Seat Belt Usage Research Articles

Advanced Vehicle Safety: A Prototype Circuit for Accident Prevention and Emergency Response

In contemporary society, the pursuit of robust accident prevention, detection, and reporting systems is paramount, particularly within the context of vehicular safety. This study introduces a meticulously designed prototype circuit, adaptable for deployment across diverse vehicle types. This intelligent circuitry endeavors to mitigate accidents and safeguard human lives by employing a multifaceted approach.The system's primary functions encompass the verification of seat belt usage and the assessment of alcohol consumption by the driver. Additionally, it incorporates a vibration sensor to detect accidents promptly. Complementing these features, the integration of GPS and GSM modules facilitates the rapid notification of emergency services, ensuring prompt assistance in the event of an accident.The core of this system is an Arduino microcontroller, orchestrating the interconnected components to process data and trigger actions based on predefined conditions. The circuit's performance has been rigorously tested, initially through simulation in Proteus software, and subsequently via real-world hardware implementation. Comparative analysis of software and hardware results lends insights into the system's functionality and reliability.The overarching objective of this study is to curtail accidents arising from intoxicated driving, unforeseen driver fatigue, and road obstructions. In instances of accidents, the electronic apparatus employed has the capacity to dispatch spontaneous and precise distress signals to law enforcement and medical personnel, thereby expediting casualty recovery and potentially saving lives. This research advances the fusion of technology and safety measures to augment road safety comprehensively.[6] Upadhyay, V., Gupta, S., Chaturvedi, S. and Singh, D. [2020], ‘Integrated accident prevention detectionand response system (iapdrs)’,International journal of engineering and advanced technology9(3), 2086–2089.[7] Vitkar, S. P., Banare, A. and Nadar, J. [2022], ‘Conceptual framework for accident detection and pre-vention’,Journal of Pharmaceutical Negative Resultspp. 7449–7455.[8] Wu, C., Zhang, P., Zhang, Z., Zheng, W., Xu, B., Wang, W., Yu, Z., Dai, X., Zhang, B. and Zang, K. [2023],‘Slip partitioning and crustal deformation patterns in the tianshan orogenic belt derived from gpsmeasurements and their tectonic implications’,Earth-Science Reviewsp. 104362.[9] Xu, X., Hu, X., Zhao, Y., Lü, X. and Aapaoja, A. [2023], ‘Urban short-term traffic speed prediction withcomplicated information fusion on accidents’,Expert Systems with Applicationsp. 119887.

Visual Functions, Seatbelt Usage, Speed, and Alcohol Consumption Standards for Driving and Their Impact on Road Traffic Accidents.

The incidence of road traffic accidents (RTAs) is dramatically increasing worldwide. Consequently, driving and licensing authorities have instituted strict rules and regulations, such as vision standards, restrictions on drunk driving, seat belt usage, and speeding, for driving safety. This study aimed to summarize the global visual standards for driving license issuing and renewal and investigate the effect of driving safety laws on RTA-related death rates in different countries. The study gathered data on visual standards for driving licenses from reliable sources and extracted enforcement scores (drunk driving, seat belt usage, and speeding) and RTA-related death rates from the World Health Organization status report on road safety. The Wilcoxon test explored the association between visual standards and RTA-related death rates, while the Kruskal-Wallis test analyzed the relationship between visual functions and death rates, as well as driving safety enforcement scores and RTA-related death rates. The analysis was conducted on 71 countries and 50 states within the United States out of the 193 countries listed by the United Nations. It was found that 116 countries and states required a minimum VA range of 6/6-6/18, while 91 countries and states mandated a similar range for one-eyed drivers. VF testing for driving licenses was necessary in 77 countries and states. No significant association was observed between VA or VF testing and RTA-related death rates. However, countries that conducted more visual function tests demonstrated lower rates of RTA-related fatalities. Furthermore, RTA-related death rates were significantly associated with speeding, drunk driving, and seat belt laws. Implementing clear policies regarding vision requirements, maintaining strict rules, and promoting law enforcement on speeding, drunk driving, and seat belt usage are crucial for improving road safety. These measures should be prioritized by driving and licensing authorities worldwide to mitigate the escalating incidence of RTAs.

Single-vehicle roadway departure crashes at rural two-lane highway curved segments: A diagnosis using pattern recognition

Curved segments account for a disproportionately high proportion of fatal and serious injury crashes, with most of these crashes occurring on rural two-lane (R2L) highways. During the 10-year period from 2008 to 2017, a total of 1 234 fatal single-vehicle roadway departure (SV-RwD) crashes occurred on R2L roads in Louisiana, out of which 635 (51.5 %) crashes occurred on curved segments. Therefore, it is critical to investigate the causes of SV-RwD crashes, specifically those that occur on curved segments. This study aimed to investigate the ‘association knowledge’ of the factors contributing to SV-RwD crashes on R2L curved segments in Louisiana using fatal and injury crash data collected from 2008 to 2017. The study utilized Cluster Correspondence Analysis (CCA), a robust joint dimension reduction and clustering method for handling high-dimensionality and multicollinearity of crash data, to achieve this objective. Based on the cluster validation measures, the study identified five clusters with specific traits, including alcohol-impaired male drivers with no seatbelt usage, young (15–24 years old) female drivers’ crash involvement in cloudy weather conditions, animal-involved crashes in rainy weather conditions, crashes occurring on hillcrest locations under cloudy weather conditions, and crashes in the dark with the presence of streetlights and higher traffic volume. Furthermore, young (15–24 years) female drivers were identified in most clusters, implying that this specific age group of female drivers requires special consideration when dealing with SV-RwD collisions on R2L curved segments. To improve safety on R2L curved segments, policymakers can use the findings of this study to develop targeted countermeasures.

COVID-19 and transport safety

ABSTRACT Transportation safety has substantially been impacted by the COVID-19 Pandemic. To contain the spread of the virus, governments around the world released guidelines (e.g. stay-at-home orders), which reduced or eliminated peoples’ daily commutes. These travel restrictions introduced new safety challenges for roadways and drivers, transit riders, and pedestrians and cyclists. Many cities, states, and countries around the world reported more severe crashes despite fewer drivers on the road. Transit ridership reduced as the risk of infection with COVID-19 kept transit users away, and walking and biking became more popular as they could be done individually in open air. This paper conducts a structured critical review to summarise and discuss studies around the world on roadway, transit, and pedestrian and bicycle safety since the start of the COVID-19 pandemic. For roadway safety, we further review studies that examine the direct measures of safety (e.g. crash statistics and models) as well as indirect or surrogate measures (e.g. speeding, aggressive driving, and reduced seatbelt usage). Surrogate measures, although indirectly, can affect the risk of crashes and contribute to the increase in frequency and severity of crashes. Findings are documented and discussed. We then provide suggestions on potential avenues for future research. Particularly, research studies show that the rate of severe injury crashes, as well as aggressive driving (e.g. speeding) increased in most places during the travel restrictions, and continued even after these restrictions were lifted. The safety of pedestrians and bicycles has also become increasingly important due to the increase in the number of users of these modes.

Data mining approach to explore emergency vehicle crash patterns: A comparative study of crash severity in emergency and non-emergency response modes

Emergency vehicle crashes, involving police vehicles, ambulances, and fire trucks, pose a serious traffic safety concern causing severe injury and deaths to first responders and other road users. However, limited research is available focusing on the contributing factors and their interactions related to these crashes. This research aims to address this gap by 1) identifying patterns of emergency vehicle crashes based on severity levels in both emergency and non-emergency modes and 2) comparing the associations by response modes for the related fatal, nonfatal injury, and no-injury crashes. Two national crash databases, Fatality Analysis Reporting System (FARS) and Crash Report Sampling System (CRSS), were utilized for police-reported emergency vehicle crashes from January 2016 to February 2020. Association rule mining (ARM) was employed to reveal the association between factors that strongly contributed to these crashes. The generated rules were validated using the lift increase criterion (LIC). The results showed the complex nature of risk factors influencing the severity of emergency vehicle crashes. The fatal consequences of speeding with no seatbelt usage were evident for emergency mode, whereas none of these risky driving attributes was observed for non-emergency mode. In addition, the analysis identified the risk of fatal emergency vehicle crashes involving pedestrians in dark-lighted conditions in both response modes. Regarding nonfatal injury severity, angle collisions were more likely to occur at urban intersections during emergencies, while rear-end crashes were more frequent on segments with a posted speed limit of 40–45 mph during non-emergency incidents. The outcomes also revealed that the no-injury crashes involving fire trucks exhibited different patterns depending on the response mode. The findings of this study can guide in making effective strategies to improve safe driving behavior of first responders. The identified associations provide insights into the factors that can be controlled to ensure safe operation of emergency vehicles on the road.

Analyzing the Effectiveness of Imbalanced Data Handling Techniques in Predicting Driver Phone Use

Distracted driving leads to a significant number of road crashes worldwide. Smartphone use is one of the most common causes of cognitive distraction among drivers. Available data on drivers’ phone use presents an invaluable opportunity to identify the main factors behind this behavior. Machine learning (ML) techniques are among the most effective techniques for this purpose. However, the potential and usefulness of these techniques are limited, due to the imbalance of available data. The majority class of instances collected is for drivers who do not use their phones, while the minority class is for those who do use their phones. This paper evaluates two main approaches for handling imbalanced datasets on driver phone use. These methods include oversampling and undersampling. The effectiveness of each method was evaluated using six ML techniques: Multilayer Perceptron (MLP), Support Vector Machine (SVM), Naive Bayes (NB), Bayesian Network (BayesNet), J48, and ID3. The proposed methods were also evaluated on three Deep Learning (DL) models: Arch1 (5 hidden layers), Arch2 (10 hidden layers), and Arch3 (15 hidden layers). The data used in this document were collected through a direct observation study to explore a set of human, vehicle, and road surface characteristics. The results showed that all ML methods, as well as DL methods, achieved balanced accuracy values for both classes. ID3, J48, and MLP methods outperformed the rest of the ML methods in all scenarios, with ID3 achieving slightly better accuracy. The DL methods also provided good performances, especially for the undersampling data. The results also showed that the classification methods performed best on the undersampled data. It was concluded that road classification has the highest impact on cell phone use, followed by driver age group, driver gender, vehicle type, and, finally, driver seatbelt usage.

Seat belt usage in buses – An observation study of usage and travellers’ perspectives

This study aims to evaluate seat belt usage in buses and to understand travellers’ incentives of seat belt usage. Methods used are observational studies (10 cities, with 328 bus observations), focus group discussion (7 groups with a total of 32 participants) and a web survey (n = 1737 respondents). The results show that the seat belt use among bus passengers can be improved especially in regional and commercial bus traffic. It is more common to buckle up on long trips than on short trips. However, even though observations show high usage during long trips, travellers report that they remove the seat belt after a while if they want to sleep or for comfort reasons. For the bus drivers it is not possible to control passengers’ usage. Dirty seat belts and technical malfunction might deter some passengers from using them and therefore systematic cleaning and control of seats and belts are recommended. On short trips one reason for not using the belt is related to worries about getting stuck and not being ready to get off in time. In general, it is most important to increase the usage on high-speed roads (>60 km/h), in lower speed it might be more important to provide a seat for each passenger. Based on the results a list of recommendations is presented.

Empirical examination of interdependent relationship between usage of seatbelt restraint system and driver-injury severity of single-vehicle crashes in Thailand using a joint econometric analysis

Objectives The paper aims to examine the interdependent relationship between the usage of the seatbelt restraint system and severities of the driver-injury in single-vehicle crashes. Methods This paper developed a comprehensive joint econometric structure − a joint random parameters binary probit-binary probit model − that allows for the simultaneous examination of injury severity of the driver in a crash, and taking into account the fact that seat belt use can be endogenous to the outcomes of driver injury. The developed model is tested using data on drivers-injury severities involved in single-vehicle crashes in Thailand from 2012-2017. Results In terms of the interdependent relationship between seatbelt use status and driver-injury severities, the findings suggest that drivers who do not use seat belts may demonstrate more dangerous or aggressive driving behaviors (such as speeding), subsequently increasing their likelihood of involvement in severe or fatal crashes. Additionally, the result also shows that drivers who are involved in speeding-related crashes are less likely to wear a seatbelt and have a higher risk of sustaining severe and fatal injuries. The findings also reveal that in crashes, drivers who are young, or operating trucks are less likely to be wearing their seat belts. The study also indicates that severe and fatal crashes are associated with factors such as elderly drivers, alcohol involvement, unbelted drivers, fatigue, depressed medians, and barrier medians. Conversely, a crash in a U-turn area, driving a passenger car, pickup truck, or large truck, or colliding with a guardrail reduces the likelihood of severe and fatal injuries. Conclusions Neglecting the hidden endogenous effect in statistical analyses could result in an overestimation of the impact of seat belt usage on crash-injury outcomes. The findings of this study can provide valuable insights for relevant authorities aiming to improve driver safety.

Identifying roadway departure crash patterns on rural two-lane highways under different lighting conditions: Association knowledge using data mining approach

Introduction: More than half of all fatalities on U.S. highways occur due to roadway departure (RwD) each year. Previous research has explored various risk factors that contribute to RwD crashes, however, a comprehensive investigation considering the effect of lighting conditions has been insufficiently addressed. Data: Using the Louisiana Department of Transportation and Development crash database, fatal and injury RwD crashes occurring on rural two-lane (R2L) highways between 2008-2017 were analyzed based on daylight and dark (with and without streetlight). Method: This research employed a safe system approach to explore meaningful complex interactions among multidimensional crash risk factors. To accomplish this, an unsupervised data mining algorithm association rules mining (ARM) was utilized. Results and conclusions: Based on the generated rules, the findings reveal several interesting crash patterns in the daylight, dark-with-streetlight, and dark-no-streetlight, emphasizing the importance of investigating RwD crash patterns depending on the lighting conditions. In daylight condition, fatal RwD crashes are associated with cloudy weather conditions, distracted drivers, standing water on the roadway, no seat belt use, and construction zones. In dark lighting condition (with and without streetlight), the majority of the RwD crashes are associated with alcohol/drug involvement, young drivers (15–24 years), driver condition (e.g., inattentive, distracted, illness/fatigued/asleep), and colliding with animal(s). Practical Applications: The findings also reveal how certain driver behavior patterns are connected to RwD crashes, such as a strong association between alcohol/drug intoxication and no seat belt usage in the dark-no-streetlight condition. Based on the identified crash patterns and behavioral characteristics under different lighting conditions, the findings could aid researchers and safety specialists in developing the most effective RwD crash mitigation strategies.

The mixed-mixed multinomial logit model for identification of factors to the passengers’ seatbelt use

A better understanding of the underlying factors to the choice of seatbelt use could contribute to the policy solutions, which consequently enhance the rate of seatbelt usage. To achieve that goal, it is important to obtain unbiased and reliable results by employing a valid statistical technique. In this paper, the latent class (LC) model was extended to account for unobserved heterogeneity across parameters within the same class. The random parameter latent class, or mixed-mixed (MM) model, is an extension of the mixed and LC models by adding another layer to the LC model, with an objective of accounting for heterogeneity within a same class. The results indicated that although the LC model outperformed the mixed model, the standard LC model did not account for the whole heterogeneity in the dataset and adding an extra layer for changing the parameter across the observations result in an improvement in a model fit. The results indicated that seatbelt status of the driver, vehicle type, day of a week, and driver gender are some of factors impacting whether or not passengers would wear their seatbelts. It was also observed that accounting for day of a week, drivers’ gender, and type of vehicle heterogeneities in the second layer of the MM model result in a better fit, compared with the LC technique. The results of this study expand our understanding about factors to the choice of seatbelt use while capturing extra heterogeneity of the front-seat passengers’ choice of seatbelt use. This is one of the earliest studies implemented the technique in the context of the traffic safety, with individual-specific observations.

Examining Seat Belt Use Habits in Wyoming: A Bayesian Hierarchical Logit Approach

Wyoming has one of the lowest seat belt law compliance rates in the United States. Understanding the factors associated with seat belt non-use is crucial for the development of appropriate mitigation measures that aid in increasing seat belt usage rates. In this study, Bayesian binary logistic regression models were developed to: i) investigate the factors associated with daytime seat belt non-use using observational survey data; and ii) assess the factors related to seat belt non-use in fatal crashes while accounting for possible intra-class correlation (effects of unobserved factors common to occupants in the same vehicle). The results indicated that males were less likely to use seat belts than females. Also, trips made in pick-up trucks, those made within urban areas, those made during weekdays, and those made by means of vehicles with Wyoming license plates were likely to involve seat belt non-use. Furthermore, counties with thriving oil and gas industries had lower seat belt use rates. It was also inferred that young occupants, rear seat occupants, impairment, weekdays, traveling around midnight, traveling on collector roads, and traveling on local roads were associated with seat belt non-use. A strong correlation in seat belt non-use among occupants within the same vehicle warrants the implementation of the hierarchical logistic model to investigate seat belt use among occupants involved in fatal crashes. The findings of this study highlight remarkable trends in seat belt use habits in Wyoming, which will aid legislatures in proposing road safety measures aimed at raising seat belt usage proportions.

Cellphone-distracted crashes of novice teen drivers: Understanding associations of contributing factors for crash severity levels and cellphone usage types

Objective As novice teen drivers are uniquely susceptible to the harmful effects of secondary activities on cellphones, 38 states and Washington D.C. have banned all types of cellphone usage for drivers younger than 18 years or in the learner/intermediate phase of driving. Despite the prevalence of such cellphone prohibitions, several surveillance studies have highlighted the persistent engagement of teenagers in cellphone-distracted driving, which increases the related crash risk. Most of the prior studies broadly consider cellphone usage as a general distraction instead of investigating different distraction-related tasks associated with cellphone use. This study analyzed the cellphone crashes of novice teenagers (aged 15–17 years) to discover the grouping of contributing factors by crash severity levels and cellphone usage types. Methods The current study collected five years (2015–2019) of related crash data from the Louisiana Department of Transportation and Development. A manual effort was carried out to recognize the type of cellphone tasks before collision by reading the narratives of police-investigated crash reports. Association rule mining was applied to explore the associations between numerous crash attributes in multiple circumstances without relying on any predetermined hypotheses. Results The cumulative effect of cellphone distraction and no seatbelt usage is frequently visible in confirmed injury crash scenarios. Cellphone crashes of novice teenagers at intersections are strongly associated with talking/listening rather than texting/browsing/dialing and reaching for/answering/locating. The associations among environmental factors and modes of cellphone usage significantly influence the manner of collisions. Single-vehicle crashes are associated with cellphone manipulation while driving on weekends in cloudy weather, whereas sideswipe collisions are frequent in evening hours during reaching for/answering/locating the cellphones. In relation to texting/browsing/dialing, novice teenagers operating vans/SUVs are strongly associated with traffic control violations. Conclusions The findings are expected to be beneficial for policymakers and other safety officials to develop strategic planning and implementable countermeasures when dealing with cellphone-distracted novice teenagers. The association of factors identified from the analysis exhibits real-world crash scenarios critical to strengthening driver education programs to mitigate teen driver crashes. Moreover, cellphone crashes and related casualties can be reduced by eliminating or improving one of the attributes involved in the crash patterns.

Influence of Demographic Disparities on Seat Belt Compliance in an Urban Area (Washington, DC)

This study evaluated the potential influence of demographic factors on seat belt compliance rates in an urban area. Washington D.C., which is the capital of the United States, is an urban area with mixed and diverse population. The city (and all states) conducts seat belt compliance surveys annually as a requirement of the National Highway Traffic Safety Administration (NHTSA). This article used compliance rates obtained from the field for 2014 through 2020 and matched those with demographic data for the same timeframe. The demographic data for the city was obtained from the United States Census Bureau. Demographic variables including race, educational and income levels for the eight wards in Washington D.C. we extracted for analysis. Overall, seat belt compliance usage in Washington ranged from 93% to 95.7% between 2014 and 2020. Approximately 42.3% of its population are Caucasian while 43.9% are African Americans with the remaining being Asian, Hispanics and other races. In addition, seat belt usage was reported by ward. Using single factor analysis of variance, it was determined that compliance rates in the wards were not statistically influenced by race, educational level, or income level at 5% level of significance. However, when comparing yearly seatbelt compliance from 2014 to 2020, the compliance rates of 2014 versus 2019, and 2014 versus 2020 were determined to be statistically different. Seat belt use should be encouraged for everyone in all jurisdictions. The analysis shows that, in this urban area, the three demographic variables do not have any influence on the compliance rates.

Observed relationships between driver and passenger restraint use in the front and rear seats

Objective Seat belt usage has increased substantially since the 1960s, yet driver use continues to affect passenger usage. Recent observational restraint use findings for Maryland will examine the relationship between driver and passenger usage, including adults and children in the rear seat. Methods Analyses were based on observational front and rear seat studies administered in parallel from 2016 to 2019. A statistically rigorous front seat project yielded weighted results among drivers and outboard passengers. A study of adults and children in the rear seat was based on a convenience sample of vehicles. Restraint usage results were presented as frequencies and proportions among occupants with known belt use, along with the 95% confidence interval for overall rates. Results Overall restraint usage rates averaged 90.9% in the front seat study and 81.1% in the rear seat sample. In vehicles with two front seat occupants and a belted driver, the proportion of belted passengers averaged 93.0% over four years. However, among unbelted drivers, only 41.6% of passengers were belted on average. In the rear seat study, an average of 82.7% were belted in vehicles driven by a restrained driver, differing for children (92.0%) versus adults (70.4%). Analysis of vehicles with an unbelted driver revealed an average of 45.0% of belted rear seat occupants, with a considerable difference for children (65.0%) compared with adults (21.0%). Conclusions Observational seat belt studies in Maryland in recent years have shown that, despite overall rates above 80%, passenger use in both the front and rear seats is associated with driver restraint use.

Seat Belt Restraint Evidence Generated by Unrestrained Occupant Interaction in a Rollover

<div class="section abstract"><div class="htmlview paragraph">Assessment of the physical evidence on a seat belt restraint system provides one source of data for determining an occupant’s seat belt use or non-use during a motor vehicle crash. The evidence typically associated with loading from a restrained occupant has been extensively researched and documented in the literature. However, evidence of loading to the restraint system can also be generated by other means, including the interaction of an unrestrained occupant with a stowed restraint system. The present study evaluates physical evidence on multiple stowed restraint systems generated via interaction with unrestrained occupants during a full-scale dolly rollover crash test of a large multiple passenger van. Unbelted anthropomorphic test devices (ATDs) were positioned in the driver and right front passenger seats and in all designated seating positions in the third, fourth, and fifth rows. Occupant kinematics during the dolly rollover were evaluated through on-board and off-board real-time and high-speed video, and physical evidence on the restraint systems was documented. Analysis of the occupant kinematics demonstrated multiple ATD interactions with stowed restraint systems in the vehicle, which generated corresponding physical evidence on those restraint systems. The findings of the present study demonstrate that the presence of physical evidence on the restraint system alone is insufficient for determination of occupant seat belt usage. A methodology for assessing restraint webbing and hardware evidence in the context of occupant seat belt use versus non-use is detailed. Thorough documentation of the restraint system physical evidence, evaluation of the occupant kinematics and injury patterns, and evaluation of the restraint system evidence as it relates to the body habitus of the occupant of interest can provide an objective scientific basis for the determination of occupant restraint status.</div></div>

Exploring Factors in a Crossroad Dataset Using Cluster-Based Association Rule Mining

Investigating the contributory factors in crossroad accidents is a high-priority issue in the traffic safety analysis. This study exploits a method based on association rules to analyze these contributory factors. Using data about one year of crossroad traffic accidents in Isfahan, Iran, 63 and 156 association rules are generated for non-serious and serious accidents, respectively. The results show that both accident severity levels are associated with head-to-the-side collisions and the spring season. The frequency of non-serious accidents is about 38% higher than that of serious accidents. However, the association analysis results show that serious accidents are associated with more influencing factors than non-serious. Seat belt usage and road surface condition are additional decisive factors for serious accidents but not so for non-serious. The association analysis reveals that many influencing factors (such as traffic lights and the existence of a traffic enforcement camera) exhibit effects only under some specific circumstances (e.g., the peak of traffic).

The Latent Class Multinomial Logit Model for Modeling Front-Seat Passenger Seatbelt Choice, Considering Seatbelt Status of Driver

The literature review highlighted the impacts of drivers’ behavior on passengers’ attitudes in the choice of seatbelt usage. However, limited studies have been done to determine those impacts. Studying the passengers’ seatbelt use is especially needed to find out why passengers choose not to buckle up, and consequently it helps decision makers to target appropriate groups. So, this study was conducted to find drivers’ characteristics that might impact the passenger’s seatbelt use, in addition to other passengers’ characteristics themselves. While performing any analysis, it is important to use a right statistical model to achieve a less biased point estimate of the model parameters. The latent class multinomial logit model (LC-MNL) can be seen as an alternative to the mixed logit model, replacing the continuous with a discrete distribution, by capturing possible heterogeneity through membership in various clusters. In this study, instead of a response to the survey or crash observations, we employed a real-life observational data for the analysis. Results derived from the analysis reveal a clear indication of heterogeneity across individuals for almost all parameters. Various socio-demographic variables for class allocation and models with different latent numbers were considered and checked in terms of goodness of fit. The results indicated that a class membership with three factors based on vehicle type would result in a best fit. The results also highlighted the significant impacts of driver seatbelt status, time of a day, distance of traveling, vehicle type, and driver gender, instead of passenger gender, as some of the factors impacting the passengers’ choice of seatbelt usage. In addition, it was found that the belting status of passengers is positively associated with the belting condition of drivers, highlighting the psychological behavioral impact of drivers on passengers. Extensive discussion has been made regarding the implications of the findings.

Child safety in cars: An observational study on the use of child restraint systems in The Netherlands

Objective To minimize children’s injuries due to car accidents, children must be transported in approved child restraint systems (CRS). The European Union optimized child protection by implementing R129 legislation for CRS in 2013. However, compliance with CRS recommendations after introduction of this newer standard has been scarcely evaluated. The main objectives of this study were to determine the prevalence of various types of CRS misuse and to investigate the use of ISOFIX and i-Size seats and parental knowledge regarding safe transportation of children in cars 5 years after the introduction of the newer R129 standard. Methods During a cross-sectional observational study in the summer of 2018, parking lots of sites in the Netherlands were visited by researchers. Arriving or departing Dutch drivers who transported children under 9 years old were interviewed by means of a questionnaire and the misuse of CRS was directly observed using a checklist. Misuse was defined as CRS inappropriate for the child (based on height and weight) and/or CRS wrongly installed in the car and/or child improperly restrained in CRS. Results In total, 392 drivers and 470 children were included in the study. Results showed that 83% of the children were transported with at least 1 misuse of their CRS: 7% of the CRS were inappropriate for the child, 49% of the CRS were wrongly installed in the car, and 59% of the children were improperly restrained in a CRS. Most CRS were installed using the seat belt (88%) compared to ISOFIX (12%). ISOFIX usage did not result in less CRS installation misuse (P = .338). The number of observed i-Size CRS was low (n = 13, 3%). Most drivers were familiar with ISOFIX (76%), but only 13% of the drivers had heard of i-Size. Conclusions For 9 out of 10 children, CRS misuse was observed. Many children were transported in an appropriate CRS, but various mistakes were made when installing the CRS in the car and restraining children in the CRS. Moreover, ISOFIX usage did not result in statistically significant less CRS installation misuse compared to traditional seat belt usage, and i-Size CRS are still rather unknown 5 years after their introduction.

Isolated vehicle rollover is not an independent predictor of trauma injury severity.

ObjectivesThe objective of this study was to determine if vehicle rollover in a motor vehicle crash is an independent predictor of major injury.MethodsA retrospective cohort study of all patients injured in motor vehicle crashes presenting to a major trauma center between July 2012 and June 2016 was conducted. Crashes were classified into groups: non‐rollover, isolated rollover (without other mechanisms of injury), or mixed‐mechanism rollover (with other mechanisms of injury). Associations between rollover group, other covariates (entrapment, encapsulation, ejection, death on scene, high speed, seat belt usage, airbag deployment, trauma team activation), and major injury (injury severity score >15, major surgery, intensive care unit admission, or in‐hospital death) were tested using binary logistic regression models. Vehicle rollover was categorized either as “present” or “absent” on 1 model or as either “none,” “isolated,” or “mixed mechanism” in the other.ResultsIn 2446 motor vehicle crashes, there were 423 rollovers (196 isolated, 227 mixed mechanisms). Compared with crashes without rollovers, the prevalence of patients with major injury was lower in crashes with isolated rollovers and higher in crashes with mixed‐mechanism rollovers (13.8% vs 9.5% vs 27.5%, respectively; P < 0.001). Rollover (present vs absent) was not an independent predictor of major injury (odds ratio [OR], 1.10; 95% confidence interval [CI], 0.78–1.53). Patients in crashes with mixed‐mechanism but not isolated rollovers had increased odds (OR, 2.04; 95% CI, 1.41–2.96) of major injury compared with patients from crashes without rollovers.ConclusionsPatients from crashes with isolated vehicle rollovers may not need to be transported to a trauma center as they carry a lower risk of injury.

Does driver seatbelt use increase usage among front seat passengers? An exploratory analysis

Introduction and Method: Observational data collected during the Wisconsin 2017, 2018, and 2019 National Occupant Protection Use Survey (NOPUS) were analyzed for this study to explore the influence of drivers’ seatbelt use on front seat passengers’ usage in the same vehicle. The analyses include comparing seatbelt usage rates for drivers and front passenger(s) based on their gender and based on geographical area as well as analyses of the aggregated data. Results: The descriptive analyses strongly suggest that seatbelt usage rates of passengers differ considerably depending on whether the driver uses the seatbelt. When female drivers wear seatbelts, seatbelt usage rates for female front seat passengers for the three years 2017, 2018, and 2019 are 97.8%, 96.3%, and 97.1% respectively, with corresponding usage rates for male passengers being 95.5%, 93.0%, and 96.0% respectively. When male drivers wear seatbelts, the seatbelt usage rates for male front seat passengers for the three years 2017, 2018, and 2019, are 93.4%, 95.5%, and 94.3%, respectively, with the corresponding usage rates for female passengers being 97.7%, 96.0%, and 97.7%, respectively. The evidence suggests that drivers’ use of seatbelts significantly improves the seatbelt usage of front seat passengers. Seatbelt usage rates of male passengers as well as female passengers are higher while traveling with female drivers who use seatbelts than while traveling with male drivers who use seatbelts. Conclusions and Practical Applications: Future seatbelt use campaigns should target males.