Innovative research on the topic areas of higher risk drivers and the implications for safety, education, and training. This collection spans a broad range of research methods and international contexts. Highlights include impact of covid-19, novel technologies, risky behaviors, and novel research methods (e.g. computational methods, naturalistic driving, administrative data linkage).
Exploratory Analysis of Young Adults’ Trajectories Through the UK Driving Licence Acquisition Process
Chenyang Wu (firstname.lastname@example.org), Southeast UniversityShow Abstract
Scott Le Vine, SUNY New Paltz
Aruna Sivakumar, Imperial College London
The UK is one of many high-income countries to experience a decline in driving licence acquisition among young adults in the 2000s. This paper draws on newly available nationally representative microdata that captures the progress of individual drivers through the UK driving test acquisition process, to establish socio-demographic correlates. Using data from the 2016/17 England’s National Travel Survey data, we first present a series of binary logit models to identify factors associated with progression through the various phases of the UK’s driving licence acquisition process. We then identify factors that are associated with (1) the frequency of taking the driving licence tests, (2) the number of times having failed the theory and driving tests. Our main finding is that socio-demographic factors appear to be relatively poor predictors of progress through the licence acquisition process, with employment status the strongest single correlate of the variables we tested. Age is negatively associated with progress through the early phases when respondents are applying for provisional licence and taking theory test, but this relationship turns positive in later stages of the acquisition process. To the authors’ knowledge, this study is the first opportunity to evaluate this novel data resource covering the UK’s driving licence acquisition process. It is hoped that this study provides insights for policymakers to understand young adults’ delay in acquiring licences, particularly the extent to which there may be structural inequalities.
Young Driver Survey
Kathy Sifrit, National Highway Traffic Safety Administration (NHTSA)Show Abstract
Christine Watson, National Highway Traffic Safety Administration (NHTSA)
Rory Austin (email@example.com), National Highway Traffic Safety Administration (NHTSA)
Motor vehicle crashes remain a leading cause of death among young people, and many factors influence young drivers’ elevated risk. To better understand these factors and to design more effective countermeasures to address them, the National Highway Traffic Safety Administration conducted a survey of the self-reported traffic safety behaviors, attitudes, and beliefs of young drivers. Between 2014 and 2017, the research team administered the Young Driver Survey to 17,698 drivers 16 to 21 years old in Florida, Georgia, Massachusetts, Nebraska, and Oklahoma. The survey sample was drawn from Department of Motor Vehicles’ databases. The sample included 17,698 respondents with a 22% response rate across the five States. Survey data were weighted to account for selection probabilities and to align the sample with each State’s demographic characteristics. Some young drivers reported risky behaviors like not wearing seat belts in back seats or reading and sending texts while driving, and young drivers who engaged in risky behaviors more frequently also reported more crashes. The frequency of young drivers’ risky or safe behaviors, attitudes, or beliefs often differed between sexes, ages, or geographic locations. While Graduated Driver Licensing (GDL) laws help reduce risk and exposure for all young drivers, these survey findings suggest that additional efforts focused on specific areas of risk for young drivers may improve safety. These efforts may include the GDL component of banning cell phone use by beginning drivers, high-visibility cell phone and text messaging ban enforcement, and communications and outreach to support speed enforcement.
The Effect of COVID-19 on Young Drivers in North Carolina and Implications for Policy
Natalie O'Brien (firstname.lastname@example.org), University of North CarolinaShow Abstract
Arthur Goodwin, University of North Carolina
Yudan Wang, North Carolina A&T State University
Kristel Robison, University of North Carolina
Bevan Kirley, University of North Carolina
Stephanie Harrell, University of North Carolina
COVID-19 and the response to contain the virus has had widespread impacts on travel behavior in the U.S. T he effect of COVID-19 on the safety of young drivers is not known. Preliminary data suggests overall crashes for young drivers dropped substantially between March and May; however, there may be other ways in which novice drivers are being negatively affected by the pandemic. Several states, including North Carolina, have waived their road-test requirement for new drivers, meaning teens can become licensed without proving their driving competence in a real-world setting. Although the intent is to fight the spread of the coronavirus (since physical distancing is not possible during a road test), waiving the test could result in greater numbers of unqualified new drivers. Young driver researchers also suspect COVID-19 has had a large impact on the amount of driving practice teens receive during the learner period. Research shows that most teen driving practice occurs during routine trips to school, extracurricular activities and other common destinations. With schools closed and most activities canceled, opportunities for driving practice have been severely curtailed. An additional issue posed by the pandemic is substantial delays in the licensing process for new drivers. Licensing offices are closed or have reduced hours. Moreover, driver education classes may be restricted or unavailable. Consequently, it is widely believed that rates of teen licensure have declined sharply during the pandemic. The objective of this project is to examine the impact of COVID-19 and the response to contain the virus on teen driver mobility and safety in North Carolina. Methods: To gain a comprehensive understanding of how the system is responding to the current pandemic, we are taking the following steps: Comparing driver licensing data for young drivers in North Carolina from January 1 to June 30, 2020 with historical averages. Comparing the number of teens who completed driver education classes in North Carolina from January 1 to June 30, 2020 with historical averages. Using preliminary 2020 NC crash data to assess the initial effects of the virus on young driver crash rates. Specifically, we are comparing the number and characteristics of crashes from January 1 to June 30, 2020 with historical averages. Collecting self-report data from parents of teen drivers in North Carolina via online questionnaires and focus groups to learn how COVID-19 has affected their supervised driving experience. Results: This study is currently underway with a completion date of December 31, 2020. Full results will be available for presentation at TRB in January 2021. Discussion: Results of this study will be important for identifying policy and other recommendations for addressing how the pandemic has influenced the mobility and safety of teenage drivers.
Establishing the Scientific Foundation for Driving Among Autistic Adolescents and Young Adults
Allison Curry (email@example.com), Children's Hospital of PhiladelphiaShow Abstract
Rachel Myers, CHOP
Meghan Carey, CHOP
Christina Labows, CHOP
Emma Sartin, Chopin Technologies
Kristina Metzger, Children's Hospital of Philadelphia
Catherine McDonald, University of Pennsylvania
Cynthia Mollen, Children's Hospital of Philadelphia
Sheila Klauer, Virginia Polytechnic Institute and State University (Virginia Tech)
Ben Yerys, Children's Hospital of Philadelphia
Potential Benefits of Case Management for Recidivist Traffic Offenders
Teresa Senserrick, Queensland University of TechnologyShow Abstract
Barry Watson, Queensland University of Technology
Background: Despite extensive penalties and sanctions, a small group of drivers persistently reoffend, contributing to many road injuries each year. While transport authority data identifies these drivers as predominantly male, young, low-socioeconomic area residents, and commonly unlicensed, wider research reveals strong links to general disadvantage. This includes low education, unemployment, cultural and ethnic minority backgrounds, and co-occurring personality, cognitive and/or mental health challenges. As such, an in-depth literature review was undertaken to explore whether adopting a case management approach – to work one-on-one with these individuals to address wider contributing factors – has potential to reduce reoffending and associated road trauma. Methods: Transport, science and education literature databases and key transport authority and research centre websites were searched during June-July 2019. As traffic offender literature mostly focused on driving-under-the-influence, a systematic search of interventions to reduce alcohol use was also undertaken, yielding 21 meta-analyses and 3 additional studies. Research quality was assessed via the Maryland Scale for Scientific Rigor (individual studies) or AMSTAR2 (systematic reviews). Results: Offender case management findings were predominantly based on violent, sex offender or mixed offender populations, but with overlapping predictive attributes to recidivist traffic offenders. Best-practice was identified as the Risk-Need-Responsivity (RNR) model, which focuses on identifying what risks the offender presents, what offender needs underlie these risks and what responsivity options, including psychology-based treatment tailored to the individual, will reduce reoffending. The focus is less on justice and deterrence models and more on respectful and otherwise ‘normal’ treatment of the individual, including addressing health and welfare needs, to address the underlying reasons for why they reoffend. More recent models were the Good Lives Model and, a hybrid of this and the RNR, the Risk-Need-Responsivity-Motivation model, which place more emphasis on boosting the individuals’ strengths to redirect them towards a ‘good life’. Traffic offender applications of case management were found only for driving-under-the-influence recidivists and associated with considerable reductions in recidivism, other convictions and prison time. Case management included a mix of individual and group-based therapies, education programs and intensive monitoring requirements, including alcohol interlocks, daily breath tests, alcohol monitoring bracelets and/or home confinement; commonly to reduce prison time, which also contributed to strong cost-benefits. Other supports included referrals to employment, education, financial, housing and legal services, and grief and domestic violence counselling. Several cognitive behavioural and motivation-based therapies showed success in reducing alcohol use, if not sobriety, offering ready options to include in case management initiatives. Discussion: The review provides strong support for implementing and evaluating a case management approach for recidivist traffic offenders, with many relevant programs and services already available. Addressing wider contributing health and welfare factors could result in both improved quality of life for the individuals and reduced road trauma, potentially resulting in considerable cost-benefits. In particular, early attention to young people failing to navigate through graduated driver licensing systems or repeatedly offending has potential to prevent a lifetime of disadvantage and recidivism. Better integration of overlapping roles in government departments of transport, justice, health and human services is likely needed.
Time-to-Collision Estimations Among Drivers with Developmental Disabilities: Learning Effects and Cognitive Factors
Austin Svancara (firstname.lastname@example.org), University of Alabama, BirminghamShow Abstract
Rajesh Kana, University of Alabama
Haley Bednarz, University of Alabama, Birmingham
Gabriela Sherrod, University of Alabama, Birmingham
Kristina Visscher, University of Alabama, Birmingham
Benjamin McManus, University of Alabama, Birmingham
Despina Stavrinos, University of Alabama, Birmingham
Background: Drivers with Autism Spectrum Disorder 1 (ASD) and Attention-Deficit/Hyperactivity Disorder 2 (ADHD) have a higher crash risk compared to typically developing (TD) individuals. The elevated crash risk may be due to their associated, but distinct, symptomologies (e.g., cognitive functioning 3,4 ). One aspect of driving not well-explored among drivers with developmental disabilities is the ability to judge time-to-collision (TTC), an important perceptual ability that precedes vehicle braking/maneuvering to avoid collisions. 5 Large TTC estimates could present potential safety risks to drivers. The goal of the present project was to examine TTC estimates among drivers with ASD and ADHD and the potential learning effects that may occur within a TTC estimation task, and to identify cognitive correlates of TTC estimations among these at-risk drivers. Methods: Fifty-five licensed drivers (n ASD = 16, n ADHD = 20, n TD = 19) were recruited into three age, gender, and IQ matched groups ( M age = 20.63, 60% male, M IQ = 107.89). Performance-based cognitive abilities were assessed using a Time Reproduction task (time perception [TP]), the Useful Field of View – Selective Attention subtest (selective attention [SA]), Wechsler Adult Intelligence Scale – Digit Span (working memory [WM]), Wechsler Abbreviated Scale of Intelligence – Vocabulary and Matrix Reasoning (intelligence [IQ]), and executive function (EF) was measured with the Behavior Rating Inventory of Executive Function – Self Report. Participants completed 60 trials on a TTC estimation task in a high-fidelity driving simulator (during half of the trials the vehicle moved 30mph and 60mph for the other half). As the participant moved forward, a vehicle would intermittently appear and disappear ahead of them. The gap between the participant and the moment of disappearance was the true TTC interval. Participants pressed a button when they thought a collision would have occurred had the target vehicle remained on screen. TTC accuracy (a ratio of the TTC estimate and the true TTC interval) was calculated for each TTC trial. Results: Drivers with ASD ( p <.001) and drivers with ADHD ( p <.001) reported greater EF difficulty compared to TD drivers, there were no differences on performance-based cognitive measures. A linear mixed regression revealed drivers with ASD produced larger TTC estimates over time (β=0.02, p =.040), and with higher speed (β=0.09, p =.013). Across all groups, higher TTC accuracy scores were significantly predicted by higher TP accuracy (β=0.05, p =.04), poorer SA (β=-0.05, p =.020), higher IQ (β=0.06, p =.008), and greater reported EF difficulty (β=0.11, p <.001). See Figure 1 and Table 1 to view group differences on all outcomes. Discussion: Drivers with ASD, compared to TD drivers, produced larger TTC estimates in the 60mph condition, which may present an area of safety concern for this group of vulnerable drivers. A larger TTC estimate may result in smaller windows for braking. Performance-based cognitive measures suggest higher cognitive functioning is associated with larger TTC estimates. Individuals with higher cognitive functioning may perceive themselves better capable to react to impending collisions. However, self-perceived EF difficulty is also related to larger TTC estimates. Future research should explore how individuals with higher and lower cognitive functioning use TTC information to inform their driving.
Attitudes and Beliefs that Influence Cell Phone Use among Young Drivers
Jordan Blenner (email@example.com), U.S. Department of TransportationShow Abstract
Nandi Taylor, University of North Carolina, Chapel Hill
Introduction: Young drivers are at major risk for injuries and fatalities due to distracted driving. This study focuses on different factors that affect distracted driving behavior among young drivers. Methods: We examined data from the 2015 National Survey on Distracted Driving Attitudes and Behaviors to measure the impact that demographic variables, social norms, likelihood to do or say something to others who are engaging in distracted driving, and perceived safety have on texting (reading and sending a text/email) and smartphone app use while driving. The population of interest was 16 to 24-year-old drivers. We analyzed the data using Rao-Scott chi-square tests and multivariate logistic regression models. By using sample weights, we created nationally representative estimates. Results: Young drivers reported engaging in distracted driving behavior while driving, with 42% reading a text, 33% sending a text, and 23% using their smartphone apps. Multivariate regression results revealed that perceived safety had the strongest association with cell phone use while driving. Sending a text/email was associated with social norms, whereas reading a text/email was associated with age-education. Conclusions: Self-reported engagement in distracted driving is associated with specific beliefs and demographics. Practical Applications: Young drivers’ engagement in cell phone use while driving may be reduced by focusing on ways to change social norms and perceived safety. Keywords: young drivers; distracted driving; cell phone use
Prediction of Drivers’ Willingness Not to Give Way to Ambulances: An Application of an Extended Theory of Planned Behavior
Xiaoxiao Wang (firstname.lastname@example.org), Wuhan UniversityShow Abstract
Not giving way to ambulances leads to delays in rescuing patients and sometimes may even cause traffic collisions, which is a public health issue of great concern in many countries including China. This study aimed to examine the socio-psychological factors underlying drivers’ willingness not to give way to ambulances on urban roads. Data were collected among 423 drivers by an online survey in China. A self-reported questionnaire based on an extended theory of planned behavior (TPB) model was used to measure drivers’ behavioral willingness, attitude, subjective norm, perceived behavioral control, moral norm, anticipated action regret, and anticipated inaction regret. Better-educated drivers had a lower willingness not to give way to ambulances ( M = 2.31, SD = 0.699 ) than less-educated ones ( M = 2.97, SD = 0.826 ); and drivers having emergency medical services (EMS) experiences using ambulances had a lower willingness not to give way to ambulances ( M = 2.37, SD = 0.732 ) than ones without related experiences ( M = 2.93, SD = 0.838 ). Attitude, perceived behavioral control, moral norm, anticipated action regret, and anticipated inaction regret were significant predictors of drivers’ willingness not to give way to ambulances, while subjective norm was not significant. The TPB was useful for understanding drivers’ willingness of not giving way to ambulances, and the extended TPB accounted for 61.5% of the variation. The findings can be used to design more effective interventions especially for driver education programs to improve drivers’ willingness of not giving way to ambulances on urban roads.
Using Pulse Rate Variability to Investigate Differences in Autonomic Processing of Hazards in Novice and Experienced Young Drivers
Theresa Chirles (email@example.com), Johns Hopkins UniversityShow Abstract
Johnathon Ehsani, Johns Hopkins University
Renee Ge, Johns Hopkins University School of Medicine
Karen Seymour, Johns Hopkins University School of Medicine
Neale Kinnear, TRL, Wokingham UK
Background: Young driver’s crash risk is highest during the first year of independent driving, largely due to inexperience and poor judgement. Previous research has shown that driving experiences result in the formation of somatic markers which bias the options available for decision-making (Bechara & Damasio, 2005), assisting the driver in avoiding crashes. Our prior work has shown experienced drivers are more likely to have a skin conductance response (SCR), a somatic marker indicating autonomic arousal, than novice drivers in the United Kingdom and the U.S. context (Kinnear et al., 2013, Chirles et al. 2020) when watching videos that included necessary action to avoid a driving hazard (event). The purpose of this study was to further investigate the role of the autonomic nervous system, using Pulse Rate Variability (PRV), when viewing driving videos. We hypothesized event videos would have greater measures of PRV across both groups, but that experienced drivers would exhibit greater measures of variability in the event and non-event (routine driving) videos. Methods: Novice and experienced drivers (16-20 years old) viewed a Driving Hazard Perception Task (Ehsani et al., 2020) while their pulse was measured using Biopac® photoplethysmograph equipment. Novice drivers had a learner’s permit and less than 1,000 miles driving experience, while experienced drivers had a driver’s license for at least 2 years and had driven more than 3,000 miles in the past 12 months. The Driving Hazard Perception Task presented 30 naturalistic driving videos, divided into 30-second event and non-event video clips. Event and non-event clips were presented in a random order, and the participants rated the likelihood of a crash occurring in each 30-second video. We extracted the R-R intervals across each video clip and calculated the standard deviation, mean, and root mean square of the intervals. We ran a mixed model analysis to investigate the effects of experience and video type on PRV. Results/Discussion: Pandemic-related disruptions to in-person research have limited our ability to complete data collection and complete the analyses. In-person research is now resuming, and the results and analysis will be completed for presentation at TRB in January 2021. Embodiment cognitive theory recognizes the role of the sensory-motor systems in judgement and decision making (Petracca, 2020). This research has the potential to further advance understanding of the influence of experience on the autonomic processes necessary for successful crash avoidance.
The Formation and Evolution of Mental Models in Drivers’ with Driver Assistance Technologies
Laura Mangus, WESTAT, Inc.Show Abstract
John Lenneman (firstname.lastname@example.org), Toyota Motor Corporation
James Jenness, WESTAT, Inc.
Driver assistance (DA) technologies (e.g., lane keeping) pose challenges to the formation and maintenance of drivers’ mental models (MM) of their operation, which may be overcome through consumer education and interface design strategies, but an understanding of how MMs for DA technologies form and evolve is needed. Therefore, we studied drivers’ experiences under extended real-world driving conditions for the purpose of delineating the formation and evolution of drivers’ MMs of DA technologies. Recent purchasers (n=52) of a vehicle with at least two DA technologies were interviewed approximately every two weeks for up to six months. Summary variables dependent on researchers’ interpretations of interview responses (all with inter-rater reliability of r > 0.6) were extracted and reduced using pre-defined criteria (e.g., MM complexity was rated low to high on a 5-point scale depending on the number of systems mentioned and the amount of detail/specificity provided). Other summary variables included:Functional accuracy of DA technology capabilities Accuracy of technology understanding Emotional valence Level of anthropomorphic orientation Level of mechanical orientation Questionnaire items completed at the first and last interviews included the Van Der Laan Scale of System Acceptance (measures satisfaction and usefulness) and questions about confidence in their knowledge of their vehicle’s DA technologies, feelings of importance in understanding how the system works, perceptions of system intuitiveness/difficulty, and trust in their vehicle’s DA technologies . To determine the evolution of drivers’ MMs over time, net changes in the summary variable ratings and participant responses from the first to the final interviews were calculated (e.g., final interview – first interview score). Finally, changes in summary variables and MM questionnaire items were compared to personality-related data collected during the first interview using the Hoyle Brief Sensation Seeking Scale (assesses thrill-seeking, general disinhibition), the Driver Behavior Questionnaire (assesses driving risk, errors, lapses, violations), and the Rotter Locus of Control scale (assesses internal vs. external locus of control) [2-4]. Comparisons between the first and last interviews revealed that as MM complexity increases so does the driver’s understanding of DA technology function. However, the results also revealed that an increase in MM complexity is accompanied by a decrease in trust in DA technologies Further, as accuracy of technology understanding increases, drivers’ ratings of their own knowledge of system capabilities and limitations decreases, possibly indicating that the more people learn, the more they realize there are things they do not know. Finally, personality related factors were shown to be correlated with MM evolution. The results indicated that thrill seeking individuals develop higher their functional accuracy and that individuals with external locus of controls will find DA technologies less intuitive over time. These results, and others to be presented, indicate that MM formation and evolution of DA technologies is a dynamic, complex process. However, with increasing complexity comes increasing opportunity to design future consumer education and design approaches for the purpose of facilitating safe and efficient use of DA technologies.
Optimization Method of Risk Driving Behavior Education and Training Based on Driver Type Classification: the Case of Mobile Phone Use While Driving
Xiaohua Zhao, Beijing University of TechnologyShow Abstract
Yang Ding, Beijing University of Technology
Yiping Wu (email@example.com), Beijing University of Technology
Yuan Yan, DiDi Chuxing
Cheng Gong, DiDi Chuxing
Yang Shi, DiDi Chuxing
Different drivers are motivated by different values and prefer to learn for different purposes. To improve the effectiveness of drivers’ education and training, a Targeted and Differentiated Optimization Method of Risk Driving Behavior Education and Training (TDOM-RDBET) considering the characteristics of driver types was developed in this study. On the basis of drivers’ risk value rankings, the high risk drivers were selected. Then by virtue of subjective questionnaire, the selected drivers were classified into four types: individualists with learning orientations, individualists with performance orientations, cooperators with learning orientations, and cooperators with performance orientations. Moreover, the corresponding feedback to different driver types targeting different risky driving behavior was designed. Then, the education and training dictionary [Editor’s note: The authors use the term “dictionary” to describe an education and training guide where the suitable feedback was designed corresponding to different driver types. ] was generated. Finally, the training effectiveness of TDOM-RDBET was assessed. Through the case study of mobile phone use while driving, the effectiveness of TDOM-RDBET was evaluated based on Didi platform (an online ride-hailing platform). The results of the evaluation test showed that the optimization method presented was more effective than the general training method. The results of this study could provide guidance for driving education and training targeting risky driving behavior.
Modelling the relationship between practical driving test faults and collision risk post-test
Neale Kinnear, TRL, Wokingham UKShow Abstract
Sritika Chowdhury, TRL
Caroline Wallbank, TRL
Shaun Helman, TRL
Sachin Mohanani, University of Warwick
Newly qualified drivers (especially young newly qualified drivers) have a much greater collision risk than is the case for drivers with greater experience. Research has shown that youthfulness and inexperience are the two key risk factors for road accidents in this group (Wells, Tong, Sexton, Grayson & Jones, 2008; Maycock, 2002; Forsyth, Maycock & Sexton, 1995; Maycock, Lockwood & Lester, 1991). Previous TRL modelling has demonstrated relationships between this collision risk and various variables describing the characteristics of newly qualified drivers; their exposure to the driving environment (both pre- and post-test); reported confidence and driving style (amongst others) (Wallbank et. al., 2017). This work extended this analysis to consider whether information on the faults that a novice driver obtained when they took their practical driving test could be used to predict future collision risk.
A Survey Study of Older Drivers in Illinois
Roshan Pokhrel, Southern Illinois University, EdwardsvilleShow Abstract
Yan Qi (firstname.lastname@example.org), Southern Illinois University, Edwardsville
Older population aged 65 or above are vulnerable in motor vehicle crashes due to the deterioration in their physical and health conditions. Quite a few studies have been conducted on senior people traffic safety, but, how older people driving habits and demographic characteristics are associated with their crashes or crash risks have not been fully investigated. Aimed to fill the knowledge gap, a survey was conducted among older drivers in IL and data on older people’s mobility need, driving habits, physical conditions, medication use, demographic characteristics, and crash experience were gathered. The odds ratio and logistic regression model were employed to analyze the survey data. The statistical analysis only found three significant variables, alcohol and medicine use as well as longer miles drove, which increased crash risk among older drivers. Surprisingly, a physician warning of the side effects of prescription drugs marginally increased older drivers’ crash risk. The study also found that Caucasians older drivers were less likely to be involved in motor vehicle crashes compared to other races. In addition, older female drivers and older drivers with a college education faced a lower crash risk.
Attribution Theory in Traffic Safety
Samia Akter, South Carolina State UniversityShow Abstract
Judith Mwakalonge, South Carolina State University
Gurcan Comert, Benedict College
Saidi Siuhi, South Carolina State University
Md Mahmud Hasan Mamun, Florida International University
Attribution theory refers to the psychological phenomenon where one person tries to perceive the cognitive behavior of others by ascribing his or her own emotions, opinions, and desires. For instance, during passing at an intersection, a driver expects that the maneuvering of other drivers coming from the opposite direction would be like own self. When expected behaviors do not match with future behaviors of the opposite driver, a collision is likely to occur. This study prepared a detailed review and investigated the application of the attribution theory to predict the opposing drivers' cognitive behavior and performance at highway intersections. This phenomenon was evaluated by utilizing the second Strategic Highway Research Program (SHRP-2) and National Highway Traffic Safety Administration (NHTSA) data sources. From the data analysis, it was observed that the driver ages 21-25 involved in the highest number of fatal accidents from 2009-2018 in the USA. It was found that the younger driver contributed less fatal collisions than an elderly driver. From simulation models, the impacts of attribution theory and driver age in the collision of highway intersection were examined.
A targeted internet-based intervention for novice driver offenders
Ian Faulks, Queensland University of TechnologyShow Abstract
A targeted online intervention developed for novice driver traffic offenders, the TOP ONLINE - Novice Driver Traffic Offender Unit, is described. It was found that the unit resulted in better targeting of young drivers who are traffic offenders, as well as addressing inefficiencies in program delivery and the operation of the Local Court-based Traffic Offender Intervention Program (TOIP) in New South Wales, Australia. Online provision provides high fidelity of content, accessibility, and self-paced learning. Field testing of the Unit was conducted over June 2017-March 2020, with standard roll-out subsequently due to the COVID-19 pandemic. In field testing, a pool of 439 novice driver traffic offenders were offered the online program. Not all offenders opted for an online course, more than one-third (41%) wanted to attend a face-to-face class. Not all offenders who registered for the online unit actually participated: 25% of offenders who registered did not log in and commence the course. However, almost all (95%) of offenders who commenced the program completed it satisfactorily. Overall, offenders reported that they enjoyed the flexibility of when, how and at what pace they accessed the unit, and avoiding having to travel to then venue for a face-to-face session. Offenders reported few negative aspects. With the onset of COVID-19 pandemic restrictions, face-to-face classes were discontinued, and subsequently all novice drivers now complete the online Unit as part of a general online program. Online learning for TOIP can provide a targeted approach to better address offenders’ risk, needs and responsivity to intervention.
Vehicle Access of Novice Teen Drivers and The Risk for Crash/Near-Crash Events
Pnina Gershon, Massachusetts Institute of Technology (MIT)Show Abstract
Johnathon Ehsani, Johns Hopkins University
Kellienne Sita, National Institutes of Health
Chunming Zhu, National Institutes of Health
Sheila Klauer, Virginia Polytechnic Institute and State University (Virginia Tech)
Tom Dingus, Virginia Polytechnic Institute and State University (Virginia Tech)
Bruce Simons-Morton, Virginia Polytechnic Institute and State University (Virginia Tech)
Introduction: To develop safe driving skills, novice teens need to drive to accumulate experience, at the same time crash risk increases the more one drives, so to what extent should extensive driving early in licensure be encouraged? This study examines the association between vehicle access, driving exposure, and the subsequent crash/near-crash risk during teens first year of independent driving. Methods: Real-world driving data were collected in a naturalistic cohort study of 82 newly-licensed teens (16.48 years-old, SD=0.33). Participants’ private vehicles were equipped with data acquisition systems that documented driving kinematics, miles driven, and video recordings of the driver and the driving environment. Vehicle access was determined by an objective evaluation of the primary vehicle user. A Multivariable Cox proportional hazard regression model was used to estimate adjusted hazard ratio [aHR] for a crash/near-crash event according to vehicle access. Results: During the first year of licensure, teens with primary vehicle access (67%) drove about five times more miles and had four times more crash/near-crash events than teens with shared access. While crash/near-crash rates per miles driven between groups were similar, the cumulated risk for crash/near-crash involvement was more than double for teens with primary compared to teens with shared vehicle access (aHR: 2.02, 95%CI: 1.14-3.57). Discussion: Novice teens learn to drive mainly through experience over time. Concentrated exposure early after licensure, which characterize teens with primary vehicle-access, is associated with elevate crash/near-crash risk. Parental involvement in titrating teens’ vehicle access at least during their first year of independent driving is recommended.
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