Examining the nonparametric effect of drivers' age in rear-end accidents through an additive logistic regression model

Women and insurance pricing policies: a gender-based analysis with GAMLSS on two actuarial datasets

In most of the United States, insurance companies may use gender to determine car insurance rates. In addition, several studies have shown that women over the age of 25 generally pay more than men for car insurance. Then, we investigate whether the distributions of claims for women and men differ in location, scale and shape by means of the GAMLSS regression framework, using microdata provided by U.S. and Australian insurance companies, to use this evidence to support policy makers' decisions. We also develop a parametric-bootstrap test to investigate the tail behavior of the distributions. When covariates are not considered, the distribution of claims does not appear to differ by gender. When covariates are included, the regressions provide mixed evidence for the location parameter. However, for female claimants, the spread of the distribution is lower. Our research suggests that, at least for the contexts analyzed, there is no clear statistical reason for charging higher rates to women. While providing evidence to support unisex insurance pricing policies, given the limitations represented by the use of country-specific data, this paper aims to promote further research on this topic with different datasets to corroborate our findings and draw more general conclusions.

Applying the heteroskedastic ordered probit model on injury severity for improved age and gender estimation

OBJECTIVE

Driver characteristics have been linked to the frequency and severity of car crashes. Among these, age and gender have been shown to impact both the possibility and severity of a crash. Previous studies have used standard ordered probit (OP) models to analyze crash data, and some research has suggested heteroskedastic ordered probit (HETOP) could provide improved model fit. The objective of this paper is to evaluate potential improvements of the heteroskedastic ordered probit (HETOP) model compared to the standard ordered probit (OP) model in crash analysis, by examining the effect of gender across age on injury severity among drivers. This paper hypothesizes that the HETOP model can provide a better fit to crash data, by allowing heteroskedasticity in the distribution of injury severity across driver age and gender.

METHODS

Data for 20,222 crashes were analyzed for North Carolina from 2016 to 2018, which represents the state with the highest number of fatalities per 100 million vehicle miles traveled amongst available crash data from the Highway Safety Information System.

RESULTS

Darker lighting conditions, severe road surface conditions, and less severe weather were associated with increased injury severity. For driver demographics, the probability of severe injuries increased with age and for male drivers. Moreover, the variance of severity increased with age disproportionately within and across genders, and the HETOP was able to account for this.

CONCLUSIONS

The results of the two applied approaches revealed that HETOP model outperformed the standard OP model when measuring the effects of age and gender together in injury severity analysis, due to the heteroskedasticity in injury severity within gender and age. The HETOP statistical method presented in this paper can be more broadly applied across other contexts and combinations of independent variables for improved model prediction and accuracy of causal variables in traffic safety.

Sociodemographic characteristics of youth licensing at age 17 in the context of supervised driving in Denmark

INTRODUCTION

Allowing young drivers to gain experience while being supervised by an experienced driver is a widely used measure to try to reduce crash risk. On 1 January 2017, the Danish licensing system was updated to allow licensing at age 17 with post-license supervised driving until solo driving at age 18.

METHOD

Based on data from the Danish Driving License register and Statistics Denmark, including the entire population, the purpose of this study is to determine if sociodemographic characteristics and a history of violations and crash involvement among youth predict licensing at age 17. A second purpose is to estimate the time period from licensing until the driver turns 18 and to explore changes in license demand in the context of Denmark's updated licensing system.

RESULTS

An increasing proportion choose to license at the age of 17, but the proportion below 19 with a driver's license is unchanged. On average, the license is obtained 5.3 months before turning 18. Living in rural areas, with both parents, and in a family with several cars and higher income increases the likelihood of licensing at age 17. Young people with a history of involvement in non-traffic-related accidents or violations are more likely to license at age 17.

CONCLUSION

Lowering the license age to allow supervised driving increases early licensing. The average time period from licensing until the driver turns 18 is less than six months. Sociodemographic characteristics predict early licensing.

PRACTICAL IMPLICATIONS

Minimum requirements for the time period from licensing until the driver turns 18 are needed to support a safety benefit. Follow-up studies mapping supervised driving, crash involvement, and possible changes in crash risk associated with the change in the Danish licensing system are needed to specify the requirements.

Exploring the effect of road network, demographic, and land use characteristics on teen crash frequency using geographically weighted negative binomial regression

Motor vehicle crashes are one of the leading causes of teen deaths worldwide. It is important to assess the environment and identify the risk factors influencing teen crashes for planning strategies and improving their safety. This research, therefore, focuses on exploring the effect of road network, demographic, and land use characteristics to compute teen crash frequency. Data for 201 spatially distributed road segments in Mecklenburg County, North Carolina, USA were considered for the evaluation. Data related to teen crashes were obtained from the Highway Safety Information System (HSIS). Demographic and land use characteristics were extracted around each selected road segment using two different buffer widths (0.25 miles and 0.5 miles). Teen crash frequency of each road segment was used as the dependent variable. The generalized linear models with the negative binomial distribution (GLM-based NB model) and geographically weighted negative binomial regression models (GWNBR and GWNBRg) were developed and compared. The annual average daily traffic (AADT), light commercial land use, number of household units, and number of pupils enrolled in public or private high schools are significant explanatory variables influencing teen crash frequency. Both methods have good predictive capabilities and can be used to compute teen crash frequency. However, the GWNBR and GWNBRg better capture the spatial dependency and spatial heterogeneity of associated risk factors influencing teen crash frequency.

Restoration of DNA integrity and cell cycle by electric stimulation in planarian tissues damaged by ionizing radiation

Exposure to high levels of ionizing γ-radiation leads to irreversible DNA damage and cell death. Here, we establish that exogenous application of electric stimulation enables cellular plasticity to reestablish stem cell activity in tissues damaged by ionizing radiation. We show that sub-threshold direct current stimulation (DCS) rapidly restores pluripotent stem cell populations previously eliminated by lethally γ-irradiated tissues of the planarian flatworm Schmidtea mediterranea. Our findings reveal that DCS enhances DNA repair, transcriptional activity, and cell cycle entry in post-mitotic cells. These responses involve rapid increases in cytosolic [Ca2+] through the activation of L-type Cav channels and intracellular Ca2+ stores leading to the activation of immediate early genes and ectopic expression of stem cell markers in postmitotic cells. Overall, we show the potential of electric current stimulation to reverse the damaging effects of high dose γ-radiation in adult tissues. Furthermore, our results provide mechanistic insights describing how electric stimulation effectively translates into molecular responses capable of regulating fundamental cellular functions without the need for genetic or pharmacological intervention.

Using Speech Data From Interactions With a Voice Assistant to Predict the Risk of Future Accidents for Older Drivers: Prospective Cohort Study

Background

With the rapid growth of the older adult population worldwide, car accidents involving this population group have become an increasingly serious problem. Cognitive impairment, which is assessed using neuropsychological tests, has been reported as a risk factor for being involved in car accidents; however, it remains unclear whether this risk can be predicted using daily behavior data.

Objective

The objective of this study was to investigate whether speech data that can be collected in everyday life can be used to predict the risk of an older driver being involved in a car accident.

Methods

At baseline, we collected (1) speech data during interactions with a voice assistant and (2) cognitive assessment data—neuropsychological tests (Mini-Mental State Examination, revised Wechsler immediate and delayed logical memory, Frontal Assessment Battery, trail making test-parts A and B, and Clock Drawing Test), Geriatric Depression Scale, magnetic resonance imaging, and demographics (age, sex, education)—from older adults. Approximately one-and-a-half years later, we followed up to collect information about their driving experiences (with respect to car accidents) using a questionnaire. We investigated the association between speech data and future accident risk using statistical analysis and machine learning models.

Results

We found that older drivers (n=60) with accident or near-accident experiences had statistically discernible differences in speech features that suggest cognitive impairment such as reduced speech rate (P=.048) and increased response time (P=.040). Moreover, the model that used speech features could predict future accident or near-accident experiences with 81.7% accuracy, which was 6.7% higher than that using cognitive assessment data, and could achieve up to 88.3% accuracy when the model used both types of data.

Conclusions

Our study provides the first empirical results that suggest analysis of speech data recorded during interactions with voice assistants could help predict future accident risk for older drivers by capturing subtle impairments in cognitive function.

Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes

A rear-end crash is a widely studied type of road accident. The road area at the crash scene is a factor that significantly affects the crash severity from rear-end collisions. These road areas may be classified as urban or rural and evince obvious differences such as speed limits, number of intersections, vehicle types, etc. However, no study comparing rear-end crashes occurring in urban and rural areas has yet been conducted. Therefore, the present investigation focused on the comparison of diverse factors affecting the likelihood of rear-end crash severities in the two types of roadways. Additionally, hierarchical logistic models grounded in a spatial basis concept were applied by determining varying parameter estimations with regard to road segments. Additionally, the study compared coefficients with multilevel correlation model and those without multilevel correlation. Four models were established as a result. The data used for the study pertained to rear-end crashes occurring on Thai highways between 2011 and 2015. The results of the data analysis revealed that the model parameters for both urban and rural areas are in the same direction with the larger number of significant parameter values present in the rural rear-end crash model. The significant variables in both the urban and rural road segment models are the seat belt use, and the time of the incident. To conclude, the present study is useful because it provides another perspective of rear-end crashes to encourage policy makers to apply decisions that favor rules that assure safety.

Alcohol and illicit substances associated with fatal crashes in Queensland: An examination of the 2011 to 2015 Coroner's findings

PROBLEM

The problem of impaired driving is well documented in the literature but is heavily dependent upon self-report studies and/or databases that do not include in-depth information about the contributing origins of fatalities.

AIM

This study aimed to conduct an in-depth analysis of Coroner's findings for all fatally injured drivers in the state of Queensland in order to explore the prevalence of alcohol and different types of illicit substances (including drug combinations) in fatal crash reports.

METHOD

A total of 701 Coroner's reports related to drivers or controllers of vehicles involved in traffic related fatalities for the period of 2011-2015 were analysed, revealing 306 controllers (43.6%) were detected with either alcohol or illegal drugs (e.g., methylamphetamine, Δ9-tetrahydrocannabinol, cocaine or MDMA) RESULTS: Alcohol was the most commonly detected substance identified with 223 cases (72.9% of the drug and alcohol sample). Illicit drug detections totalled 147 cases (48% of the drug and alcohol sample) with Δ9-tetrahydrocannabinol the most commonly detected illicit substance (109 cases; 35.6% of the drug and alcohol sample) followed by methylamphetamine (total of 63 cases; 20.6% of the drug and alcohol sample). An important theme to emerge was the prevalence of polysubstance use among fatally injured drivers, not just for alcohol and one drug type, but also multiple drug combinations. Fatality trends revealed a decrease in both non-substance and alcohol-related fatalities across the study period. However, road fatalities where an illicit substance was detected increased by approximately 57%. Males were overrepresented as a proportion of total fatalities (82.4%) and there were no significant sex or age differences regarding illicit substance related deaths. Drivers of passenger vehicles were most commonly identified in the data (66.2%), but motorcycle operators were disproportionately represented (28.1% of the total controller sample compared to 4% of vehicle registrations in Queensland) CONCLUSION: This case study analysis of fatal crashes not only confirms the ongoing problem of alcohol and driving, but also illuminates the emerging (and escalating) issue of illicit substances detected in fatally injured drivers.

Newly Developed TV-Based Cognitive Training Games Improve Car Driving Skills, Cognitive Functions, and Mood in Healthy Older Adults: Evidence From a Randomized Controlled Trial

Background: Cognitive training in a laboratory improves car driving skills of older car drivers. However, it remains unclear whether other types of cognitive training at home have beneficial effects on driving skills. Using our developed cognitive training games that can be played on a television with a set-top box in a person’s home, we investigated the effects of a 6-week cognitive training program on driving skills, which included on-road evaluation (primary outcome), and cognitive functions and emotional states (secondary outcome) in older people.

Methods: In this double-blinded randomized control trial (RCT), 60 older licensed drivers were randomly assigned into one of the two groups: a cognitive training game for car driving (CTCD) group and an active control cognitive training game (ACT) group. Participants in the CTCD group played the CTCD (processing speed, dual attention, and speed prediction) for 20 min in five sessions per week for 6 weeks. Participants in the ACT group played the ACT (selecting the larger number; selecting a number from largest to smallest; play a game of rock, article, scissors) for 20 min in five sessions per week for 6 weeks. We measured driving skills, various cognitive functions, and emotional states before and after the 6-week intervention period.

Results: Our main results showed that compared to the ACT group, the CTCD group demonstrated improved driving skills (adjusted p = 0.034). Moreover, the CTCD group demonstrated improved inhibition (stroop, adjusted p = 0.042: reverse Stroop, adjusted p = 0.043) and processing speed performance symbol search (SS), adjusted p = 0.049; digit symbol coding (adjusted p = 0.047), compared to the ACT group. The CTCD group scored higher on vigor–activity mood (adjusted p = 0.041) as measured using the Profile of Mood State.

Discussion: This randomized controlled trial provides scientific evidence for the benefits of the 6-week CTCD program on driving skills and cognitive functions, such as processing speed, inhibition, and vigor–activity mood, in healthy older people. Our results suggest that cognitive training is useful to improve the driving skills of older adults.

Trial registration: This trial was registered at The University Hospital Medical Information Network Clinical Trials Registry (UMIN 000029769). Registered 31 October 2017, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000034010

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.

Impact of Medical Conditions and Medications on Road Traffic Safety

Objectives

Many medical conditions and medicines with therapeutic importance have been shown to impair driving skills, causing road traffic accidents, which leads to great human and economic suffering in Oman. The primary purpose of this study was to assess retrospectively the extent of medical conditions and medications influencing road traffic safety among drivers involved in road accidents.

Methods

We conducted a retrospective study among 951 injured or non-injured drivers who reported to Khoula and Nizwa hospitals. We used the Al-Shifa database to find the drivers and contacted randomly selected patients over phone.

Results

The majority of victims were male (72.0%), involving personal cars, and reported at Khoula Hospital. The results show that 7.6% of the victimized drivers had a history of medical conditions with diabetes and hypertension (36.1% each) the most common. About 4.0% of victims were on medications of which insulin was the most common (9.4%). Loss of control was contributed to 38.5% of cases followed by dizziness (25.6%), sleep amnesia (10.3%), and blurred vision (7.7%). Other effects blamed by victimized drivers include vertigo, phonophobia, photophobia, back pain, loss of sensation, and headache accounting for 17.9% of cases.

Conclusion

Medical conditions and medications influence road traffic safety to some extent in Oman.

Risk factors for the severity of injury incurred in crashes involving on-duty police cars

OBJECTIVE

This article explores the risk factors associated with police cars on routine patrol and/or on an emergency run and their effects on the severity of injuries in crashes.

METHODS

The binary probit model is used to examine the effects of important factors on the risk of injuries sustained in crashes involving on-duty police cars.

RESULTS

Several factors significantly increase the probability of crashes that cause severe injuries. Among those causes are police officers who drive at excessive speeds, traffic violations during emergency responses or pursuits, and driving during the evening (6 to 12 p.m.) or in rainy weather. Findings also indicate some potential issues associated with an increase in the probability of crashes that cause injuries. Younger police drivers were found to be more likely to be involved in crashes causing injuries than middle-aged drivers were. Distracted driving by on-duty police officers as well as civilian drivers who did not pull over to let a police car pass in emergency situations also caused serious crashes.

CONCLUSIONS

Police cars are exempted from certain traffic laws under emergency circumstances. However, to reduce the probability of being involved in a crash resulting in severe injuries, officers are still obligated to drive safely and follow safety procedures when responding to emergencies or pursuing a car. Enhancement of training techniques for emergency situations or driving in pursuit of an offender and following the safety procedures are essential for safety in driving during an emergency run by police.

Decrease of morbidity in road traffic accidents in a high income country - an analysis of 24,405 accidents in a 21 year period

BACKGROUND

The WHO initiated the "Decade of Action for Road Safety" because the fatality on road traffic accidents could become the fifth leading cause of death in 2030. On the contrary, fatalities continue to decrease in high income countries. The aim of the study was to find evidence for changes in injury severity of passenger car occupants after road traffic accidents in Germany over time, and to find contributing factors.

METHODS

Data from the German In Depth Accident Study (GIDAS), representative for Germany, was used. A total of 24.405 accidents, reported from 1991 until 2011. 44.503 adult passenger car occupants were examined. A multivariable logistic regression model was developed to find reasons for observed trends over time.

RESULTS

The relative decrease in mortality was 68.8% from 1991 until 2011. Between 2006 and 2011, the percentage of severely injured traffic victims was less than half, both in terms of the whole body and individual body regions. For injuries with an Abbreviated Injury Scale (AIS) ≥ 2, the percentage of persons with lower leg injuries declined by 72.5%, followed by the percentage of persons with pelvic injuries (61.5%), upper extremity injuries (57.7%), head injuries (54.3%), thorax injuries (50.0%), and abdomen injuries (40.0%). The multivariable regression model found 13 independent variables associated with injury prevention (e.g. seat belt use: OR 0.41, CI 95% 0.32-0.49; airbag: OR 0.86, CI 95% 0.75-0.99). The implementation of protective factors increased over time while accident constellations with a high probability for severe injury decreased over time.

CONCLUSION

The decrease of severe injuries after road traffic accidents can be only attributed to a comprehensive approach including the enforcement of road safety policies and innovations in car engineering and emergency medicine. Traffic related measures and alcohol level control, and seat belt usage enforcement next to other technical advances are considered especially important.

Development of crash modification factors for changing lane width on roadway segments using generalized nonlinear models

This study evaluates the effectiveness of changing lane width in reducing crashes on roadway segments. To consider nonlinear relationships between crash rate and lane width, the study develops generalized nonlinear models (GNMs) using 3-years crash records and road geometry data collected for all roadway segments in Florida. The study also estimates various crash modification factors (CMFs) for different ranges of lane width based on the results of the GNMs. It was found that the crash rate was highest for 12-ft lane and lower for the lane width less than or greater than 12ft. GNMs can extrapolate this nonlinear continuous effect of lane width and estimate the CMFs for any lane width, not only selected lane widths, unlike generalized linear models (GLMs) with categorical variables. The CMFs estimated using GNMs reflect that crashes are less likely to occur for narrower lanes if the lane width is less than 12ft whereas crashes are less likely to occur for wider lanes if the lane width is greater than 12ft. However, these effects varied with the posted speed limits as the effect of interaction between lane width and speed limit was significant. The estimated CMFs show that crashes are less likely to occur for lane widths less than 12ft than the lane widths greater than 12ft if the speed limit is higher than or equal to 40mph. It was also found from the CMFs that crashes at higher severity levels (KABC and KAB) are less likely to occur for lane widths greater or less than 12ft compared to 12-ft lane. The study demonstrates that the CMFs estimated using GNMs clearly reflect variations in crashes with lane width, which cannot be captured by the CMFs estimated using GLMs. Thus, it is recommended that if the relationship between crash rate and lane width is nonlinear, the CMFs are estimated using GNMs.