationship between the BASIC scores and crash records of the carriers. Exogenous variables are Unsafe Driving, Fatigue Driving, Driver Fitness, Controlled Substances/Alcohol, and Vehicle Maintenance. Crash-Per-Million-Miles is the endogenous variable in the SEM. We observed existence of a latent variable driver characteristic, which in turn influences three of the exogenous variables. Based on the SEM model output we concluded that four of the exogenous variables—Unsafe Driving, Fatigue Driving, Driver Fitness, and Controlled Substances/Alcohol—have significant influence on the endogenous variable.

Alcohol Mixed With Energy Drink Use Among U.S. 12th-Grade Students: Prevalence, Correlates, and Associations With Unsafe Driving

PurposeThe consumption of alcohol mixed with energy drinks (AmED) is a risky drinking behavior, most commonly studied using college samples. We know little about rates of AmED use and its associations with other risk behaviors, including unsafe driving, among high school students. This study examined the prevalence and correlates of AmED use among high school seniors in the United States. MethodsNationally representative analytic samples included 6,498 12th-grade students who completed Monitoring the Future surveys in 2012 and 2013. Focal measures included AmED use, sociodemographic characteristics, academic and social factors, other substance use, and unsafe driving (i.e., tickets/warnings and accidents) after alcohol consumption. ResultsApproximately one in four students (24.8%) reported AmED use during the past 12 months. Rates of AmED use were highest among males and white students. Using multivariable logistic regression models controlling for sociodemographic characteristics, results indicate that students who cut class, spent more evenings out for fun and recreation, and reported binge drinking, marijuana use, and illicit drug use had a greater likelihood of AmED use. AmED use was also associated with greater odds of alcohol-related unsafe driving, even after controlling for sociodemographic, academic, and social factors and other substance use. ConclusionsAmED use among 12th-grade students is common and associated with certain sociodemographic, academic, social, and substance use factors. AmED use is also related to alcohol-related unsafe driving, which is a serious public health concern.

Drivers' Perceptions of Unsafe Driving Behaviors and Their Countermeasures: A Study in Saudi Arabia

There is an increased public concern about the role of aggressive driving and "road rage" in crashes and traffic fatalities. There is no general agreement as to what constitutes aggressive driving. Consequently, the objective of the study was to survey of the perceptions on the specific unsafe driving acts. Perceptions and beliefs of drivers about unsafe and aggressive driving actions and their countermeasures are presented in this paper. The study primarily looked at the wide range of driver attitudes about speeding and other forms of unsafe driving behavior. The study was conducted in Jeddah, the second largest city of Saudi Arabia by interviewing a sample of 300 drivers. The results indicated that the drivers, in general, prefer to drive at higher speeds and could be considered as more aggressive compared to the drivers in the United States. The most dangerous reported driving act was "drive thru red light", followed by "racing another driver". Only 23% of the drivers thought that it was dangerous to drive over 30 km of the legal speed limits. The most often seen unsafe driving action was "speeding (70%), followed by "driving too closely (57%), "failing to use turn signals (53%), "drive inattentively (50%)", and "running red lights (43%)". The main causes of unsafe driving behaviors were "being in a hurry/time pressure (66%)", "aggressive behavior of others (52%)", and "refusing traffic rules (51%)". The countermeasure that was viewed to be the most effective in reducing unsafe driving behaviors was assigning more traffic police officers (66%). The study revealed that, more than half the drivers believed that more frequent ticketing (60%), doubling or tripling fines (54%), and doubling the length of imprisonment (53%) would be effective in reducing unsafe driving behaviors.

Alcohol and Marijuana Use Patterns Associated With Unsafe Driving Among U.S. High School Seniors: High Use Frequency, Concurrent Use, and Simultaneous Use

This article examines noncausal associations between high school seniors' alcohol and marijuana use status and rates of self-reported unsafe driving in the past 12 months. Analyses used data from 72,053 students collected through annual surveys of nationally representative cross-sectional samples of U.S. 12th-grade students from 1976 to 2011. Two aspects of past-12-month alcohol and marijuana use were examined: (a) use frequency and (b) status as a nonuser, single substance user, concurrent user, or simultaneous user. Measures of past-12-month unsafe driving included any tickets/warnings or accidents, as well as tickets/warnings or accidents following alcohol or marijuana use. Analyses explored whether an individual's substance use frequency and simultaneous use status had differential associations with their rate of unsafe driving. Higher substance use frequency (primarily alcohol use frequency) was significantly and positively associated with unsafe driving. The rate of engaging in any unsafe driving was also significantly and positively associated with simultaneous use status, with the highest rate associated with simultaneous use, followed by concurrent use, followed by use of alcohol alone. Individuals who reported simultaneous use most or every time they used marijuana had the highest likelihood of reporting unsafe driving following either alcohol or marijuana use. This article expands the knowledge on individual risk factors associated with unsafe driving among teens. Efforts to educate U.S. high school students (especially substance users), parents, and individuals involved in prevention programming and driver's education about the increased risks associated with various forms of drug use status may be useful.

Potential Distractions and Unsafe Driving Behaviors Among Drivers of 1- to 12-Year-Old Children

ObjectiveDriver distraction has been identified as a threat to individual drivers and public health. Motor vehicle collisions remain a leading cause of death for children, yet little is known about distractions among drivers of children. This study sought to characterize potential distractions among drivers of children. MethodsA 2-site, cross-sectional, computerized survey of child passenger safety practices was conducted among adult drivers of 1- to 12-year-old children who presented for emergency care between October 2011 to May 2012. Drivers indicated the frequency with which they engaged in 10 potential distractions in the past month while driving with their child. Distractions were grouped in 4 categories: 1) nondriving, 2) cellular phone, 3) child, and 4) directions. Information about other unsafe driving behaviors and sociodemographic characteristics was collected. ResultsNearly 90% of eligible parents participated. Analysis included 570 drivers (92.2%). Non-driving-related and cellular phone–related distractions were disclosed by >75% of participants. Fewer participants disclosed child (71.2%) and directions-related distractions (51.9%). Child age was associated with each distraction category. Cellular phone–related distractions were associated with the child riding daily in the family car, non-Hispanic white, and higher education. Parents admitting to drowsy driving and being pulled over for speeding had over 2 times higher odds of disclosing distractions from each category. ConclusionsDistracted driving activities are common among drivers of child passengers and are associated with other unsafe driving behaviors. Child passenger safety may be improved by preventing crash events through the reduction or elimination of distractions among drivers of child passengers.