scholarly journals Traffic Accidents Severity Prediction using Support Vector Machine Models

2020 ◽  
Vol 9 (7) ◽  
pp. 1345-1350
Keyword(s):  
Support Vector Machine ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Children And Youth ◽  
Support Vector ◽  
Road Traffic Accidents ◽  
Linear Kernel ◽  
Road Accidents ◽  
Severity Prediction ◽  
Decision Making Model

In recent years, road traffic accidents (RTA) have become one of the highest national health concerns worldwide. RTA have become the leading cause of losing lives among children and youth. Recent studies have proven that Data Mining Techniques can break down the complexity that prevails between RTA and corresponding factors. In this paper, Support Vector Machine (SVM) based on Radial basis function (RBF) and Linear Kernel Function is applied to predict fatal road accidents in Lebanon. The experimental results reveal that SVM using RBF give the highest accuracy (86%) and the best AUC (86.6%). The obtained decision-making model claims to tackle the fatal RTA phenomenon.

scholarly journals Comparison of Prediction Models for Mortality Related to Injuries from Road Traffic Accidents after Correcting for Undersampling

2021 ◽  
Vol 18 (11) ◽  
pp. 5604
Author(s):  
Yookyung Boo ◽  
Youngjin Choi
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
National Level ◽  
Brier Score ◽  
Support Vector ◽  
Main Diagnosis ◽  
Road Traffic Accidents ◽  
Multiple Variables ◽  
Type Of Injury ◽  
Kernel Model

In this study, four models—logistic regression (LR), random forest (RF), linear support vector machine (SVM), and radial basis function (RBF)-SVM—were compared for their accuracy in determining mortality caused by road traffic injuries. They were tested using five years of national-level data from the Korea Disease Control and Prevention Agency’s (KDCA) National Hospital Discharge In-Depth Survey (2013 through to 2017). Model performance was measured for accuracy, precision, recall, F1 score, and Brier score metrics using classification analysis that included characteristics of patients, accidents, injuries, and illnesses. Due to the number of variables and differing units, the rates of survival and mortality related to road traffic accidents were imbalanced, so the data was corrected and standardized before the classification models’ performances were compared. Using the importance analysis, the main diagnosis, the type of injury, the site of the injury, the type of injury, the operation status, the type of accident, the role at the time of the accident, and the sex were selected as the analysis factors. The biggest contributing factor was the role in the accident, which is the driver, and the major sites of the injuries were head injuries and deep injuries. Using selected factors, comparisons of the classification performance of each model indicated RBF-SVM and RF models were superior to the others. Of the SVM models, the RBF kernel model was superior to the linear kernel model; it can be inferred that the performance of the high-dimensional transformed RBF model is superior when the dimension is complex because of the use of multiple variables. The findings suggest there are limitations to analyses involving imbalanced, multidimensional original data, such as data on road traffic mortality. Thus, analyses must be performed after imbalances are corrected.

scholarly journals Comparative Study of Machine Learning Classifiers for Modelling Road Traffic Accidents

2022 ◽  
Vol 12 (2) ◽  
pp. 828
Author(s):  
Tebogo Bokaba ◽  
Wesley Doorsamy ◽  
Babu Sena Paul
Keyword(s):  
Machine Learning ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Real Life ◽  
Support Vector ◽  
Road Traffic Accidents ◽  
Machine Learning Classifiers ◽  
Reduction Techniques ◽  
Learning Classifiers ◽  
Accident Data

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.

scholarly journals Traumatic and Nontraumatic Driving Accidents Due to Dry Spells in Northern Iran: A Time Series Analysis

2018 ◽  
Vol 10 (4) ◽  
pp. 723-730
Author(s):  
Enayatollah Homaie Rad ◽  
Shahrokh Yousefzadeh-Chabok ◽  
Zahra Mohtasham-Amiri ◽  
Naeima Khodadadi-Hasankiadeh ◽  
Ali Davoudi-Kiakalayeh ◽  
...  
Keyword(s):  
Time Series ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Dry Period ◽  
The Caspian Sea ◽  
Northern Iran ◽  
Dry Spells ◽  
Dry Spell

Abstract Driving in rain is very dangerous, and drivers seem not to drive properly whenever it rains. In such situations, the risk of driving increases on rainy days, especially after a prolonged dry period. This would be a problem for drivers steering on slippery roads. In this study, the effect of dry spells on road traffic accidents and resulting mortality in Rasht, Iran, located in the southern margin of the Caspian Sea, in a 3-yr period from 21 March 2014 to 19 March 2017 was examined using time series patterns. The results of the study showed that the first day after a dry spell had the greatest impact on road accidents and resulting injuries and deaths. It was also found that with increased length of a dry spell, the risk of accidents and related deaths and injuries rises.

scholarly journals Road Traffic Accidents by 'Nasimon' and 'Karimon'-A Study in Faridpur

2012 ◽  
Vol 7 (1) ◽  
pp. 6-9
Author(s):  
ASMJ Chowdhury ◽  
MS Alam ◽  
SK Biswas ◽  
RK Saha ◽  
AR Mondal ◽  
...  
Keyword(s):  
Low Socioeconomic Status ◽  
Urban Areas ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Motor Vehicles ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
College Hospital ◽  
Medical College

Road traffic accidents in Bangladesh have been rapidly increasing with huge mortality through road accidents each year. There are many causes of road accidents in recent years; one important cause is running of locally made improvised three wheelers (flat bed tricycle) in the urban areas and also on the highways, popularly known as 'Nasimon' and 'Karimon'. This prospective study was carried out in Faridpur Medical College Hospital from January through June 2011, to study the accident patients caused by 'Nasimon' and 'Karimon'. Fifty six (12%) patients were of RTA by 'Nasimon' and 'Karimon' out of a total of 468 patients admitted into our hospital during this period. Most patients (41, 73.21%) were male, highest accidents (24, 42.86%) were observed among 21-30 years age group and most victims (33, 58.93%) were belonged to low socioeconomic status. Commonest (31, 55.36%) victims were passengers of 'Nasimon' and 'Karimon' while maximum number of accidents (46, 82.14%) took place in the urban areas and on the highways. Injury pattern of victims were similar to that found in any other road accident patients. These three wheelers 'Nasimon' and 'Karimon' are run in violating of Bangladesh Motor Vehicles Act (1983) as they are totally unfit for plying on the highways. Strict surveillance against these illegal and risky vehicles on the highways and in the urban areas by law enforcing agencies is required as a measure to reduce the burden of road accidents in our country.DOI: http://dx.doi.org/10.3329/fmcj.v7i1.10289Faridpur Med. Coll. J. 2012;7(1): 06-09

scholarly journals Delivery of First Aid to Victims in Road Transportation Accidents

2020 ◽  
Vol 9 (3) ◽  
pp. 417-421
Author(s):  
A. V. Baranov
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Human Life ◽  
First Aid ◽  
The State ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Road Transportation ◽  
Scientific Publications ◽  
Road Traffic Injuries

Relevance. Most of the victims of road accidents die prior to the arrival of medical staff, therefore, providing first aid to injured people in the first minutes after receiving injuries is very important for saving human life and health. Timely and skillful provision of first aid to victims of road accidents prevents further deterioration of the state of the human body and can positively affect the entire process of its further treatment and rehabilitation.Aim of study. To characterize the delivery of first aid to victims of road traffic accidents at the present stage and to outline possible ways for its improvement.Material and methods. To achieve this goal, an analysis was made of the results of domestic and foreign scientific research and regulatory legal acts on the issue of providing first aid to victims of road accidents. The literature search was carried out in specialized scientific search engines eLibrary, PubMed, Scopus using the keywords: first aid, prehospital stage, road traffic injuries, road traffic accidents. For the analysis, scientific articles published between 1980 and 2020 were selected. Resources with outdated or inaccurate information were excluded, some scientific papers were found by links to articles. The state of the problem of providing first aid to victims of road traffic injuries, for the most part, reflects scientific publications over the past ten years.

scholarly journals Driving Culture in Iran

2018 ◽  
Vol 35 (2) ◽  
pp. 107-111
Author(s):  
Shirin Saeidi
Keyword(s):  
Middle East ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Political Life ◽  
Internal Conflict ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Political Climate ◽  
Legal Structure ◽  
The Relationship

Driving Culture in Iran creatively explores the relationship between legalculture and citizenry formation in post-revolutionary Iran. Banakar focusseson driving customs and explanations for citizens’ disregard of trafficlaws, demonstrating that the exceptionally high rates of road accidents andlack of law abidance is due to the complex cultural and political climate. Themonograph argues that the state’s propaganda machine promotes revolutionaryzeal but in a context where people are penalized if they dissent (3). Consequently, dissension becomes a tool for control, setting into motionmultiple forms of internal conflict which are reflected in the way Iraniansrelate to one another as well as in increasing rates of road traffic accidents(4). The originality of the study rests in its exploration of political life atthe juncture of law and culture. Through his analysis of the unintendedcultural outcomes of the legal structure in Iran, Banakar contributes to ourunderstanding of citizenship formation in hybrid and religiously chargedregimes. In particular, the book illustrates how citizens’ distrust of the statecan have deadly consequences on Iran’s roads. The monograph will be ofinterest to academics and other professionals working on the Middle East,Islam, and from a multitude of disciplinary perspectives ...

scholarly journals Road Traffic Accidents Analysis Using Data Mining Techniques

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
G. Janani ◽  
N. Ramya Devi
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Rule Mining ◽  
Data Mining Techniques

Road Traffic Accidents (RTAs) are a major public concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, RTAs are among the leading cause of death and injury. Most of the analysis of road accident uses data mining techniques which provide productive results. The analysis of the accident locations can help in identifying certain road accident features that make a road accident to occur frequently in the locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. Data analysis has the capability to identify different reasons behind road accidents. In the existing system, k-means algorithm is applied to group the accident locations into three clusters. Then the association rule mining is used to characterize the locations. Most state of the art traffic management and information systems focus on data analysis and very few have been done in the sense of classification. So, the proposed system uses classification technique to predict the severity of the accident which will bring out the factors behind road accidents that occurred and a predictive model is constructed using fuzzy logic to predict the location wise accident frequency.

scholarly journals A Comparison of Nowruz 2016 and Nowruz 2017 Accidents Data in Iran

2020 ◽  
Vol 5 (2) ◽  
pp. 71-78
Author(s):  
Abdolmajid Rahmani Daranjani ◽  
◽  
Mahmoud Rezaeizadeh ◽  
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Road Transport ◽  
Warning Signs ◽  
World Health ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Factors Affecting ◽  
The World ◽  
On The Road

Background: Road traffic accidents are currently among the most essential public health issues. According to the World Health Organization, given the rapid growth of road transport globally, road traffic accidents could be the third leading cause of death and disability in the world by 2020. This article examined the role of the human factor in road accidents during the Nowruz holidays, as a major cultural event in Iran. Materials and Methods: We explored the data of road accidents that occurred in Nowruz in 2016 and 2017 in Iran. Traffic accident data concerning the Nowruz holidays of 2016 and 2017 were collected by census method of sampling and based on the report of highway police. Additionally, the frequency of these accidents was analyzed according to travel time, accident type, gender, age, education, and vehicle type in different provinces. Results: The present study findings suggested that among human factors affecting Nowruz accidents in 2016 and 2017, the highest frequency belonged to unnecessary speeding. As in 2016 and 2017, it was the main responsible characteristic for 56.42% and 55.01% of accidents, respectively. In Nowruz 2016, the provinces of Tehran, Khorasan Razavi, Isfahan, Fars, and Khuzestan; in Nowruz 2017, the provinces of Tehran, Isfahan, Khorasan Razavi, Fars, and Gilan encountered the highest rates of accidents leading to injuries and deaths. Conclusion: To control unnecessary speeding and regulations disregard, planning for culturizing and the community-level education are suggested. Besides, increasing the quality and intelligence of vehicles and the construction of sliders, vertical lines on the road, warning signs, and billboards could help reduce the rate of accidents. Creating a working group of experts in psychology, traffic, etc., to study the pathology of dangerous behaviors, useless haste, and disregard for regulations and providing solutions could also be effective.

scholarly journals Analysis Of Road Accidents Involving Children

2020 ◽  
Vol 02 (10) ◽  
pp. 25-27
Author(s):  
Ikromov Ikboljon Abdukhalilovich ◽  
◽  
Akhunov Javlon Abdujalilovich ◽  
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
New Technologies ◽  
Statistical Data ◽  
Road Traffic ◽  
Educational Institutions ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Safety Rules

The article presents the analysis of statistical data of drilling road accidents with children. Proposals are given for the development of new technologies for the prevention of injuries to children in road traffic accidents, as well as training them in road safety rules and ensuring the safety of pedestrians on the roads around educational institutions.

REDUCTION OF RETAIL TRADE IN ALCOHOLIC PRODUCTS AS A FACTOR OF REDUCING THE NUMBER OF ACCIDENTS ON THE ROADS OF RUSSIA

2020 ◽  
pp. 39-42
Author(s):  
Т.М. Мазурчук ◽  
К.К. Беляева ◽  
А. Чосович
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Scientific Publication ◽  
Scientific Basis ◽  
Retail Trade ◽  
Alcoholic Beverages ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
Expert Assessments ◽  
The Relationship

В научной публикации изучаются показатели реализации алкоголя в розничной торговле и статистики по дорожно-транспортным происшествиям в России. Употребление алкоголя как пешеходами, так и водителями транспортного средства является одним из основных факторов возникновения дорожно-транспортных происшествий на автомобильных дорогах во всем мире. Поэтому цель работы заключается в определении зависимости между объемами реализации алкогольной продукции в розничной торговле и динамикой дорожно-транспортных происшествий на дорогах России. Для выявления зависимости между исследуемыми показателями в статье используются методы сравнительного и корреляционного анализа, экспертных оценок, а также метод выделения главной. Научной базой исследования послужили публикации российских экспертов, сведения международных организаций, нормативно-правовые документы,данные Министерства здравоохранения и Министерства внутренних дел РФ. The scientific publication examines the indicators of alcohol sales in the retail trade and statistics on road traffic accidents in Russia. Alcohol consumption is a major contributor to road traffic accidents around the world, both by pedestrians and drivers. Therefore, the aim of the work, the authors set themselves to determine the relationship between the volume of sales of alcoholic beverages in retail trade and the dynamics of road accidents on the roads of Russia. To identify the relationship between the studied indicators, the article uses the methods of comparative and correlation analyzes the method of expert assessments, as well as the method of highlighting the main one. The scientific basis of the study was the publications of Russian experts, data from international organizations, regulatory documents, data from the Ministry of Health and the Ministry of Internal Affairs of the Russian Federation.

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