Analysis Of Traffic Accidents Research Articles

Multi-criteria analysis of technical solutions for increasing level crossing safety: case study level crossing Poznanovec in Croatia

The paper includes safety and traffic accidents analysis of the level crossing Poznanovec located in the northwest region of Croatia. Based on the analysis of the accidents new low-cost technical solutions were proposed to increase safety on level crossing Poznanovec. A total of three variants were proposed with each composed of low-cost technical solutions and evaluated by AHP method (Analytic Hierarchy Process) as one of the methods for Multi-Criteria analysis. The AHP model consisted of six criteria: safety, financial cost, construction, ecological, spatial-urban and traffic-technological criterion. The AHP method was implemented in the software Expert choice which was used to determine the best-ranked variant solution. A sensitivity analysis was performed to confirm the acceptability of the best-ranked variant. The results showed that best-ranked variant for reconstruction is Variant 1. The practical implications of the results and the possibilities of best-ranked variant implementation are discussed.

Analysis of traffic accidents with fuzzy and crisp data mining techniques to identify factors affecting injury severity

Injury severity in motor vehicle traffic accidents is determined by a number of factors including driver, vehicle, and environment. Airbag deployment, vehicle speed, manner of collusion, atmospheric and light conditions, degree of ejection of occupant’s body from the crash, the use of equipment or other forces to re-move occupants from the vehicle, model and type of vehicle have been considered as important risk factors affecting accident severity as well as driver-related conditions such as age, gender, seatbelt use, alcohol and drug involvement. In this study, we aim to identify important variables that contribute to injury severity in the traffic crashes. A contemporary dataset is obtained from National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS). To identify accident severity groups, we performed different clustering algorithms including fuzzy clustering. We then assessed the important factors affecting injury severity by using classification and regression trees (CRT). The results which would guide car manufacturers, policy makers and insurance companies indicate that the most important factor in defining injury severity is deployment of air-bag, followed by extrication, ejection occurrences, and travel speed and alcohol involvement.

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction

Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this work is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR), and naive Bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using the C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Further, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots.

Analysis of Fatal and Injury Traffic Accidents in Istanbul Sarıyer District with Spatial Statistics Methods

Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been carried out in the world and in Turkey to reduce the number of traffic accidents, but these studies have not been very effective in reducing accidents. In this study, 3105 fatal or injured traffic accidents between 2010–2017 in Sarıyer district of Istanbul, Turkey’s largest city in terms of population, were discussed. We analyzed the statistical information on the subject in detail within the framework of geographic information systems. It has been tried to determine the sections where traffic accidents are concentrated in this region with studies based on spatial methods. Thematic accident map was created according to the accident types. In this context, the advantages and disadvantages of these methods were compared using Point Density, Kernel Density, Getis Ord Gi*, and Anselin Local Moran’s I (LISA) Spatial Autocorrelation. In addition, in order to observe the change in accidents, thematic accident and Kernel Density maps were created separately according to accident occurrence types in the beginning and last year. From this point of view, the changes that occurred in the accidents were interpreted. The current study determined that the most accidents were on some streets and these streets divided into regions in a plan. The cases were examined with statistical analyses according to accident types and using the Kernel Density method. In addition, it has been observed that Kernel Density method gives better visual results than other spatial methods. In this study, spatial analysis and statistical analysis methods were used to evaluate traffic accidents more realistically. The day of the week effect and month of the year effect on traffic accidents was investigated for the first time. In addition, it is proposed to bring a new approach to the prevention of traffic accidents by using hotspot, accident type, and day of the week effect.

Analysis and forecast of road traffic accident in Saudi Arabia from 1990 until 2018

Background: Road traffic accidents (RTAs) are an epidemic problem in Saudi Arabia, resulting in high morbidity and mortality rates. This paper investigates the increasing number of RTAs and their related injuries and mortalities in Saudi Arabia.Methods: This study was performed on the population of Saudi Arabia using secondary data from the general authority for statistics from 1990 to 2018. Correlation among the variables (RTAs, injuries, mortalities, and population) was conducted using statistical package for the social sciences (SPSS), and forecasts of their trends over the next ten years using linear regression was discussed.Results: Eastern, Makkah and Riyadh regions were the top three regions in the number of RTAs accounting for 69% of the total RTAs in Saudi Arabia. All regions have had a pattern of RTA rise from 1990 till 2014 that dropped in the last 4 years. Riyadh had the highest injury rate per 10,000 RTA, although it had the lowest RTA rate per 100,000 population in the period from 2010-2014. Mortality rate in Riyadh doubled between the years 2014 and 2018 while Makkah accounted for the highest RTA-related mortality rates. The correlation between RTAs and mortalities were the highest in the country (r=0.92). In 2030, the average annual increase in the rate of RTAs, related injuries, and related mortalities will be 3%, 2% and 2.1%, respectively.Conclusions: Decision makers in Saudi traffic and transportation department should continue monitoring accidents prevention strategies and their effect. Reasons behind high injury and mortality rates, despite the decrease in the rate of RTAs, should be investigated.

Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.

EDR, DTG 데이터를 이용한 PC-Crash와 Carmaker 프로그램의 검증 및 신뢰성에 관한 연구

The event recording devices such as EDR and DTG have recently been developed and installed in automobiles. The reliability of EDR application is being conducted in many previous studies, but with the development and development of autonomous vehicles, it is necessary to study the reliability of EDR and DTG application results for programs that can analyze autonomous driving. Therefore, in this study, the analysis was carried out in a way to secure the reliability of the application results of EDR and DTG of Carmaker, which can analyze the traffic accident analysis program PC-Crash and autonomous driving, and secure the reliability of the Carmaker program that applied EDR in Korea and abroad. As a result of the analysis, it was found that the speed error rate gradually increased from high speed to low speed, and the maximum error speed was less than 5 km/h through the average error rate for each speed. In the future, it is thought that it can be usefully used for analysis of traffic accidents in the event of autonomous vehicle accidents.

Image and Video Dehazing based on Gamma Correction Method Contrast Enhancement

As the revolution in computational photography and computer vision applications facilitates fast and reliable information, quality of the scene and visual perception and is being increasingly used in various fields like public safety, traffic accident analysis, crime forensics, remote sensing area and military surveillance. We make an investigation of the dehazing effect of scenes affected by weather phenomena. ‘Dehazing’ has emerged as a promising technology to recover the clear image and video from an input hazy scene, such that the quality can be significantly enhanced. A scene captured in the outdoor environment affected by haze like fog mist and dust particles in the atmosphere. We are utilizing a ‘Dehazing algorithm, to remove this unwanted haze from videos and Real-time video. Also, remove haze from images, for this, we use a novel method of video dehazing based on contrast enhancement. From our observation, it is concluded that hazy image and video has low contrast, so we estimate transmission map to maximize the contrast of output scene. And we use the depth estimation process to detect or identify hidden parameters from the scene, and also creates a corresponding haze scene with high fidelity. Finally, we reconstruct or restore the seen without changing its originality. Hence dehazing performance with fewer artifacts and better coding efficiency and demonstrate that the proposed algorithm can remove haze efficiently and recover the parameters of the original scene

Geospatial analysis of severe road traffic accidents in Singapore in 2013-2014.

Injury is a significant cause of mortality and morbidity. We aimed to investigate which areas in Singapore have a significantly higher incidence of road traffic accidents (RTA) resulting in severe injuries (Tier 1), which is defined as an Injury Severity Score (ISS) greater than 15, and to develop a spatiotemporal model. Data was obtained from the National Trauma Registry. The RTA locations were geomapped onto the Singapore map, and spatial statistical techniques were used to identify hotspots with the Getis-Ord Gi* algorithm. From 1 January 2013 to 31 December 2014, there were 35,673 people who were injured as a result of RTAs and 976 Tier 1 RTA victims. A total of 920 people were included in the geospatial analysis. Another 56 were involved in RTAs that did not occur within Singapore or had missing location data and thus were not included. 745 (81.0%) were discharged alive, whereas 175 (19.0%) did not survive to discharge (median ISS 38.00, interquartile range 30.00-48.00). Most of the Tier 1 RTA victims were motorcycle riders (50.1%, n = 461), pedestrians (21.8%, n = 201) and cyclists (9.9%, n = 91). The majority were male and aged 20-40 years, and there was a peak occurrence at 0600-0759 hours. Nine hotspots were identified (p < 0.01). Information from studying hotspots of RTAs, especially those resulting in severe injuries, can be used by multiple agencies to direct resources efficiently.

Eliciting a mathematical model from the traffic safety index to estimate the number of road traffic accidents

Traffic accidents have become one of the most important problems experienced by countries, leading to the death or injury of many people and the waste of money, which is supposed to be spent on developmental and economic projects that benefit the entire society. In Iraq with the absence of suitable recording system of (Iraqi Roads Traffic Accident Data) and the lack in the measure of highway safety. Thus, lead to error in the analysis of traffic accidents. The aim of this study is to estimate Road Safety Index value and developing a model related it with Road Traffic Accident. To reach the research aim, parameters of Roadway, traffic, Roadside, Pavement and Miscellaneous, characteristics of ten cities in central and southern Iraq (Baghdad, Babylon, Karbala, Najaf, Qadissiya, Muthanna, Dhi Qar, Wasit, Maysan and Basra) were studied. The results show that the extra increase of Road Traffic Accident can be represented by negative exponential trend in relation with Road Safety Index, at 0.05 level of significance 87.6% of variation in Road Safety Index can be accounted for by exponential relationship with Road Traffic Accident.

Traffic accident analysis and Control Countermeasures of fatigue driving on Expressway

In the current high-speed accidents, there is a great cause of fatigue driving. This paper first analyzes the law of fatigue driving accidents on expressways, including time distribution, type distribution and other distribution characteristics of accidents in various states. Secondly, it investigates the sections with heavy traffic accidents and frequent accidents, so as to analyze and find out the unreasonable and deficiencies. Finally, it summarizes the shortcomings of expressway, combined with the fatigue driving accidents caused by human subjective factors, suggestions and improvements are made. Through this study, for the prevention of fatigue driving accidents, drivers need to improve their safety awareness, family supervision and social supervision is very important, and after the accident, we need to correctly handle the results of the accident.

التحليل المکاني للحوادث المرورية الجسيمة في مدينة أبها عام 1441 باستخدام نظم المعلومات الجغرافية. Spatial analysis of serious traffic accidents in the city of Abha, Kingdom of Saudi Arabia 1441 Using GIS

هدفت الدراسة إلى التعرف على التوزيع المکاني للحوادث المرورية الجسيمة في مدينة أبها عام 1441 وخصائص هذه الحوادث وما نتج عنها من وفيات. اعتمدت الدراسة على المنهج الوصفي التحليلي لبيانات الظاهرة. الحوادث المرورية الجسيمة في منطقة الدراسة ما زالت مرتفعة، ترکزت الحوادث على الطرق الرئيسة. جاء طريق الملک فهد في المرتبة الأولى واستأثر أيضا بأکثر من ثلث حوادث الدهس. غالبية الوفيات کانت في الفئة العمرية (18 - 36) والغالبية من الذکور. عدم الالتزام بالقواعد والأنظمة المرورية کان السبب الرئيس، أکثر من (71 %) من الحوادث المرورية کانت حوادث اصطدام. اتضح توزيعا متساو إلى حد ما بين الحوادث النهارية والليلية. ترکزت حوادث النهار بين الساعة الثانية بعد الظهر إلى الثالثة بينما ترکز خمس الحوادث الليلية بين الساعة السابعة والثامنة مساء. جاءت أيام الاثنين في المرتبة الأولى، بينما أيام الخميس أقل حوادث. التوزيع الشهري، سجلت أقل نسبة للحوادث في شهر رمضان، بينما کانت أعلى نسبة في أشهر ذو القعدة، شوال وذو الحجة على التوالي. بلغت وفيات الحوادث في مدينة أبها (55) وفاة. أثبتت السياسات التي انتهجتها إدارة المرور نجاحها بشکل جيد بالمقابل ما زال عدم الالتزام بقواعد المرور وأنظمته يمثل تحد للمسؤولين. توعية المجتمع وخاصة فئة الشباب أمر على جانب کبير من الأهمية. تخطيط شبکة الطرق في مدينة أبها يحتاج إلى إيجاد طرق التفافية خارج المدينة، إعادة هندسة الحرکة المرورية على الطرق القائمة حاليا لتسهيل الحرکة المرورية الاستفادة من تقنيةGIS أمر مهم.

Development of road infrastructure safety management system according to updates of EU Directive 96/2008/EC

The traditional approach to the analysis of traffic accidents has mostly involved identifying omissions in vehicles and drivers, which led to the occurrence of a traffic accident. However, more recent EU directives dealing with this area emphasize infrastructure failures that may be the real cause of the accident. This approach refers to preventive action, ie the design of such infrastructure that will, in case of failure of the driver, "forgive" the driver his mistake and prevent the occurrence of a traffic accident or reduce the consequences of a traffic accident. To achieve this, a completely new approach to the problem is needed, ie to build, reconstruct and regenerate the road infrastructure according to its real function from the aspect of traffic safety. The realization of these concepts in our area implies primarily the education of all entities that have contact with road infrastructure (designers, managers, auditors, etc.), with emphasis on the fact that savings on the material are significantly less than the savings achieved by reducing the number of accidents, with injured faces and fatalities.

Spatial Analysis of Traffic Accidents in the Iraqi Middle Euphrates Provinces: A Case Study

Traffic accidents are among the most important problems that leave economic and social impacts as a burden on the citizen. Inaddition, they leave economic costs in terms of material or human losses. Some traffic accidents lead to a permanent disability or temporary disability that needs a period of time, which of course, requires financial costs for the purpose of medical treatment. The problem of traffic accidents is witnessing an increase at the present time. This is primarily attributed to the increase in the number of residents and vehicles of various kinds. They leave negative effects, which became a human tragedy. Therefore, this problem can be attributed to a set of factors causing the increase in traffic accidents of various types, such as those accidents related to the driver, including lack of compliance with the law, regulations, traffic signals, lack of maintenance for the transportation network in general, as well as failure to adhere to the legal age related to the driver’s age and recklessness... etc. The present study aims to study traffic accidents in Iraq in general and in the Middle Euphrates region, as it is a central focus in Iraq, in addition to identifying the causes that led to the development of the problem in the study area and thus taking measures that would reduce or limit the problem.Traffic accidents have recently increased in Iraq at high rates for the period (2001-2018). The total number of traffic accidents reached about (539,496) accidents, according to the statistics of the Ministry of Planning, the Central Agency, the Transportation and Communications Department. This number is considered high in comparison with the population of Iraq.

Road Traffic Accident Analysis and Visualization of Accident Prone Areas

Road Traffic Accident Analysis and Visualization of Accident Prone Areas

The illusion of absence: how a common feature of magic shows can explain a class of road accidents

The purpose of the present note is to draw attention to the potential role of a recently discovered visual illusion in creating traffic accidents. The illusion consists in a compelling and immediate experience that the space behind an occluding object in the foreground is empty. Although the illusion refers to a region of space, which is invisible due to occlusion (a blind spot), there is evidence to suggest that it is nevertheless driven by visual mechanisms and that it can be just as deceptive and powerful as ordinary visual illusions. We suggest that this novel illusion can make situations involving blind spots in a road user's field of view even more dangerous than one would expect based on the lack of visibility by itself. This could be because it erroneously makes the road user feel that (s)he has actually seen everything there is to see, and thus has verified that the blind spot is empty. This hypothesis requires further testing before definitive conclusions can be drawn, but we wish to make researchers and authorities involved in the analysis of traffic accidents and on-the-spot crash investigations aware of its potential role in order to encourage registration of relevant data and facilitate further research.

A probabilistic Bayesian inference model to investigate injury severity in automobile crashes

Big data analytics examines millions, if not billions of records, to unmask hidden patterns, provide actionable insights and interpretable results for various domains. One area that has great potential to leverage the value of big data and analytics is the critical analysis of traffic accidents. Investigation results help in providing an in-depth understanding of the risks and provide measures to potentially prevent these risk factors hence enhancing the well-being of individuals who may experience such accidents. This study explains existing models and proposes a data science methodology in a field where probabilistic modeling makes much sense for faster, better decision-making. The main objective of this data analytics study is to identify the high-risk factors with their apparent significance to influence the probability of injury severity on automobile crashes using a geographically representative car crash dataset. To obtain reliable, accurate, and intuitive results, a multi-step probabilistic inference model based on Bayesian Belief Network— highly-acclaimed machine learning methodology—is proposed. The underlying inference model provides researchers with a causally accurate way to explore the domain (with the subject matter expert inputs) while disengaging issues related to statistical correlations and causal effects. In this study, we also used the data to create a web-based probabilistic inference simulator, a Bayesian inference decision support tool, which will be a publicly available/accessible tool, to help decision-makers better understand and to conduct what-if analysis on variable interdependencies.

Analysing the injury severity characteristics of urban elderly drivers’ traffic accidents through the generalised ordered logit model: A case of Seoul, South Korea

As ageing population is growing faster, traffic accidents involving elderly drivers become a serious social problem in South Korea. The present study aims to examine the impact of environmental characteristics on the injury severity of accidents involving elderly drivers in Seoul, South Korea. To achieve the purpose, the study divided elderly drivers into the following two groups: young-elderly drivers aged 65–69 years and middle- and old-aged drivers over 69 years old. The study also analysed non-elderly drivers aged 30 to 64 years as the comparative group. The study used the generalised ordered logit model, which is widely used to analyse data with ordinal scales. The findings from the study draw attention to the fact that (1) the characteristics of traffic accidents by injury severity considerably differed by age group. (2) risk of accident severity involving elderly drivers increase in areas with heavy traffic volumes and facilities that may create a complex driving condition to elderly drivers, (3) since elderly drivers tend to require longer response time with impaired vision under complex driving environment, it increased the risk of traffic accidents that older drivers face a higher risk of fatal injuries than younger counterparts. Thus, in order to reduce traffic accidents involving elderly drivers, the traffic safety policies should take environmental characteristics as well as the human factor concerning elderly drivers’ difficulties because of ageing and longer cognitive response time. This study contributes to the research in traffic accidents involving elderly drivers in that not only the accident characteristics (human factors, road condition, weather), mostly used for traffic accident analysis, but also environmental factors concerning the urban characteristics of Seoul Metropolitan City were analysed to compare the risk of traffic accidents and accident severity by age groups.

Image and Video Dehazing based on Gamma Correction Method Contrast Enhancement

As the revolution in computational photography and computer vision applications facilitates fast and reliable information, quality of the scene and visual perception and is being increasingly used in various fields like public safety, traffic accident analysis, crime forensics, remote sensing area and military surveillance. We make an investigation of the dehazing effect of scenes affected by weather phenomena. ‘Dehazing’ has emerged as a promising technology to recover the clear image and video from an input hazy scene, such that the quality can be significantly enhanced. A scene captured in the outdoor environment affected by haze like fog mist and dust particles in the atmosphere. We are utilizing a ‘Dehazing algorithm, to remove this unwanted haze from videos and Real-time video. Also, remove haze from images, for this, we use a novel method of video dehazing based on contrast enhancement. From our observation, it is concluded that hazy image and video has low contrast, so we estimate transmission map to maximize the contrast of output scene. And we use the depth estimation process to detect or identify hidden parameters from the scene, and also creates a corresponding haze scene with high fidelity. Finally, we reconstruct or restore the seen without changing its originality. Hence dehazing performance with fewer artifacts and better coding efficiency and demonstrate that the proposed algorithm can remove haze efficiently and recover the parameters of the original scene.