The relative odds of involvement in seven crash configurations by driver age and sex

Management of physical and psychological trauma resulting from motor vehicle crashes in Australian general practice: a mixed-methods approach

BACKGROUND

In Australia, motor vehicle crashes (MVC)-related health data are available from insurance claims and hospitals but not from primary care settings. This study aimed to identify the frequency of MVC-related consultations in Australian general practices, explore the pharmacological management of health conditions related to those crashes, and investigate general practitioners' (GPs) perceived barriers and enablers in managing these patients.

METHODS

Mixed-methods study. The quantitative component explored annual MVC-related consultation rates over seven years, the frequency of chronic pain, depression, anxiety or sleep issues after MVC, and management with opioids, antidepressants, anxiolytics or sedatives in a sample of 1,438,864 patients aged 16 + years attending 402 Australian general practices (MedicineInsight). Subsequently, we used content analysis of 81 GPs' qualitative responses to an online survey that included some of our quantitative findings to explore their experiences and attitudes to managing patients after MVC.

RESULTS

MVC-related consultation rates remained stable between 2012 and 2018 at around 9.0 per 10,000 consultations. In 2017/2018 compared to their peers, those experiencing a MVC had a higher frequency of chronic pain (48% vs. 26%), depression/anxiety (20% vs. 13%) and sleep issues (7% vs. 4%). In general, medications were prescribed more after MVC. Opioid prescribing was much higher among patients after MVC than their peers, whether they consulted for chronic pain (23.8% 95%CI 21.6;26.0 vs. 15.2%, 95%CI 14.5;15.8 in 2017/2018, respectively) or not (15.8%, 95%CI 13.9;17.6 vs. 6.7%, 95% CI 6.4;7.0 in 2017/2018). Qualitative analyses identified a lack of guidelines, local referral pathways and decision frameworks as critical barriers for GPs to manage patients after MVC. GPs also expressed interest in having better access to management tools for specific MVC-related consequences (e.g., whiplash/seatbelt injuries, acute/chronic pain management, mental health issues).

CONCLUSION

Chronic pain, mental health issues and the prescription of opioids were more frequent among patients experiencing MVC. This reinforces the relevance of appropriate management to limit the physical and psychological impact of MVC. GPs identified a lack of available resources (e.g. education, checklists and management support tools) for managing MVC-related consequences, and the need for local referral pathways and specific guidelines to escalate treatments.

Real-world crash configurations and traffic violations among newly licensed young drivers with different route familiarity levels

OBJECTIVE

Young drivers aged 24 and below are at heightened risks of being influenced by their route familiarity levels. This study aims to compare prevalences of crash culpability, crash configurations and risky driver behaviors among newly licensed young drivers when they are driving on roads with different route familiarity levels.

METHODS

Based on the road traffic crash and violation data in Yunnan Province of China from January 2017 through December 2019, we classified drivers' different route familiarity levels by utilizing spatial distance away from residence-based method, including driving on high route familiarity (HRF) and low route familiarity (LRF) roads. Prevalence ratios were estimated using generalized estimating equation log-binomial regression models.

RESULTS

We identified 12016 newly licensed young drivers driving on HRF roads and 2189 drivers on LRF roads. Within 48 months of licensure, young drivers on LRF roads were more likely to be at fault for their motor vehicle crashes than those on HRF roads. Young drivers on LRF roads were more likely to be with failure to obey traffic control device, with failure to yield right of way, wrong way driving, backing unsafely and improper parking compared with those on HRF roads. Drivers on LRF roads were less likely to be inattentive and driving with unsafe speed and following too closely compared with those on HRF roads.

CONCLUSIONS

Several basic aspects of targeted countermeasures can be put forward. Visual impacts such as rectangular rapid-flashing beacon (RRFB) can be used in order to prevent wrong way driving on the tourist roadways. Arranging safety talks and programs in colleges and universities and technical interventions like Advanced Driver Assistance Systems (ADAS) can be used to reduce young drivers' driving distraction and overconfidence. It is recommended that the driving schools can use these research findings to include in licensure program to make young drivers more aware of the various factors that expose them to crash risks so that more defensive driving may be needed under different situations, and this can also help build the graduated driving licensure (GDL) programme in China.

In-vehicle warnings for work zone and related rear-end collisions: A driving simulator experiment

Work zone area on roads is a critical component of road networks which concerns the safety of workers and passing by drivers. However, the passive speed reduction and lane changes caused by lane closure have led to frequent rear-end collisions in work zone areas. To help drivers better anticipate work zone situation and reduce collision risks, this paper proposes two types of in-vehicle warnings for work zone areas: Leading Vehicle Brake Warning (LVBW), and Lane-Closed Warning & Leading Vehicle Brake Warning (LCW & LVBW). The LVBW delivers a danger warning message to drivers upon the brake of the leading vehicle, while the LCW & LVBW provides an additional work-zone position message to remind drivers to decelerate in advance. A driving simulator experiment was conducted with 44 participants (24 males and 20 females) to test drivers' performance in work zone area under different conditions, comprising two warning types (LVBW vs. LCW & LVBW), four warning times (3 s, 5 s, 7 s and 9 s) and two visibility conditions (clear and foggy weather). The results showed significant safety benefits of the lane-closed warning message under the LCW & LVBW condition. In contrast, the warning of leading vehicle's brake in both LVBW and LCW & LVBW conditions had limited efficacy, which indicates that earlier warning about lane-closure is important to assist drivers in anticipating the complex situations in work zones. Drivers' speed control and collision avoidance performances were impaired in fog, but the impairment was compensated by the warning messages. Compared with male drivers, female drivers tend to be more cautious when approaching the work zone areas. Overall, this study plays a pioneering role in developing effective safety countermeasures for work zone areas and providing strong support for implementing in-vehicle warning technologies.

Novel use of a virtual driving assessment to classify driver skill at the time of licensure

Motor vehicle crash rates are highest immediately after licensure, and driver error is one of the leading causes. Yet, few studies have quantified driving skills at the time of licensure, making it difficult to identify at-risk drivers before independent driving. Using data from a virtual driving assessment implemented into the licensing workflow in Ohio, this study presents the first population-level study classifying degree of skill at the time of licensure and validating these against a measure of on-road performance: license exam outcomes. Principal component and cluster analysis of 33,249 virtual driving assessments identified 20 Skill Clusters that were then grouped into 4 major summary "Driving Classes"; i) No Issues (i.e. careful and skilled drivers); ii) Minor Issues (i.e. an average new driver with minor vehicle control skill deficits); iii) Major Issues (i.e. drivers with more control issues and who take more risks); and iv) Major Issues with Aggression (i.e. drivers with even more control issues and more reckless and risk-taking behavior). Category labels were determined based on patterns of VDA skill deficits alone (i.e. agnostic of the license examination outcome). These Skill Clusters and Driving Classes had different distributions by sex and age, reflecting age-related licensing policies (i.e. those under 18 and subject to GDL and driver education and training), and were differentially associated with subsequent performance on the on-road licensing examination (showing criterion validity). The No Issues and Minor Issues classes had lower than average odds of failing, and the other two more problematic Driving Classes had higher odds of failing. Thus, this study showed that license applicants can be classified based on their driving skills at the time of licensure. Future studies will validate these Skill Cluster classes in relation to their prediction of post-licensure crash outcomes.

Modelling the relationship of driver license and offense history with fatal and serious injury (FSI) crash involvement

INTRODUCTION

Previous research has indicated that increases in traffic offenses are linked to increased crash involvement rates, making reductions in offending an appropriate measure for evaluating road safety interventions in the short-term. However, the extent to which traffic offending predicts fatal and serious injury (FSI) crash involvement risk is not well established, prompting this new Victorian (Australia) study.

METHOD

A preliminary cluster analysis was performed to describe the offense data and assess FSI crash involvement risk for each cluster. While controlling demographic and licensing variables, the key traffic offenses that predict future FSI crash involvement were then identified. The large sample size allowed the use of machine learning methods such as random forests, gradient boosting, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. This was done for the 'all driver' sample and five sometimes overlapping groups of drivers; the young, the elderly, and those with a motorcycle license, a heavy vehicle license endorsement and/or a history of license bans.

RESULTS

With the exception of the group of drivers who had a history of bans, offense history significantly improved the accuracy of models predicting future FSI crash involvement using demographic and licensing data, suggesting that traffic offenses may be an important factor to consider when analyzing FSI crash involvement risk and the effects of road safety countermeasures.

CONCLUSIONS

The results are helpful for identifying driver groups to target with further road safety countermeasures, and for showing that machine learning methods have an important role to play in research of this nature. Practical Application: This research indicates with whom road safety interventions should particularly be applied. Changes to driver demerit policies to better target offenses related to FSI crash involvement and repeat traffic offenders, who are at greater risk of FSI crash involvement, are recommended.

Are there sex differences in crash and crash-related injury between men and women? A 13-year cohort study of young drivers in Australia

BACKGROUND

Young men have long been known to be disproportionately impacted by road crash and crash-related injury compared to young women and older drivers. However, there is limited insight into how sex differences in crash and crash-related injury changes over time as men and women get older and gain more driving experience. To explore sex differences in crash and crash-related injury, we undertook a sex disaggregated analysis in a large longitudinal cohort of over 20,000 young drivers in New South Wales, Australia, for up to 13 years after they first attained their independent car driver licence.

METHODS

DRIVE Study survey data from 2003-04 were linked with police, hospital and deaths data up to 2016. Sex differences were analysed using cumulative incidence curves investigating time to first crash and in negative binominal regression models adjusted for driver demographics and crash risk factors.

RESULTS

After adjusting for demographics and driving exposure, compared with women, men had 1.25 (95% CI 1.18-1.33), 2.07 (1.75-2.45), 1.28 (95% CI 1.13-1.46), 1.32 (95% CI 1.17-1.50) and 1.59 (95% CI 1.43-1.78) times higher rates of any crash, single vehicle crash, crash on streets with a speed limit of 80 km/h or above, crash in wet conditions and crash in the dark, respectively. By contrast, men were less likely to be involved in crashes that resulted in hospitalisation compared to women 0.73 (95% CI 0.55-0.96).

CONCLUSIONS

Young men are at increased risk of crash, and this risk persists as they get older and gain more driving experience. Despite lower risk of crash, women are at higher risk of crash related injury requiring hospitalisation. These differences in men's and women's risk of crash and injury signal the need for better understanding of how sex and/or gender may contribute to risk of crash and injury across the life-course.

The mediating effect of driver characteristics on risky driving behaviors moderated by gender, and the classification model of driver's driving risk

High-risk drivers are more likely to be involved in traffic accidents, and the driving risk level of drivers could be affected by many potential factors, such as demographics and personality traits. Based on the Structural Equation Model (SEM), this study involves a sample of 3150 drivers from the Strategic Highway Research Program 2 (SHRP 2), to explore the relationships among drivers' demographic characteristics (gender, age, and cumulative driving years), sensation seeking, risk perception, and risky driving behaviors. More specifically, the mediation model of driver characteristics on risky driving behaviors moderated by gender is constructed by the SEM. The results show that the effects of driving experience on risky driving behaviors are partially mediated by sensation seeking and risk perception for male drivers, while those are completely mediated by sensation seeking and risk perception for female drivers. Moreover, the development trend of risky driving behavior engagements declines greater with the growing of driving experience for female drivers than male drivers. Finally, a classification model of the driver's driving risk is proposed by the Random Forest classifier, in which the driving risk level of the driver evaluated by the crash and near-crash rate could be classified through the driver's self-reported demographics, sensation seeking, risk perception, and risky driving behaviors. The classification accuracy achieves up to 90 percent, which offers an alternative approach to identifying potential high-risk drivers to reduce property losses, injuries, and death caused by traffic accidents.

A systematic review of statistical models and outcomes of predicting fatal and serious injury crashes from driver crash and offense history data

BACKGROUND

Expenditure on driver-related behavioral interventions and road use policy is often justified by their impact on the frequency of fatal and serious injury crashes. Given the rarity of fatal and serious injury crashes, offense history, and crash history of drivers are sometimes used as an alternative measure of the impact of interventions and changes to policy. The primary purpose of this systematic review was to assess the rigor of statistical modeling used to predict fatal and serious crashes from offense history and crash history using a purpose-made quality assessment tool. A secondary purpose was to explore study outcomes.

METHODS

Only studies that used observational data and presented a statistical model of crash prediction from offense history or crash history were included. A quality assessment tool was developed for the systematic evaluation of statistical quality indicators across studies. The search was conducted in June 2019.

RESULTS

One thousand one hundred and five unique records were identified, 252 full texts were screened for inclusion, resulting in 20 studies being included in the review. The results indicate substantial and important limitations in the modeling methods used. Most studies demonstrated poor statistical rigor ranging from low to middle quality. There was a lack of confidence in published findings due to poor variable selection, poor adherence to statistical assumptions relating to multicollinearity, and lack of validation using new data.

CONCLUSIONS

It was concluded that future research should consider machine learning to overcome correlations in the data, use rigorous vetting procedures to identify predictor variables, and validate statistical models using new data to improve utility and generalizability of models.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019137081.

Simulator Pre-Screening of Underprepared Drivers Prior to Licensing On-Road Examination: Clustering of Virtual Driving Test Time Series Data

BACKGROUND

A large Midwestern state commissioned a virtual driving test (VDT) to assess driving skills preparedness before the on-road examination (ORE). Since July 2017, a pilot deployment of the VDT in state licensing centers (VDT pilot) has collected both VDT and ORE data from new license applicants with the aim of creating a scoring algorithm that could predict those who were underprepared.

OBJECTIVE

Leveraging data collected from the VDT pilot, this study aimed to develop and conduct an initial evaluation of a novel machine learning (ML)-based classifier using limited domain knowledge and minimal feature engineering to reliably predict applicant pass/fail on the ORE. Such methods, if proven useful, could be applicable to the classification of other time series data collected within medical and other settings.

METHODS

We analyzed an initial dataset that comprised 4308 drivers who completed both the VDT and the ORE, in which 1096 (25.4%) drivers went on to fail the ORE. We studied 2 different approaches to constructing feature sets to use as input to ML algorithms: the standard method of reducing the time series data to a set of manually defined variables that summarize driving behavior and a novel approach using time series clustering. We then fed these representations into different ML algorithms to compare their ability to predict a driver's ORE outcome (pass/fail).

RESULTS

The new method using time series clustering performed similarly compared with the standard method in terms of overall accuracy for predicting pass or fail outcome (76.1% vs 76.2%) and area under the curve (0.656 vs 0.682). However, the time series clustering slightly outperformed the standard method in differentially predicting failure on the ORE. The novel clustering method yielded a risk ratio for failure of 3.07 (95% CI 2.75-3.43), whereas the standard variables method yielded a risk ratio for failure of 2.68 (95% CI 2.41-2.99). In addition, the time series clustering method with logistic regression produced the lowest ratio of false alarms (those who were predicted to fail but went on to pass the ORE; 27.2%).

CONCLUSIONS

Our results provide initial evidence that the clustering method is useful for feature construction in classification tasks involving time series data when resources are limited to create multiple, domain-relevant variables.

Comparison of traffic collision victims between older and younger drivers in South Korea: Epidemiologic characteristics, risk factors and types of collisions

Objective

This study aimed to show the epidemiological characteristics and the difference in the risk factors and types of collision between older and younger drivers in Korea.

Methods

We collected data from the Emergency Department-based Injury In-depth Surveillance retrieved by the Korea Centers for Disease Control and Prevention from 2011 to 2015. We included injured drivers aged ≥ 18 years who were registered in the database, who were limited to drivers of four-wheeled vehicles. The enrolled patients were divided according to age into older (≥ 65 years) and younger (< 65 years) drivers. The total number of enrolled drivers was 37,511; 2,361 (6.3%) of them were older drivers. The epidemiological characteristics (e.g., age, sex, fatality rate) of traffic collision victims for 5 years were determined, and the risk factors (e.g., seat belt use) and types of collision (single- vs. multi-vehicle) between the two groups were compared.

Results

The median age and interquartile range (IQR; 25^th and 75^th percentiles) of all drivers were 41.0 (IQR, 32.0–52.0), and 24,544 (65.4%) of them were men. The median age increased from 40.0 (IQR, 31.0–50.0) to 43.0 (IQR, 33.0–54.0) between 2010 and 2015 (P < 0.001). The proportion of older drivers increased from 5.0% to 8.4% annually during the study period (P < 0.001). Between 2010 and 2015, the fatality rate decreased from 3.1% to 1.2% (P = 0.287) for older drivers and from 0.9% to 0.5% (P = 0.009) for younger drivers. The proportion of single-vehicle collision (25.9% vs. 20.3%) was higher in older than in younger drivers (P < 0.001). Older drivers had a lower rate of seat-belt use than younger drivers (79.0% vs. 83.0%, P < 0.001).

Conclusions

The proportion of older drivers increased annually during the study period, and older drivers experienced more single-vehicle collision and used seat belt less frequently than younger drivers. A national policy support to reduce traffic collision in older drivers and public relation activities to enhance their seat belt use should be strengthened in the future.

Crash risk by driver age, gender, and time of day using a new exposure methodology

INTRODUCTION

Concerns have been raised that the nonlinear relation between crashes and travel exposure invalidates the conventional use of crash rates to control for exposure. A new metric of exposure that bears a linear association to crashes was used as basis for calculating unbiased crash risks. This study compared the two methods - conventional crash rates and new adjusted crash risk - for assessing the effect of driver age, gender, and time of day on the risk of crash involvement and crash fatality.

METHOD

We used police reports of single-car and multi-car crashes with fatal and nonfatal driver injuries that occurred during 2002-2012 in Great Britain.

RESULTS

Conventional crash rates were highest in the youngest age group and declined steeply until age 60-69 years. The adjusted crash risk instead peaked at age 21-29 years and reduced gradually with age. The risk of nighttime driving, especially among teenage drivers, was much smaller when based on adjusted crash risks. Finally, the adjusted fatality risk incurred by elderly drivers remained constant across time of day, suggesting that their risk of sustaining a fatal injury due to a crash is more attributable to excess fragility than to crash seriousness.

CONCLUSIONS

Our findings demonstrate a biasing effect of low travel exposure on conventional crash rates. This implies that conventional methods do not yield meaningful comparisons of crash risk between driver groups and driving conditions of varying exposure to risk. The excess crash rates typically associated with teenage and elderly drivers as well as nighttime driving are attributed in part to overestimation of risk at low travel exposure. Practical Applications: Greater attention should be directed toward crash involvement among drivers in their 20s and 30s as well as younger drivers. Countermeasures should focus on the role of physical vulnerability in fatality risk of elderly drivers.

Comparison of crash rates and rear-end striking crashes among novice teens and experienced adults using the SHRP2 Naturalistic Driving Study

OBJECTIVE

Motor vehicle crashes are the leading cause of death for teens. Previous teen and adult crash rates have been based upon fatal crashes, police-reported crashes, and estimated miles driven. Large-scale naturalistic driving studies offer the opportunity to compute crash rates using a reliable methodology to capture crashes and driving exposure. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive real-world data on teen and adult driving. This article presents findings on the crash rates of novice teen and experienced adult drivers in naturalistic crashes.

METHODS

A subset from the SHRP2 database consisting of 539 crash events for novice teens (16-19 years, n = 549) and experienced adults (35-54 years, n = 591) was used. Onboard instrumentation such as scene cameras, accelerometers, and Global Positioning System logged time series data at 10 Hz. Scene videos were reviewed for all events to identify rear-end striking crashes. Dynamic variables such as acceleration and velocity were analyzed for rear-end striking events. Number of crashes, crash rates, rear-end striking crash severity, and rear-end striking impact velocity were compared between novice teens and experienced adults.

RESULTS

Video review of the SHRP2 crashes identified significantly more crashes (P < 0.01) and rear-end striking crashes (P < 0.01) among the teen group than among the adult group. This yielded crash rates of 30.0 crashes per million miles driven for novice teens compared to 5.3 crashes per million miles driven for experienced adults. The crash rate ratio for teens vs. adults was 5.7. The rear-end striking crash rate was 13.5 and 1.8 per million miles driven for novice teens and experienced adults, respectively. The rear-end striking crash rate ratio for teens vs. adults was 7.5. The rear-end striking crash severity measured by the accelerometers was greater (P < 0.05) for the teen group (1.8 ± 0.9 g; median = 1.6 g) than for the adult group (1.1 ± 0.4 g; median = 1.0 g), suggesting that teen crashes tend to be more serious than adult crashes. Increased rear-end striking impact velocity (P < 0.01) was also observed for novice teens (18.8 ± 13.2 mph; median = 18.9 mph) compared to experienced adults (3.3 ± 1.2 mph; median = 2.8 mph).

CONCLUSION

To our knowledge, this is the first study to compare crash rates between teens and adults using a large-scale naturalistic driving database. Unlike previous crash rates, the reported rates reliably control for crash type and driving exposure. These results conform to previous findings that novice teens exhibit increased crash rates compared to experienced adults.

Peer Passenger Norms and Pressure: Experimental Effects on Simulated Driving Among Teenage Males

OBJECTIVE

Serious crashes are more likely when teenage drivers have teenage passengers. One likely source of this increased risk is social influences on driving performance. This driving simulator study experimentally tested the effects of peer influence (i.e., risk-accepting compared to risk-averse peer norms reinforced by pressure) on the driving risk behavior (i.e., risky driving behavior and inattention to hazards) of male teenagers. It was hypothesized that peer presence would result in greater driving risk behavior (i.e., increased driving risk and reduced latent hazard anticipation), and that the effect would be greater when the peer was risk-accepting.

METHODS

Fifty-three 16- and 17-year-old male participants holding a provisional U.S., State of Michigan driver license were randomized to either a risk-accepting or risk-averse condition. Each participant operated a driving simulator while alone and separately with a confederate peer passenger. The simulator world included scenarios designed to elicit variation in driving risk behavior with a teen passenger present in the vehicle.

RESULTS

Significant interactions of passenger presence (passenger present vs. alone) by risk condition (risk-accepting vs. risk-averse) were observed for variables measuring: failure to stop at yellow light intersections (Incident Rate Ratio (IRR)=2.16; 95% Confidence Interval [95CI]=1.06, 4.43); higher probability of overtaking (IRR=10.17; 95CI=1.43, 73.35); shorter left turn latency (IRR=0.43; 95CI=0.31,0.60); and, failure to stop at an intersection with an occluded stop sign (IRR=7.90; 95CI=2.06,30.35). In all cases, greater risky driving by participants was more likely with a risk-accepting passenger versus a risk-averse passenger present and a risk-accepting passenger present versus driving alone.

CONCLUSIONS

Exposure of male teenagers to a risk-accepting confederate peer passenger who applied peer influence increased simulated risky driving behavior compared with exposure to a risk-averse confederate peer passenger or driving alone. These results are consistent with the contention that variability in teenage risky driving is in part explained by social influences.

Do as I say, not as I do: Distracted driving behavior of teens and their parents

INTRODUCTION

Driver distraction is an important contributor to crash risk. Teenage driver distraction can be influenced by the attitudes and behaviors of parents. This study examined teens' and their parents' engagement in distracting behavior while driving.

METHOD

Survey data were collected from a national sample of 403 parent-teen dyads using random-digit dialing telephone interviews.

RESULTS

Results demonstrated few parent or teen sex differences in distracting behavior engagement while driving, or in their perceptions of each others' behavior. Parents and teens' frequencies of distracting behavior engagement were positively correlated. Parents' and teens' perceptions of each others' distracting behavior engagement while driving exceeded their own selfreports. Finally, the likelihood that teens reported engaging in distracting behavior while driving was more strongly associated with their perceptions of their parents' distracting behavior than by parents' self reports of their own behavior.

CONCLUSIONS

These results suggest that parents' examples of driving behavior are an important influence on teen driving behavior, but potentially more important are teens' perceptions of their parents' behaviors.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

AIMS

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

METHODS

A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

RESULTS

Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

CONCLUSIONS

Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

Simulated Driving Assessment (SDA) for teen drivers: results from a validation study

BACKGROUND

Driver error and inadequate skill are common critical reasons for novice teen driver crashes, yet few validated, standardised assessments of teen driving skills exist. The purpose of this study is to evaluate the construct and criterion validity of a newly developed Simulated Driving Assessment (SDA) for novice teen drivers.

METHODS

The SDA's 35 min simulated drive incorporates 22 variations of the most common teen driver crash configurations. Driving performance was compared for 21 inexperienced teens (age 16-17 years, provisional license ≤90 days) and 17 experienced adults (age 25-50 years, license ≥5 years, drove ≥100 miles per week, no collisions or moving violations ≤3 years). SDA driving performance (Error Score) was based on driving safety measures derived from simulator and eye-tracking data. Negative driving outcomes included simulated collisions or run-off-the-road incidents. A professional driving evaluator/instructor (DEI Score) reviewed videos of SDA performance.

RESULTS

The SDA demonstrated construct validity: (1) teens had a higher Error Score than adults (30 vs. 13, p=0.02); (2) For each additional error committed, the RR of a participant's propensity for a simulated negative driving outcome increased by 8% (95% CI 1.05 to 1.10, p<0.01). The SDA-demonstrated criterion validity: Error Score was correlated with DEI Score (r=-0.66, p<0.001).

CONCLUSIONS

This study supports the concept of validated simulated driving tests like the SDA to assess novice driver skill in complex and hazardous driving scenarios. The SDA, as a standard protocol to evaluate teen driver performance, has the potential to facilitate screening and assessment of teen driving readiness and could be used to guide targeted skill training.

Comparison of teen and adult driver crash scenarios in a nationally representative sample of serious crashes

Motor vehicle crashes are the leading cause of death and acquired disability during the first four decades of life. While teen drivers have the highest crash risk, few studies examine the similarities and differences in teen and adult driver crashes. We aimed to: (1) identify and compare the most frequent crash scenarios-integrated information on a vehicle's movement prior to crash, immediate pre-crash event, and crash configuration-for teen and adult drivers involved in serious crashes, and (2) for the most frequent scenarios, explore whether the distribution of driver critical errors differed for teens and adult drivers. We analyzed data from the National Motor Vehicle Crash Causation Survey, a nationally representative study of serious crashes conducted by the U.S. National Highway Traffic Safety Administration from 2005 to 2007. Our sample included 642 16- to 19-year-old and 1167 35- to 54-year-old crash-involved drivers (weighted n=296,482 and 439,356, respectively) who made a critical error that led to their crash's critical pre-crash event (i.e., event that made the crash inevitable). We estimated prevalence ratios (PR) and 95% confidence intervals (CI) to compare the relative frequency of crash scenarios and driver critical errors. The top five crash scenarios among teen drivers, accounting for 37.3% of their crashes, included: (1) going straight, other vehicle stopped, rear end; (2) stopped in traffic lane, turning left at intersection, turn into path of other vehicle; (3) negotiating curve, off right edge of road, right roadside departure; (4) going straight, off right edge of road, right roadside departure; and (5) stopped in lane, turning left at intersection, turn across path of other vehicle. The top five crash scenarios among adult drivers, accounting for 33.9% of their crashes, included the same scenarios as the teen drivers with the exception of scenario (3) and the addition of going straight, crossing over an intersection, and continuing on a straight path. For two scenarios ((1) and (3) above), teens were more likely than adults to make a critical decision error (e.g., traveling too fast for conditions). Our findings indicate that among those who make a driver critical error in a serious crash, there are few differences in the scenarios or critical driver errors for teen and adult drivers.

Gender differences of young drivers on injury severity outcome of highway crashes

PROBLEM

Gender differences of young drivers involved in crashes and the associated differences in risk factors have not been fully explored in the United States (U.S.). Accordingly, this study investigated the topic, where the odds ratios (ORs) were used to identify differences in crash involvements between male and female young drivers.

METHOD

Logistic regression models for injury severity of young male drivers and young female drivers were developed. Different driver, environmental, vehicle, and road related factors that have affected young female drivers' and young male drivers' crash involvements were identified using the models.

RESULTS

Results indicated that some variables are significantly related to female drivers' injury risk but not male drivers' injury risk and vice versa. Variables such as driving with valid licenses, driving on weekends, avoidance or slow maneuvers at time of crash, non-collision and overturn crashes, and collision with a pedestrian were significant variables in female driver injury severity model but not in young male driver severity model. Travel on graded roadways, concrete surfaces, and wet road surfaces, collision with another vehicle, and rear-end collisions were variables that were significant in male-driver severity model but not in female-driver severity model.

SUMMARY

Factors which increase young female drivers' injury severity and young male drivers' injury severity were identified. This study adds detailed information about gender differences and similarities in injury severity risk of young drivers.

PRACTICAL APPLICATIONS

It is important to note that the findings of this study show that gender differences do exists among young drivers. This sends a message to the industry that the transportation professionals and researchers, who are developing countermeasures to increase the traffic safety, may need to pay attention to the differences. This might be particularly true when developing education materials for driver training for young/inexperienced drivers.

Social norms and risk perception: predictors of distracted driving behavior among novice adolescent drivers

PURPOSE

Adolescent drivers are at elevated crash risk due to distracted driving behavior (DDB). Understanding parental and peer influences on adolescent DDB may aid future efforts to decrease crash risk. We examined the influence of risk perception, sensation seeking, as well as descriptive and injunctive social norms on adolescent DDB using the theory of normative social behavior.

METHODS

403 adolescents (aged 16-18 years) and their parents were surveyed by telephone. Survey instruments measured self-reported sociodemographics, DDB, sensation seeking, risk perception, descriptive norms (perceived parent DDB, parent self-reported DDB, and perceived peer DDB), and injunctive norms (parent approval of DDB and peer approval of DDB). Hierarchical multiple linear regression was used to predict the influence of descriptive and injunctive social norms, risk perception, and sensation seeking on adolescent DDB.

RESULTS

92% of adolescents reported regularly engaging in DDB. Adolescents perceived that their parents and peers participated in DDB more frequently than themselves. Adolescent risk perception, parent DDB, perceived parent DDB, and perceived peer DDB were predictive of adolescent DDB in the regression model, but parent approval and peer approval of DDB were not predictive. Risk perception and parental DDB were stronger predictors among males, whereas perceived parental DDB was stronger for female adolescents.

CONCLUSIONS

Adolescent risk perception and descriptive norms are important predictors of adolescent distracted driving. More study is needed to understand the role of injunctive normative influences on adolescent DDB. Effective public health interventions should address parental role modeling, parental monitoring of adolescent driving, and social marketing techniques that correct misconceptions of norms related to around driver distraction and crash risk.