Higher crash and near-crash rates in teenaged drivers with lower cortisol response: an 18-month longitudinal, naturalistic study

Critical safety management driver identification based upon temporal variation characteristics of driving behavior

Identifying critical safety management drivers with high driver-level risks is essential for traffic safety improvement. Previous studies commonly evaluated driver-level risks based upon aggregated statistical characteristics (e.g., driving exposure and driving behavior), which were obtained from long-period driving monitoring data. However, given the great advancements of the connected vehicle and in-vehicle data instrumentation technologies, there has been a notable increase in the collection of short-period driving data, which has emerged as a prominent data source for analysis. In this data environment, traditionally employed aggregated behavior characteristics are unstable due to the time-varying feature of driving behavior coupled with insufficient data sampling periods. Thus, traditional modeling methods based upon aggregated statistical characteristics are no longer feasible. Instead of utilizing such unreliable statistical information to represent driver-level risks, this study employed temporal variation characteristics of driving behavior to identify critical safety management drivers in the short-period driving data environment. Specifically, the relationships between driving behavior temporal variation characteristics and individual crash occurrence probability were developed. To eliminate the impacts of drivers' driving behavior heterogeneity on model performance, "traffic entropy" index that could quantify the abnormal degrees of driving behavior was proposed. Deep learning models including convolutional neural network (CNN) and long short-term memory (LSTM) were employed to conduct the temporal variation feature mining. Empirical analyses were conducted using data obtained from online ride-hailing services. Experiment results showed that temporal variation characteristics based models outperformed traditional aggregated statistical characteristics based models. The area under the curve (AUC) index was improved by 4.1%. And the proposed traffic entropy index further enhanced the model performance by 5.3%. The best model achieved an AUC of 0.754, comparable to existing approaches utilizing long-period driving data. Finally, applications of the proposed method in driver management program development and its further investigations have been discussed.

Traffic safety and public health in China - Past knowledge, current status, and future directions

Transportation-related harms have developed into a social disease, threatening public safety and health in China. We aimed to increase the global understanding of traffic safety and public health in China from past knowledge, current status, and future directions by collecting, collating, and analyzing the Chinese traffic incidents reported in the published literature. A systematic search of China National Knowledge Infrastructure, Weipu, and published articles referenced in PubMed, Web of Science and ProQuest between January 1, 1988 and April 30, 2023 was performed. China encountered the first recorded traffic accident as early as three thousand years ago in the Shang Dynasty. An increase in vehicle capacity and velocity increased the traffic risks during the transition from rickshaws and livestock to motor vehicles in varying traffic environments. Humans are not only the decisive factor of a large number of vehicles, traffic routes, and environmental variables, but also the victims at the end and starting point of traffic accidents. Injuries (mechanical force, burns) and diseases (traffic-related air pollution, noise) caused by traffic activities not only threaten public health, but also cause risks to safe driving. Analysis of traffic activities and biomarkers promotes the treatment of traffic injuries in ethology and medicine. China prepared for the construction of healthy transportation in the "decade of road safety" toward an estimation of worldwide road traffic injuries in 2030. Improvement of traffic safety concerning public health under the "Outline of the National Comprehensive Three-dimensional Transportation Network Planning" in China will propel the realization of worldwide traffic environmental advancement.

Causation analysis of crashes and near crashes using naturalistic driving data

Understanding crash causation to the extent needed for applying countermeasures has always been a focus as well as a difficulty in the field of traffic safety. Previous research has been limited by insufficient crash data and analysis methods more suitable to single crashes. The use of crashes and near crashes (CNCs) and naturalistic driving studies can help solve the data problem, and use of pre-crash scenarios can identify the high-prevalence causes across multiple crashes of a given scenario. This study therefore proposes a two-stage crash causation analysis method based on pre-crash scenarios and a crash causation derivation framework that systematically categorizes and analyzes contributing factors. From the Shanghai Naturalistic Driving Study (SH-NDS), 536 CNCs were extracted, and were grouped into 23 different pre-crash scenarios based on the National Highway Traffic Safety Administration (NHTSA) pre-crash scenario typology. In-depth investigations were conducted, and CNCs sharing the same scenario were analyzed using the proposed framework, which identifies causation patterns based on the interaction of the framework's road user, vehicle, roadway infrastructure, and roadway environment subsystems. Through statistical analysis, the causation patterns and their contributing factors were compared for three common pre-crash scenarios of highest incidence: rear-end, lane change, and vehicle-pedalcyclist. Braking error in low-speed car following, following too closely, and non-driving-related distraction were important causes of rear-end scenarios. In lane change scenarios, the main causation patterns included illegal use of turn signals and dangerous lane changes as critical factors. Pedalcyclist scenarios were particularly impacted by visual obstructions, inadequate lanes for non-motorized vehicles, and pedalcyclists violating traffic regulations. Based on the identified causation patterns and their contributing factors, countermeasures for the three common scenarios are suggested, which provide support for safety improvement projects and the development of advanced driver assistance systems.

Quantifying the effect of roadway, driver, vehicle, and location characteristics on the frequency of longitudinal and lateral accelerations

The purpose of this study is to understand and quantify the simultaneous effects of roadway speed category, driver age, driver gender, vehicle class, and location on the rates of longitudinal and lateral acceleration epochs. The rate of usual as well as harsh acceleration epochs are used to extract insights on driving risk and driver comfort preferences. However, an analysis of acceleration rates at multiple thresholds incorporating various effects while using a large-scale and diverse dataset is missing. This analysis will fill this research gap. Data from the 2nd Strategic Highway Research Program Naturalistic Driving Study (SHRP2 NDS) was used for this analysis. The rate of occurrence of acceleration epochs was modeled using negative binomial distribution based generalized linear mixed effect models. Roadway speed category, driver age, driver gender, vehicle class, and location were used as the fixed effects and the driver identifier was used as the random effect. Incidence rate ratios were then calculated to compare subcategories of each fixed effect. Roadway speed category has the strongest effect on longitudinal and lateral accelerations of all magnitudes. Acceleration epoch rates consistently decrease as the roadway speed category increases. The difference in the rates depends on the threshold and is up to three orders of magnitude. Driver age is another significant factor with clear trends for longitudinal and lateral acceleration epochs. Younger and older drivers experience higher rates of longitudinal accelerations and decelerations. However, the rate of lateral accelerations consistently decreases with age. Vehicle class also has a significant effect on the rate of harsh accelerations with minivans consistently experiencing lower rates.

Decision-adjusted driver risk predictive models using kinematics information

Accurate prediction of driving risk is challenging due to the rarity of crashes and individual driver heterogeneity. One promising direction of tackling this challenge is to take advantage of telematics data, increasingly available from connected vehicle technology, to obtain dense risk predictors. In this work, we propose a decision-adjusted framework to develop optimal driver risk prediction models using telematics-based driving behavior information. We apply the proposed framework to identify the optimal threshold values for elevated longitudinal acceleration (ACC), deceleration (DEC), lateral acceleration (LAT), and other model parameters for predicting driver risk. The Second Strategic Highway Research Program (SHRP 2) naturalistic driving data were used with the decision rule of identifying the top 1% to 20% of the riskiest drivers. The results show that the decision-adjusted model improves prediction precision by 6.3% to 26.1% compared to a baseline model using non-telematics predictors. The proposed model is superior to models based on a receiver operating characteristic curve criterion, with 5.3% and 31.8% improvement in prediction precision. The results confirm that the optimal thresholds for ACC, DEC and LAT are sensitive to the decision rules, especially when predicting a small percentage of high-risk drivers. This study demonstrates the value of kinematic driving behavior in crash risk prediction and the necessity for a systematic approach for extracting prediction features. The proposed method can benefit broad applications, including fleet safety management, use-based insurance, driver behavior intervention, as well as connected-vehicle safety technology development.

An improved vehicle-pedestrian near-crash identification method with a roadside LiDAR sensor

PROBLEM

Potential conflicts between pedestrians and vehicles represent a challenge to pedestrian safety. Near-crash is used as a surrogate metric for pedestrian safety evaluations when historical vehicle-pedestrian crash data are not available. One challenge of using near-crash data for pedestrian safety evaluation is the identification of near-crash events.

METHOD

This paper introduces a novel method for pedestrian-vehicle near-crash identification that uses a roadside LiDAR sensor. The trajectory of each road user can be extracted from roadside LiDAR data via several data processing algorithms: background filtering, lane identification, object clustering, object classification, and object tracking. Three indicators, namely, the post encroachment time (PET), the proportion of the stopping distance (PSD), and the crash potential index (CPI) are applied for conflict risk classification.

RESULTS

The performance of the developed method was evaluated with field-collected data at four sites in Reno, Nevada, United States. The results of case studies demonstrate that pedestrian-vehicle near-crash events could be identified successfully via the proposed method. Practical applications: The proposed method is especially suitable for pedestrian-vehicle near-crash identification at individual sites. The extracted near-crash events can serve as supplementary material to naturalistic driving study (NDS) data for safety evaluation.

Crash rates over time among younger and older drivers in the SHRP 2 naturalistic driving study

OBJECTIVE

To examine crash rates over time among 16-17-year-old drivers compared to older drivers.

METHODS

Data were from a random sample of 854 of the 3,500 study participants in SHRP 2, a U.S. national, naturalistic driving (instrumented vehicle) study. Crashes/10,000 miles by driver age group, 3-month period, and sex were examined within generalized linear mixed models.

RESULTS

Analyses of individual differences between age cohorts indicated higher incidence rates in the 16-17-year old cohort relative to older age groups each of the first four quarters (except the first quarter compared to 18-20 year old drivers) with incident rate ratios (IRR) ranging from 1.98 to 18.90, and for the full study period compared with drivers 18-20 (IRR = 1.69, CI = 1.00, 2.86), 21 to 25 (IRR = 2.27, CI = 1.31, 3.91), and 35 to 55 (IRR = 4.00, CI = 2.28, 7.03). Within the 16-17-year old cohort no differences were found in rates among males and females and the decline in rates over the 24-month study period was not significant.

CONCLUSIONS

The prolonged period of elevated crash rates suggests the need to enhance novice young driver prevention approaches such as Graduated Driver's Licensing limits, parent restrictions, and post-licensure supervision and monitoring. Practical Applications: Increases are needed in Graduated Driver's Licensing limits, parent restrictions, and postlicensure supervision and monitoring.

Cortisol stress response predicts 9-year risky driving convictions in male first-time driving-while-impaired offenders

BACKGROUND

With driving while impaired by alcohol (DWI) representing a persistent burden on global health, better understanding and prevention of recidivism following a first-time DWI conviction are needed. Progress towards these goals is challenged by the marked heterogeneity in offender characteristics and a traffic safety literature that relies on subjective self-report measures and cross-sectional study designs. The present study tested the hypothesis that an objective neurobiological marker of behavioural maladjustment, the cortisol stress response (CSR), predicts future DWI and other traffic convictions over a 9-year follow-up period.

METHODS

One hundred thirty-two male first-time DWI offenders and 31 non-offender comparators were recruited and assessed at intake for their substance use, psychosocial and psychological characteristics and CSR. Traffic conviction data were obtained from provincial driving records. Survival analysis estimated the association between CSR and risk of a traffic conviction over time.

RESULTS

In support of our hypothesis, blunted CSR predicted traffic convictions during the follow-up duration. This effect generalized to both DWI offenders and non-DWI drivers. While CSR was lower in DWI offenders compared to non-offenders, it did not specifically predict recidivism in DWI offenders. Modelling results indicated that blunted CSR, along with DWI offender group membership, experience seeking and drug use frequency, may demarcate a high-risk driver phenotype.

CONCLUSIONS

CSR is a neurobiological marker of a driver phenotype with elevated generalized driving risk. For drivers with characteristics consistent with this phenotype, expanding the focus of intervention to address multiple forms of risky driving may be necessary to curb their overall threat to traffic safety.

Blunted stress reactivity reveals vulnerability to early life adversity in young adults with a family history of alcoholism

BACKGROUND AND AIMS

People with blunted stress reactivity have poor impulse control and also show increased risk for alcoholism. Exposure to early life adversity (ELA) contributes to blunted reactivity, but individual differences in susceptibility to ELA are not well understood. This study aimed to determine whether exposure to ELA has a greater impact on stress reactivity in young adults with a family history of alcoholism (FH+) compared with young adults with no family history of alcoholism (FH-).

DESIGN

Observational study using linear modeling.

SETTING

Oklahoma, USA.

PARTICIPANTS

Seven hundred and nine young adults (398 females) recruited through community advertisement.

MEASUREMENTS

We obtained heart rates and cortisol levels in subjects while undergoing public speaking and mental arithmetic stress compared with a resting control day (1418 test sessions). ELA was quantified as 0, 1 or > 1 adverse events experienced by age 15 years. FH+ people had one or two parents with an alcohol use disorder, and FH- controls had no such history for two generations.

FINDINGS

Increasing levels of ELA predicted progressive blunting of cortisol and heart rate reactivity for the whole sample (Fs = 4.57 and 4.70, Ps ≤ 0.011), but examination by FH status showed that the effect of ELA was significant only among FH+ (Fs ≥ 3.5, Ps < 0.05) and absent in FH- (Ps > 0.40). This difference in ELA impact was not explained by the cortisol diurnal cycle or subjective evaluation of the stressors.

CONCLUSIONS

People with a family history of alcoholism appear to be vulnerable, in terms of changes to physiological stress response, to the impact of exposure to early life adversity while people with no family history of alcoholism appear to be resilient. Blunted stress reactivity may reflect differential vulnerability to early life adversity in young adults with a family history of alcoholism.

The effects of age on crash risk associated with driver distraction

Background

Driver distraction is a major contributing factor to crashes, which are the leading cause of death for the US population under 35 years of age. The prevalence of secondary-task engagement and its impacts on distraction and crashes may vary substantially by driver age.

Methods

Driving performance and behaviour data were collected continuously using multiple cameras and sensors in situ for 3542 participant drivers recruited for up to 3 years for the Second Strategic Highway Research Program Naturalistic Driving Study. Secondary-task engagement at the onset of crashes and during normal driving segments was identified from videos. A case-cohort approach was used to estimate the crash odds ratios associated with, and the prevalence of, secondary tasks for four age groups: 16-20, 21-29, 30-64 and 65-98 years of age. Only severe crashes (property damage and higher severity) were included in the analysis.

Results

Secondary-task-induced distraction posed a consistently higher threat for drivers younger than 30 and above 65 when compared with middle-aged drivers, although senior drivers engaged in secondary tasks much less frequently than their younger counterparts. Secondary tasks with high visual-manual demand (e.g. visual-manual tasks performed on cell phones) affected drivers of all ages. Certain secondary tasks, such as operation of in-vehicle devices and talking/singing, increased the risk for only certain age groups.

Conclusions

Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers. Visual-manual distractions impact drivers of all ages, whereas cognitive distraction may have a larger impact on young drivers.

Blunted cortisol reactivity and risky driving in young offenders - a pilot study

Adolescent risky driving is a significant burden on public health. Young offenders (i.e. under custody and supervision of the criminal justice system) may be particularly vulnerable, but research is scant. Previous work indicated that blunted cortisol reactivity to stress is a marker of risk-taking predisposition, including risky driving. In this study, we hypothesized that young offenders display higher levels of risky driving than a non-offender comparison group, and that cortisol reactivity contributes to the variance in risky driving independent of other associated characteristics (i.e. impulsivity, risk taking, alcohol and drug use). We found that young offenders (n = 20) showed riskier driving in simulation than comparison group (n = 9), and blunted cortisol reactivity was significantly associated with risky driving. The results suggest young offenders are prone to risky driving, and that individual differences in the cortisol stress response may be an explanatory factor.

A validation of the low mileage bias using naturalistic driving study data

INTRODUCTION

This paper evaluated the low mileage bias (LMB) phenomenon for senior drivers using data mined from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. Supporters of the LMB construct postulate that it is only those seniors who drive the lowest annual mileage who are primarily responsible for the increased crash rates traditionally attributed to this population in general.

METHOD

The current analysis included 802 participants, all aged 65 or older who were involved in 163 property damage and injury crashes, and deemed to be at-fault in 123 (75%) of those instances. Poisson regression models were used to evaluate the association between annualized mileage driven and crash risk.

RESULTS

Results show that the crash rate for drivers with lower annualized mileage (i.e., especially for those driving fewer than approximately 3000miles per year) was significantly higher than that of drivers with higher annualized mileage, and that 25% of the overall sample were low- mileage drivers according to this criterion. Data were also evaluated by gender and meta-age group (i.e., younger-old: 65-74 and older-old: 75-99), and the results were consistent across these sub-groups.

CONCLUSIONS

This study provides strong support for the existence of the LMB.

PRACTICAL APPLICATIONS

These results can help to reshape how transportation safety stakeholders view senior drivers in general and help them to focus their efforts on those seniors most in need of either risk-reducing countermeasures or alternative means of transportation.

Evaluation of risk change-point for novice teenage drivers

The driving risk of novice teenagers is the highest during the initial period after licensure but decreases rapidly. This paper applies two recurrent-event change-point models to detect the time of change in driving risks. The models are based on a non-homogeneous Poisson process with piecewise constant intensity functions. We show that the maximum likelihood estimators of the change-points can only occur at the event times and they are consistent. A simulation study is conducted to demonstrate the model performance under different scenarios. The proposed models are applied to the Naturalistic Teenage Driving Study, which continuously recorded in situ driving behaviour of 42 novice teenage drivers for the first 18 months after licensure using sophisticated in-vehicle instrumentation. The results indicate that approximately half of the drivers have lower risk after 73.0h of independent driving after licensure while the risk for others increases. On the average the driving risk deceases after the change-point. The results provide critical information for safety education, safety countermeasure development, and Graduated Driver Licensing policy making.

A Bayesian finite mixture change-point model for assessing the risk of novice teenage drivers

The driving risk during the initial period after licensure for novice teenage drivers is typically the highest but decreases rapidly right after. The change-point of driving risk is a critical parameter for evaluating teenage driving risk, which also varies substantially among drivers. This paper presents latent class recurrent-event change-point models for detecting the change-points. The proposed model is applied to the Naturalist Teenage Driving Study, which continuously recorded the driving data of 42 novice teenage drivers for 18 months using advanced in-vehicle instrumentation. We propose a hierarchical BFMM to estimate the change-points by clusters of drivers with similar risk profiles. The model is based on a non-homogeneous Poisson process with piecewise-constant intensity functions. Latent variables which identify the membership of the subjects are used to detect potential clusters among subjects. Application to the Naturalistic Teenage Driving Study identifies three distinct clusters with change-points at 52.30, 108.99 and 150.20 hours of driving after first licensure, respectively. The overall intensity rate and the pattern of change also differ substantially among clusters. The results of this research provide more insight in teenagers' driving behaviour and will be critical to improve young drivers' safety education and parent management programs, as well as provide crucial reference for the GDL regulations to encourage safer driving.

Road safety and road traffic accidents in Saudi Arabia. A systematic review of existing evidence

OBJECTIVES

To identify the changing trends and crucial preventive approaches to road traffic accidents (RTAs) adopted in the Kingdom of Saudi Arabia (KSA) over the last 2.5 decades, and to analyze aspects previously overlooked.

METHODS

This systematic review was based on evidence of RTAs in KSA. All articles published during the last 25 years on road traffic accident in KSA were analyzed. This study was carried out from December 2013 to May 2014 in the Department of Family and Community Medicine, Taibah University, Al-Madinah Al-Munawwarah, KSA.

RESULTS

Road traffic accidents accounted for 83.4% of all trauma admissions in 1984-1989, and no such overall trend was studied thereafter. The most frequently injured body regions as reported in the latest studies were head and neck, followed by upper and lower extremities, which was found to be opposite to that of the studies reported earlier. Hospital data showed an 8% non-significant increase in road accident mortalities in contrast to police records of a 27% significant reduction during the years 2005-2010. Excessive speeding was the most common cause reported in all recent and past studies.

CONCLUSION

Disparity was common in the type of reporting of RTAs, outcome measures, and possible causes over a period of 2.5 decade. All research exclusively looked into the drivers' faults. A sentinel surveillance of road crashes should be kept in place in the secondary and tertiary care hospitals for all regions of KSA.

Learning to Drive Safely: Reasonable Expectations and Future Directions for the Learner Period

The young driver problem is typified by high crash rates early in licensure that decline with experience, but are higher initially and decline more slowly for the youngest novices. Despite considerable effort, only Graduated Driver Licensing System (GDLS) policies have been shown to improve novice young driver safety outcomes. Unfortunately, GDLS policies are mostly limited to countries with a relatively young licensure age. Meanwhile, it is not entirely clear how GDLS and other young driver transportation safety efforts, including driver training and testing, supervised practice and parental management of young drivers, can best be configured. Notably, professional training can foster improvements in vehicle management skills that are necessary, but do not assure safe driving behavior. Substantial recent research has focused on training methods to improve driving skills, but the safety benefits of driver training have not been established. While prolonged practice driving increases experience and provides supervisors with opportunities to prepare novices for independent driving, the transition to independent driving challenges novices to employ, on their own, poorly-mastered skills under unfamiliar and complex driving conditions. Licensing policies and parental management practices can limit the complexity of driving conditions while novices gain needed driving experience. Nevertheless, an emerging body of literature suggests that future advances in training and supervision of novice teenage drivers might best focus on the translation of learning to independent driving by fostering safe driving attitudes and norms, judgment, dedicated attention to driving tasks and self-control at the wheel.

Off-Road Vehicle Crash Risk during the Six Months after a Birthday

Background

Off-road vehicles are popular and thrilling for youth outside urban settings, yet sometimes result in a serious crash that requires emergency medical care. The relation between birthdays and the subsequent risk of an off-road vehicle crash is unknown.

Methods

We conducted a population-based before-and-after longitudinal analysis of youth who received emergency medical care in Ontario, Canada, due to an off-road vehicle crash between April 1, 2002, and March 31, 2014. We identified youth injured in an off-road vehicle crash through population-based health-care databases of individuals treated for medical emergencies. We included youth aged 19 years or younger, distinguishing juniors (age ≤ 15 years) from juveniles (age ≥ 16 years).

Results

A total 32,777 youths accounted for 35,202 emergencies due to off-road vehicle crashes within six months of their nearest birthday. Comparing the six months following a birthday to the six months prior to a birthday, crashes increased by about 2.7 events per 1000 juniors (18.3 vs 21.0, p < 0.0001). The difference equaled a 15% increase in relative risk (95% confidence interval 12 to 18). The increase extended for months following a birthday, was not observed for traffic crashes due to on-road vehicles, and was partially explained by a lack of helmet wearing. As expected, off-road crash risks did not change significantly following a birthday among juveniles (19.2 vs 19.8, p = 0.61).

Conclusions

Off-road vehicle crashes leading to emergency medical care increase following a birthday in youth below age 16 years. An awareness of this association might inform public health messages, gift-giving practices, age-related parental permissions, and prevention by primary care physicians.

The influence of daily sleep patterns of commercial truck drivers on driving performance

Fatigued and drowsy driving has been found to be a major cause of truck crashes. Lack of sleep is the number one cause of fatigue and drowsiness. However, there are limited data on the sleep patterns (sleep duration, sleep percentage in the duration of non-work period, and the time when sleep occurred) of truck drivers in non-work periods and the impact on driving performance. This paper examined sleep patterns of 96 commercial truck drivers during non-work periods and evaluated the influence these sleep patterns had on truck driving performance. Data were from the Naturalistic Truck Driving Study. Each driver participated in the study for approximately four weeks. A shift was defined as a non-work period followed by a work period. A total of 1397 shifts were identified. Four distinct sleep patterns were identified based on sleep duration, sleep start/end point in a non-work period, and the percentage of sleep with reference to the duration of non-work period. Driving performance was measured by safety-critical events, which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Negative binomial regression was used to evaluate the association between the sleep patterns and driving performance, adjusted for driver demographic information. The results showed that the sleep pattern with the highest safety-critical event rate was associated with shorter sleep, sleep in the early stage of a non-work period, and less sleep between 1 a.m. and 5 a.m. This study also found that male drivers, with fewer years of commercial vehicle driving experience and higher body mass index, were associated with deteriorated driving performance and increased driving risk. The results of this study could inform hours-of-service policy-making and benefit safety management in the trucking industry.

Personality, Executive Control, and Neurobiological Characteristics Associated with Different Forms of Risky Driving

Background

Road crashes represent a huge burden on global health. Some drivers are prone to repeated episodes of risky driving (RD) and are over-represented in crashes and related morbidity. However, their characteristics are heterogeneous, hampering development of targeted intervention strategies. This study hypothesized that distinct personality, cognitive, and neurobiological processes are associated with the type of RD behaviours these drivers predominantly engage in.

Methods

Four age-matched groups of adult (19–39 years) males were recruited: 1) driving while impaired recidivists (DWI, n = 36); 2) non-alcohol reckless drivers (SPEED, n = 28); 3) drivers with a mixed RD profile (MIXED, n = 27); and 4) low-risk control drivers (CTL, n = 47). Their sociodemographic, criminal history, driving behaviour (by questionnaire and simulation performance), personality (Big Five traits, impulsivity, reward sensitivity), cognitive (disinhibition, decision making, behavioural risk taking), and neurobiological (cortisol stress response) characteristics were gathered and contrasted.

Results

Compared to controls, group SPEED showed greater sensation seeking, disinhibition, disadvantageous decision making, and risk taking. Group MIXED exhibited more substance misuse, and antisocial, sensation seeking and reward sensitive personality features. Group DWI showed greater disinhibition and more severe alcohol misuse, and compared to the other RD groups, the lowest level of risk taking when sober. All RD groups exhibited less cortisol increase in response to stress compared to controls.

Discussion

Each RD group exhibited a distinct personality and cognitive profile, which was consistent with stimulation seeking in group SPEED, fearlessness in group MIXED, and poor behavioural regulation associated with alcohol in group DWI. As these group differences were uniformly accompanied by blunted cortisol stress responses, they may reflect the disparate behavioural consequences of dysregulation of the stress system. In sum, RD preference appears to be a useful marker for clarifying explanatory pathways to risky driving, and for research into developing more personalized prevention efforts.

Naturalistic teenage driving study: Findings and lessons learned

INTRODUCTION

This paper summarizes the findings on novice teenage driving outcomes (e.g., crashes and risky driving behaviors) from the Naturalistic Teenage Driving Study.

METHOD

Survey and driving data from a data acquisition system (global positioning system, accelerometers, cameras) were collected from 42 newly licensed teenage drivers and their parents during the first 18 months of teenage licensure; stress responsivity was also measured in teenagers.

RESULT

Overall teenage crash and near-crash (CNC) rates declined over time, but were >4 times higher among teenagers than adults. Contributing factors to teenage CNC rates included secondary task engagement (e.g., distraction), kinematic risky driving, low stress responsivity, and risky social norms.

CONCLUSIONS

The data support the contention that the high novice teenage CNC risk is due both to inexperience and risky driving behavior, particularly kinematic risky driving and secondary task engagement.

PRACTICAL APPLICATIONS

Graduated driver licensing policy and other prevention efforts should focus on kinematic risky driving, secondary task engagement, and risky social norms.

Lower Cortisol Activity is Associated with First-Time Driving while Impaired

Driving while impaired (DWI) is a grave and persistent high-risk behavior. Previous work demonstrated that DWI recidivists had attenuated cortisol reactivity compared to non-DWI drivers. This suggests that cortisol is a neurobiological marker of high-risk driving. The present study tested the hypothesis that this initial finding would extend to first-time DWI (fDWI) offenders compared to non-DWI drivers. Male fDWI offenders (n = 139) and non-DWI drivers (n = 31) were exposed to a stress task, and their salivary cortisol activity (total output and reactivity) was measured. Participants also completed questionnaires on sensation seeking, impulsivity, substance use, and engagement in risky and criminal behaviors. As hypothesized, fDWI offenders, compared to non-DWI drivers, had lower cortisol reactivity; fDWI offenders also showed lower total output. In addition, cortisol activity was the most important predictor of group membership, after accounting for alcohol misuse patterns and consequences and other personality and problem behavior characteristics. The findings indicate that attenuated cortisol activity is an independent factor associated with DWI offending risk at an earlier stage in the DWI trajectory than previously detected.