Background
In the Netherlands, there are no specialized or certified pediatric trauma centers, especially for severely injured children. National and regional agreements on centralization of ...pediatric trauma care are scarce. This study aims to describe the incidence, injury mechanism and in-hospital mortality of pediatric trauma in the Netherlands, as a prelude to the further organization of pediatric trauma care.
Methods
A retrospective cohort analysis of data from the Dutch National Trauma Registry in 2009–2018, concerning all children (0–16 years) hospitalized due to injury in the Netherlands.
Results
The annual number of admitted injured children increased from 8666 in 2009 to 13,367 in 2018. Domestic accidents were the most common cause of non-fatal injury (67.9%), especially in children aged 0–5 years (89.2%). Severe injury (injury severity score ≥ 16) accounted for 2.5% and 74% of these patients were treated in level-1 trauma centers. In both deceased and surviving patients with severe injuries, head injuries were the most common (72.1% and 64.3%, respectively). In-hospital mortality after severe injury was 8.2%. Road-traffic accidents (RTAs) were the leading cause of death (46.5%).
Conclusions
Domestic accidents are the most common cause of injury, especially in younger children, whereas RTAs are the lead cause of fatal injury. Severe pediatric trauma in the Netherlands is predominantly managed in level-1 trauma centers, where a multidisciplinary team of experts is available. Improving the numbers of severely injured patients primarily brought to level-1 trauma centers may help to further reduce mortality.
The highly competitive and rapidly advancing autonomous vehicle race has been on for several years now, and it has made the driver-assistance systems a shadow of their former self. Nevertheless, ...automated vehicles have many obstacles on the way, and until we have them on the roads, promising solutions that can be achievable in the near future should be sought-after. Driving-support technologies have proven themselves to be effective in the battle against car crashes, and with Vehicular Ad hoc Networks (VANETs) supporting them, their efficiency is expected to rise steeply. In this work, we propose and implement a driving-support system which, on the one hand, could immensely benefit from major advancement of VANETs, but on the other hand can effectively be implemented as a stand-alone system. The proposed system consists of a non-intrusive integrated fuzzy-based system able to detect a risky situation in real time and alert the driver about the danger. It makes use of the information acquired from various in-car sensors as well as from communications with other vehicles and infrastructure to evaluate the condition of the considered parameters. The parameters include factors that affect the driver’s ability to drive, such as his/her current health condition and the inside environment in which he/she is driving, the vehicle speed, and factors related to the outside environment such as the weather and road condition. We show the effect of these parameters on the determination of the driving risk level through simulations and experiments and explain how these risk levels are translated into actions that can help the driver to manage certain risky situations, thus improving the driving safety.
We propose a multivariate Grey-Markov model to quantify traffic accident risk from different causality factors in roundabouts that is uniquely suited for the scarce and stochastic traffic crash data ...from roundabouts. A data sample of traffic crashes occurring in roundabouts in the U.S. State of Michigan from 2016 to 2021 was collected to investigate the capabilities of this modeling methodology. The multivariate grey model (MGM(1,4)) was constructed using grey relational analysis to determine the best dimensions for model optimization. Then, the Markov chain is introduced to address the unfitness of stochastic, fluctuating data in the MGM(1,4) model. Finally, our proposed hybrid MGM(1,4)-Markov model is compared with other models and validated. This study highlights the superior predictive performance of our MGM(1,4)-Markov model in fore-casting roundabout traffic accidents under data-limited conditions, achieving a 3.02% accuracy rate, in contrast to the traditional GM(1,1) model at 8.30% and the MGM(1,4) model at 4.47%. Moreover, incorporating human, vehicle, and environmental risk factors into a multivariate crash system yields more accurate predictions than merely aggregating crash counts.
Alcohol and drug abuse is a major contributory factor of all road deaths in Europe. The aim of this study is to investigate the prevalence of alcohol and licit/illicit drug intake among victims of ...road accidents in Campania region (Italy). A retrospective analysis of road traffic deaths from 2013 to 2022 in Campania was performed. The toxicological results from fluid samples collected at autopsy were reviewed. In total, 228 road deaths occurred, mostly during nights and weekends. A total of 106 victims tested positive for alcohol and/or drugs, among which 39 (36.8%) tested positive for alcohol only, 27 (25.5%) for alcohol and drugs in association; and 40 (37.7%) for licit/illicit drugs only, either individually or in combination. Polydrug intake has been found in 21 victims, and nine in combination with alcohol. The most detected drugs were cocaine and Δ9THC, followed by benzodiazepines. Blood alcohol concentration (BAC) > 1.5 g/L was found in most alcohol positives, both alone and in association with drugs. Despite the penalties for driving under the influence of alcohol (DUI) and drugs (DUID), no decrease in the number of alcohol and/or drugs related fatal road accidents has been observed. DUI and/or DUID cases were approximately one third of the entire sample study.
This paper analyses the impact that the lockdown decreed by the Spanish Government to combat the spread of COVID-19 has had on traffic accidents in Tarragona province (Spain). During the studied ...period of the lockdown (March 16 - April 26 2020) the number of accidents per day fell by 74,3% in coparison with those in February 14-20 (reference week) and 76% in respect to the equivalent period in 2018-2019. This reduction of accidents has been higher than the decrease of mobility during the same reference period (62.9%). This suggests a multiplicative positive effect of traffic reduction on roads safety. Our findings provide new evidences of the disruptive effect of the COVID-19 pandemic on transportation and of how it could be used as a catalyst to promote more sustainable and secure transport systems.
•Overall mobility in Tarragona province during COVID-19 lockdown declined 62,9%, while traffic accidents fell 74,3%.•The relative occurrence of severe traffic accidents diminished during the lockdown.•The reduction of traffic accidents on weekends/holidays was more intense compared to weekdays.•Our findings provide new evidences of the disruptive effect of the COVID-19 pandemic on transportation and road safety.
According to the World Health Organization, road traffic injuries lead to 1.3 million deaths each year and represent the leading cause of death for young adults under 30 years old. The use of ...psychoactive substances, including alcohol, drugs and pharmaceuticals, is a well-known risk factor for road traffic injuries. Our study aims to assess the prevalence of substances consumed by drivers in western Switzerland. Such studies are pivotal to improving prevention and developing public awareness campaigns.
To assess the prevalence of psychoactive substances among drivers, roadside controls were performed in collaboration with local police, using their classical sampling procedures to detect drivers under the influence of drugs or alcohol over two time periods (P1: 2006-2008, P2: 2017-2020). When impaired driving was not suspected by the police, minimally invasive sampling strategies (i.e., oral fluids during P1 and dried blood spots during P2) were performed on volunteer drivers after a road safety survey. A posteriori analyses and statistical interpretation were then performed.
Among the 1605 drivers included in the study, 1048 volunteers provided an oral fluid sample, while 299 provided a dried blood spot sample. The percentage of drivers testing positive for at least one substance that can impact driving abilities was stable over time, with a rate of 10.5% positivity measured over both periods. Considering the different categories of substances, a slight variation was observed between both periods, with 7.6 and 6.3% of pharmaceuticals and 3.6 and 4.9% of illicit drugs for P1 and P2, respectively. Regarding the consumption of illicit drugs, the highest percentage of positivity was measured in biological fluids of drivers under the age of 35, during nights and week-ends, periods which are considered particularly prone to fatal accidents for this age group. Disturbingly, the road safety survey highlighted that drivers' perception of the risk of getting positively controlled while driving after drug consumption is low (3.3 on a 1-to-10 scale, N = 299).
The number of positive cases measured in voluntary drivers who passed the preliminary police check demonstrates the importance of systematic biofluid sampling strategies regarding driving under the influence of psychoactive substances. Although the number of fatal road accidents globally has decreased over time, the results of this study reveal the need for both better prevention and deterrent processes that could potentially reduce the risk of fatal road accidents associated with drug consumption.
Road traffic damages were amongst the central causes of passing away, hospitalization, disability, and low socioeconomic status. About 1.3 million lethal road traffic damages and 20-50 million ...nonfatal damages happened consequently of road traffic accidents every year globally. Motorcycles are a small subsection of all motor vehicles significantly over-represented in total motor vehicle accidents and lead to a great rate of deaths and disabilities.
The study aimed to assess the prevalence of motorcycle accident and associated factors among road traffic accident patients in Hawassa University Comprehensive Specialized Hospital, Hawassa city, Ethiopia in 2019.
The health institution/hospital-based retrospective cross-sectional study design was applied and a systematic random sampling technique was implemented to select the sample size of 274 patient's cards from January 2018 to January 2019. The data were entered and analyzed on SPSS 20.
From 274 patients' medical records reviewed in the study period, 151 (55.1%) injuries were due to motorcycle accident. In a multiple logistic regression analysis, age, sex, high speed, and types of roads showed significant association with motorcycle accidents.
The prevalence of motorcycle accidents was the main cause of injuries among others, which was 55.1%. Motorcycle accidents occurred mainly in males and in people with the age category of 20-29 years. Age, sex, high speed, and type of road were significantly associated with a motorcycle accident.
Improving vehicle safety and reducing traffic accidents have always been of cardinal importance in vehicle dynamics control fields. A reasonable and comprehensive safety index that characterizes the ...vehicle's safe region is the most challenging aspect of research. With the linear dynamics model as the benchmark, this article uses the deviation of yaw rate and vehicle sideslip angle from the corresponding linear response as the lateral stability indices. Meanwhile, the maximum slip ratio of the driven wheels is selected as the longitudinal stability index. The safety indicator , a quantitative index featuring the safety degree of vehicle planar motions, is then inferred by a fuzzy inference system using the lateral and longitudinal stability indices. As such, the recurrent high-order neural network model predicts the vehicle states. Based on the predicted states, a safety indicator is then derived by using fuzzy inference system, which can assess the safety of a driver's control commands. In the case of an improper driving torque demand given by the driver, the torque correction process is immediately conducted to maintain the vehicle in a safe region. Finally, two typical scenarios-slippery curves and double lane changes in low friction roads-are simulated on the MATLAB/Simulink-CarSim cosimulation platform. The hardware-in-the-loop experiments are also conducted on a driving simulator test rig, validating the performance of the developed algorithms. The holistic stability performance of the in-wheel motor driven vehicle is thoroughly analyzed and compared using three existing methods. The simulation and experimental results validate the effectiveness and feasibility of the proposed method.
Abstract
Background
Determining risk factors of single-vehicle run-off-road (SV-ROR) crashes, as a significant number of all the single-vehicle crashes and all the fatalities, may provide ...infrastructure for quicker and more effective safety measures to explore the influencing and moderating variables in SV-ROR. Therefore, this paper emphasizes utilizing a hybrid of regularization method and generalized path analysis for studying SV-ROR crashes to identify variables influencing their happening and severity.
Methods
This cross-sectional study investigated 724 highway SV-ROR crashes from 2015 to 2016. To drive the key variables influencing SV-ROR crashes Ridge, Least Absolute Shrinkage and Selection Operator (Lasso), and Elastic net regularization methods were implemented. The goodness of fit of utilized methods in a testing sample was assessed using the deviance and deviance ratio. A hybrid of Lasso regression (LR) and generalized path analysis (gPath) was used to detect the cause and mediators of SV-ROR crashes.
Results
Findings indicated that the final modified model fitted the data accurately with
$${\mathcal{X}}_{3}^{2}$$
X
3
2
= 16.09,
P
< .001,
$${\mathcal{X}}^{2}$$
X
2
/ degrees of freedom = 5.36 > 5, CFI = .94 > .9, TLI = .71 < .9, RMSEA = 1.00 > .08 (90% CI = (.06 to .15)). Also, the presence of passenger (odds ratio (OR) = 2.31, 95% CI = (1.73 to 3.06)), collision type (OR = 1.21, 95% CI = (1.07 to 1.37)), driver misconduct (OR = 1.54, 95% CI = (1.32 to 1.79)) and vehicle age (OR = 2.08, 95% CI = (1.77 to 2.46)) were significant cause of fatality outcome. The proposed causal model identified collision type and driver misconduct as mediators.
Conclusions
The proposed HLR-gPath model can be considered a useful theoretical structure to describe how the presence of passenger, collision type, driver misconduct, and vehicle age can both predict and mediate fatality among SV-ROR crashes. While notable progress has been made in implementing road safety measures, it is essential to emphasize that operative preventative measures still remain the most effective approach for reducing the burden of crashes, considering the critical components identified in this study.
Alcohol use has been linked to impairment of cognitive and psychomotor driving skills, yet the extent to which skill impairment contributes to actual crashes is unknown. A reasonable assumption is ...that some driving situations have higher skill demands than others. We contend that intersections, the presence of other vehicles or moving objects, and work zones are examples of common situations with higher skill demands. Accordingly, if skill deficits are largely responsible for alcohol-involved crashes, crashes involving a drinking driver (versus only sober drivers) should be overrepresented in these driving situations.
Publicly available FARS data from 2010 to 2017 were collected. Fatal crashes were coded as alcohol-involved (1+ driver with a blood alcohol concentration BAC ≥ .05 g/dl) or having no impaired driver (BACs = .000). Drug-positive crashes were excluded. Crashes were also coded as involving moving versus stationary objects, occurring at versus away from intersections, being multivehicle versus single vehicle, occurring at or away from work zones.
Across multiple models, controlling for time of day and type of road, alcohol-involved crashes were significantly underrepresented in crashes at intersections, with moving objects, and other vehicles. Most strikingly, alcohol-involved crashes were 24 percentage points more likely to be with a stationary object than a moving object.
No evidence supported the idea that skill reductions are a primary contributor to alcohol-involved crashes. Alternative explanations and limitations are discussed.
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