Road Traffic
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2022 ◽  
Vol 109 ◽  
pp. 104622
Igor Tchappi ◽  
Yazan Mualla ◽  
Stéphane Galland ◽  
André Bottaro ◽  
Vivient Corneille Kamla ◽  

Parul Vaid ◽  
Bhavuk Kapoor ◽  
Mayank Kapoor

Traumatic brain injury (TBI) constitutes a major health and socioeconomic problem throughout the world TBI is called the ‘silent epidemic’ because problems resulting from TBI are often not immediately visible and TBI patients are not very vociferous. Epidemiological studies of TBI are essential to the targeted prevention and effective treatment of brain-injured patients. Epidemiology analysis of surgically managed traumatic brain injury patients was done. Mean age was 35.9 years. Males were more commonly (80%) involved than females (20%). In 57.5% of cases, falls were responsible for TBI and in 42.5% of cases, Road traffic accidents were responsible. Edh was the most common type of TBI in (50%). Chronic SDH occurred in 25% of cases. Acute SDH and Contusions were both seen in 13.75% of cases. Depressed fractures occurred in 6.25% of cases and ICH occurred in 1.25% of cases. Craniotomy was the most common (42%) surgical procedure performed, followed by burrhole drainage (22.5%). Decompressive craniectomy was done in 18.75% of cases and elevation of depressed fracture was performed in 6.25% of cases. Traumatic brain injury (TBI) constitutes a major health and socioeconomic problem throughout the world. People of all ages are affected by it. Males are more commonly involved as compared to females. Timely hospitalisation and surgical management whenever indicated improves the survival.

2022 ◽  
Vol 7 (4) ◽  
pp. 642-647
Anubha Bhatti ◽  
Arushi Kakkar ◽  
Shakeen Singh

To study the epidemiology and clinical profile of ocular trauma patients presenting to tertiary care centre. Prospective study. All patients of ocular trauma in OPD/Emergency were assessed for detail between 1/1/17 to 31/6/18 and data on demographic profile was established as per guidelines of Ocular Trauma Society of India. Patients were categorized in different segments and assessed/followed for visual impairment in particular. A total of 246 cases were examined out of which 87% were males. The most common mode of ocular injury was Road Traffic Accidents. Pediatric eye trauma constituted 16.7% of the total cases. 26.8% cases arrived to our centre between 4-24 hours and 62.6% cases presented after 24 hours. Amongst 131 cases of Road Traffic Accidents, none of them were using protective measures like helmets or goggles. Of these, 17.1% were under the influence of alcohol. 28.5% were involved in medicolegal proceedings. Majority of the cases comprised of monocular trauma (78.1%). Closed globe injuries constituted 88.94% of the total cases of which most cases presented with lid edema and ecchymosis. Chemical injuries were reported in 4.5% cases. 9 patients lost vision completely and 71 cases had vision from light perception to 6/18. Ocular trauma is one of the common causes of ocular morbidity. It has been seen predominantly in male population. Public needs to be educated about safety measurements and education about prompt need to specialised care to reduce ocular trauma related visual morbidity.

2022 ◽  
Vol 12 (2) ◽  
pp. 828
Tebogo Bokaba ◽  
Wesley Doorsamy ◽  
Babu Sena Paul

Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent years, there has been a growing global interest in analysing RTAs, specifically concerned with analysing and modelling accident data to better understand and assess the causes and effects of accidents. This study analysed the performance of widely used machine learning classifiers using a real-life RTA dataset from Gauteng, South Africa. The study aimed to assess prediction model designs for RTAs to assist transport authorities and policymakers. It considered classifiers such as naïve Bayes, logistic regression, k-nearest neighbour, AdaBoost, support vector machine, random forest, and five missing data methods. These classifiers were evaluated using five evaluation metrics: accuracy, root-mean-square error, precision, recall, and receiver operating characteristic curves. Furthermore, the assessment involved parameter adjustment and incorporated dimensionality reduction techniques. The empirical results and analyses show that the RF classifier, combined with multiple imputations by chained equations, yielded the best performance when compared with the other combinations.

2022 ◽  
Vol 22 (1) ◽  
Saeed Akhtar ◽  
Eisa Aldhafeeri ◽  
Farah Alshammari ◽  
Hana Jafar ◽  
Haya Malhas ◽  

Abstract Background The aims of this cross-sectional study were to i) assess one-year period prevalence of one, two, three or more road traffic crashes (RTCs) as an ordinal outcome and ii) identify the drivers’ characteristics associated with this ordinal outcome among young adult drivers with propensity to recurrent RTCs in Kuwait. Methods During December 2016, 1465 students, 17 years old or older from 15 colleges of Kuwait University participated in this cross-sectional study. A self-administered questionnaire was used for data collection. One-year period prevalence (95% confidence interval (CI)) of one, two, three or more RTCs was computed. Multivariable proportional odds model was used to identify the drivers’ attributes associated with the ordinal outcome. Results One-year period prevalence (%) of one, two and three or more RTCs respectively was 23.1 (95% CI: 21.2, 25.6), 10.9 (95% CI: 9.4, 12.6), and 4.6 (95% CI: 3.6, 5.9). Participants were significantly (p < 0.05) more likely to be in higher RTCs count category than their current or lower RCTs count, if they habitually violated speed limit (adjusted proportional odds ratio (pORadjusted) = 1.40; 95% Cl: 1.13, 1.75), ran through red lights (pORadjusted = 1.64; 95%CI: 1.30, 2.06), frequently (≥ 3) received multiple (> 3) speeding tickets (pORadjusted = 1.63; 95% CI: 1.12, 2.38), frequently (> 10 times) violated no-parking zone during the past year (pORadjusted = 1.64; 95% CI: 1.06, 2.54) or being a patient with epilepsy (pORadjusted = 4.37; 95% CI: 1.63, 11.70). Conclusion High one-year period prevalence of one, two and three or more RTCs was recorded. Targeted education based on identified drivers’ attributes and stern enforcement of traffic laws may reduce the recurrent RTCs incidence in this and other similar populations in the region.

2022 ◽  
Marius Girtan ◽  
Valeriu Stelian Nițoi ◽  
Constantina Chiriac ◽  

The paper brings to the fore the need for state support by making investments in railway infrastructure, in order to maintain and ensure the success of railway transport of trucks by introducing RO-LA transport in rail traffic. Using this mode of transport reduces the cost of maintaining road infrastructure, protects the environment, reduces fuel consumption, and reduces road traffic congestionRO-LA transport is an alternative solution to auto transport and contributes to the streamlining of traffic of goods and people.

2022 ◽  
Vol 2022 ◽  
pp. 1-7
Yuan Lu ◽  
Shengyong Yao ◽  
Yifeng Yao

Congestion and complexity in the field of highway transportation have risen steadily in recent years, particularly because the growth rate of vehicles has far outpaced the growth rate of roads and other transportation facilities. To ensure smooth traffic, reduce traffic congestion, improve road safety, and reduce the negative impact of air pollution on the environment, an increasing number of traffic management departments are turning to new scientifically developed technology. The urban road traffic is simulated by nodes and sidelines in this study, which is combined with graph theory, and the information of real-time changes of road traffic is added to display and calculate the relevant data and parameters in the road. On this foundation, the dynamic path optimization algorithm model is discussed in the context of high informationization. Although the improved algorithm’s optimal path may not be the conventional shortest path, its actual travel time is the shortest, which is more in line with users’ actual travel needs to a large extent.

Olga Shevchenko

The last decade reflects undeniable rapid growth in intelligent connected mobility in the European Union and internationally. Whereas automotive producers united forces to address the projected technical difficulties vis-à-vis the deployment of Intelligent Connected Vehicles through coordinated efforts and partnerships, academia is committed to clarifying fundamental new regulatory concepts to reveal potential and foreseeable legal inconsistencies in such technological development. The lack of a determination of the fundamental legal concepts or the vague and ambiguous determination of essential regulatory concepts creates overall legal uncertainty and is considered an obstacle to ensuring the smooth market penetration of Intelligent Connected Vehicles in the European Union. This article claims its contribution to existing literature by integrating further unambiguous and specific regulatory concepts in the context of the regulation of Intelligent Connected Vehicles. This article addresses: (i) the prerequisites for uniform Intelligent Connected Vehicles’ fundamental regulatory concepts based on complex retrospective analysis vis-à-vis road traffic accidents involving conventional vehicles and (ii) the prototype of regulatory concepts that need to be established and accurately distinguished for intelligent connected mobility 4.0, with the cross-border element at the European Union level.

2022 ◽  
Daniel Bramich ◽  
Monica Menendez ◽  
Lukas Ambühl

<div>Understanding the inter-relationships between traffic flow, density, and speed through the study of the fundamental diagram of road traffic is critical for traffic modelling and management. Consequently, over the last 85 years, a wealth of models have been developed for its functional form. However, there has been no clear answer as to which model is the most appropriate for observed (i.e. empirical) fundamental diagrams and under which conditions. A lack of data has been partly to blame. Motivated by shortcomings in previous reviews, we first present a comprehensive literature review on modelling the functional form of empirical fundamental diagrams. We then perform fits of 50 previously proposed models to a high quality sample of 10,150 empirical fundamental diagrams pertaining to 25 cities. Comparing the fits using information criteria, we find that the non-parametric Sun model greatly outperforms all of the other models. The Sun model maintains its winning position regardless of road type and congestion level. Our study, the first of its kind when considering the number of models tested and the amount of data used, finally provides a definitive answer to the question ``Which model for the functional form of an empirical fundamental diagram is currently the best?''. The word ``currently'' in this question is key, because previously proposed models adopt an inappropriate Gaussian noise model with constant variance. We advocate that future research should shift focus to exploring more sophisticated noise models. This will lead to an improved understanding of empirical fundamental diagrams and their underlying functional forms.</div><div><br></div><div>Accepted by IEEE Transactions On Intelligent Transportation Systems on 14th Dec 2021<br></div><br>

2022 ◽  
Vol 1 (15) ◽  
pp. 127-130
Vera Aslamova ◽  
Polina Kuznetsova ◽  
Aleksandr Aslamov

The article analyzes the indicators of road traffic accidents for 2020 in the Irkutsk region and Russia. The main reasons for the implementation of road accidents are identified. The current state of road safety has been analyzed within the framework of the Safe and High-Quality Roads Project. An excess of the actual values of social and transport risks was established by 1.19 and 1.38 times the corresponding Russian indicators

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