Analysis Of Traffic Accidents Research Articles

Spatio-temporal analysis of road traffic accidents in Indian large cities

IntroductionEvery day 1374 road traffic accidents (RTAs) and 400 deaths take place in India. The number of deaths in RTAs would increase to 662 persons per day in 2030 and will not begin to decline until 2042, which is a serious public health concern. ObjectivesPresent paper attempts to analyse the trends and patterns of RTAs in India during the year 2000–2015, and the patterns in the year 2015 in cities with population size 2 million or more. MethodsThree years moving average is calculated to nullify the fluctuations in the data, exponential curve drawn to assess the pattern. Simple growth rate is calculated and absolute change found out to assess the difference between the year 2000 and 2015. ResultsThe exponential growth rate curve of the number of RTAs shows upward trend during 2000–2015 in India. The spatial analysis of severity shows that there is no direct link between the number of accidents and the severity. The city-wise analysis of RTAs by the vehicle involved, age of the persons, cite, and timing of accidents shows a varying pattern across the cities. ConclusionsThe results suggest for city-based strategies to reduce the RTAs, injuries, and deaths, under the umbrella of national policy.

Traffic Accidents Analysis before and after Mega Earthquakes concerning Road Traffic Environment

Traffic Accidents Analysis before and after Mega Earthquakes concerning Road Traffic Environment

Spatial and Temporal Analysis of Seasonal Traffic Accidents

This paper presents an approach to analyze spatial and temporal (spatiotemporal) patterns of traffic accidents and to organize them according to their level of significance. This approach was tested using three years (2011-2013) of traffic accident data for Sherbrooke. The spatiotemporal patterns of traffic accidents were analyzed using kernel density estimation (KDE) for four different seasons. Two different crash measures were compared: simple crash counts and severity-weighted crash counts. The results show that severity-weighted crash counts reveal the effect of a single fatal/severe injury or light injury crash on the patterns. However, the lack of a significance test is the main drawback of the KDE. Therefore, this paper integrates the KDE with local Moran’s I to identify clusters of statistical significance for traffic accidents within each area. Thus, after the density is calculated by the KDE, it is then applied as the attribute (input value) for calculating local Moran’s I. Our findings show that the method was successful to detect traffic accident clusters and hazardous areas in Sherbrooke.

Analysis of the loss of vehicle motion stability in the conditions of steering control disturbance

Disturbances in the vehicle motion may be caused by different factors and in many cases are the reason for dangerous traffic incidents. Disturbances within the human-vehicle system are particularly hazardous. An innovative method was designed for analyzing and simulating the process of loss of vehicle motion stability after interference in the steering system, e.g. by acting on the steering wheel by the passenger. The subject of the study is the theoretical and experimental analysis of the vehicle motion path kinematics together with the duration of the disturbance, driver’s reaction time and steering wheel turning angles. PC-Crash simulation software was employed for the purpose of studying the disturbance characteristics and their influence on the loss of vehicle motion stability. It is recognized that the studied issues are as yet poorly understood, the presented results expand our knowledge base in this area and can be employed for the purpose of analysis of actual traffic accidents.

Retrospective analysis of pediatric road traffic accidents admitted to the emergency department of a university hospital

Aim: Road traffic accidents are common in our country, but there are not many scientific studies related to childhood road traffic accidents. We aimed to report the frequency of road traffic accidents in children, the demographic characteristics of the patients, the physical effects of accidents on children and their results.Material and Methods: Study data were obtained by retrospective screening of the files of pediatric cases presenting to our emergency department because of road traffic accident between September 2017-2018. The cases were evaluated in terms of age, gender, type of accidents, type of injury, radiologic imaging rates, hospitalization and mortality rates.Results: 377 cases were reviewed. 136 (36.1%) patients were female and 241 (63.9%) were male. 36.9% (n=139) of the admissions were in summer. According to the occurrence of accidents, in-vehicle traffic accidents constituted 61.8% (n=233) of the cases. Among isolated injuries the most common site of injury was head and neck region (n=120, 31.8%). In 81.4% (n=307) of the cases tomography, in 72.1% (n = 273) of cases X-ray, in 25.7% (n=96) of cases ultrasound were requested. 270 (72.2%) patients were discharged from the emergency department with the diagnosis of soft tissue trauma. 58 (15.4%) patients were hospitalized in the respective clinics and 43 (11.4%) patients were hospitalized in the intensive care unit. It was detected that 8 patients (2.1%) died, 4 of them occurred in the emergency department. Conclusion: Pediatric road traffic accidents mostly occur in the summer and most of them are in-vehicle accidents. Boys are more exposed to road traffic accidents. Injuries in traffic accidents mostly locate in the head and neck regions followed by extremities. It was found that tomographic imaging was overused in our study. New strategies should be developed to reduce tomography overuse.

Incidence of Pedestrian Traffic Injury in Sao Paulo Brazil

Pedestrian traffic injuries represent an important cause of mortality, and although the occurrence rates are lower than collisions between vehicles, the lethality is much higher due to the vulnerability of the pedestrians. This study characterized the victims of traffic accidents as to gender, age group, period of occurrence, association with alcohol and drug use, place of accidents, diagnosis of attendance, evolution of victims and types of vehicles involved, in order to assist public managers in intervening in such scenario. It is a cross-sectional, quantitative, descriptive and retrospective epidemiological study of 2719 pedestrians injured in traffic accident records, during 2017 in Sao Paulo, Brazil. Men were involved in 61.9% of the traffic accidents and the most affected age group was between 20 and 24 years (12.4%). The highest incidence was in the afternoon (12.2%), in the South region (4.5%) and 46.3% associated with cars. The lower limb traumas were the most frequent (32.3%) and 76.5% of the victims followed to hospital discharge. This study revealed the importance of the epidemiological analyses of traffic accidents. It is an important tool to guide governments to promote public and drivers education to respect the traffic regulations. And besides, it can be used to manage the assistance of the pedestrian victims of traffic accidents by the maintaining of the pre-hospital and hospital care teams in strategic locations to minimize the time between the accident and the victim’s care by the public Brazilian National Health System (Sistema Unico de Saude - SUS).

Traffic accident analysis based on C4.5 algorithm in WEKA

At present, China is in a period of steady development of highways. At the same time, traffic safety issues are becoming increasingly serious. Data mining technology is an effective method for analysing traffic accidents. In-depth information mining of traffic accident data is conducive to accident prevention and traffic safety management. Based on the data of Wenli highway traffic accidents from 2006 to 2013, this study selected factors including time factor, linear factor and driver characteristics as research indicators, and established the decision tree using C4.5 algorithm in WEKA to explore the impact of various factors on the accident. According to the degree of contribution of each variable to the classification effect of the model, various modes affecting the type of the accident are obtained and the overall prediction accuracy is about 80%.

Big Data Analytics in Intelligent Transportation Systems: A Survey

Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.

Traffic Accident Analysis in Prosses Evidence in Traffic Accidents Based on Act No. 22 of 2009

Proof play an important role in the process of examination of the court, the development progress in the field of information technology and telecommunications, also developed the theories and practices of the use of evidence outside of a predetermined in the procedural law in Indonesia The problems of this study are: traffic accident analysis methods in the process of proving the traffic accident under the Act No. 22 of 2009. Obstacles and solutions in traffic accident analysis methods in the process of proving the traffic accident under the Act No. 22 of 2009.The research approach used adalan normative research. Empirical normative legal research. Data obtained from the study will be analyzed using qualitative methods of normative analysis.Based on this study, the result that the completion of a traffic accident encountered on the streets and certain times and considered as a routine activity, because over the task of administrative services in the field of vehicle or driver in addition to the public discipline road users is still very low. If there is no presence of members of the Police / Traffic Police physically there is a tendency offense by violating traffic signs. So for the purpose of realizing Kamseltibcar Kudus Resort Police and increased professionalism Police Traffic Accident Analysis required implementation by implementing the handling of traffic accident right scene.Keywords: Law Enforcement; Criminal Law Advisory; Traffic Accident Analysis Proof of Traffic Accidents.

The Impact of the Efficiency of the System for Vibrations Damping on the Efficiency of Vehicle Braking

This paper presents the plan and results of the research of the efficiency of the braking system depending on the condition of the shock absorbers and the velocity of the vehicle movement at the moment of braking. As expected, it has been proven that the braking efficiency decreases with decreasing efficiency of the system for damping vibrations. The interdependence of these two systems is also represented by a mathematical model that can serve for practical purposes in the analysis of traffic accidents.

고속도로 위험물질수송차량 사고데이터 분석을 통한 위험요인 도출 연구

Traffic accidents of hazardous material transport vehicles are occurring steadily while traffic accidents on expressways have been declining for decades. The risk of a hazardous material transport vehicle is much higher than that of other transportation modes because of the possibility of exposure or leakage of dangerous materials loaded in the event of a collision. Especially, the expressway has the high-speed limit and high traffic volume, thereby the socioeconomic loss in case of an accident is huge. To date, there has been a very limited analysis of traffic accidents involving hazardous materials transporting vehicles on highways in spite of the high risk of vehicle accidents. Therefore, this study is very meaningful in that it analyzes for the first time the accident patterns of the vehicle carrying the hazardous materials on the expressway. Crash data for the 11-year period from 2007 to 2017 was provided by Korea Highway Corporation, and accident data of transportation vehicles for hazardous materials were extracted from the database. The extracted data were analyzed by year, accident cause, severity, geometric structure, road facility, Time, and route, and we derived the crash patterns and implications of the hazardous material transport vehicle accident. Based on the results of this study, systematic management and policy directions of expressway hazardous materials transportation vehicles are suggested.

Analysis of traffic accidents involving 119 emergency vehicles

Analysis of traffic accidents involving 119 emergency vehicles

Reliability verification of vehicle speed estimate method in forensic videos

In various types of traffic accidents, including car-to-car crash, vehicle–pedestrian collision, and hit-and-run accident, driver overspeed is one of the critical issues of traffic accident analysis. Hence, analysis of vehicle speed at the moment of accident is necessary. The present article proposes a vehicle speed estimate method (VSEM) applying a virtual plane and a virtual reference line to a forensic video. The reliability of the VSEM was verified by comparing the results obtained by applying the VSEM to videos from a test vehicle driving with a global positioning system (GPS)-based Vbox speed. The VSEM verified by these procedures was applied to real traffic accident examples to evaluate the usability of the VSEM.

Analysis of Child-related Road Traffic Accidents in Vietnam

In recent years, the number of road traffic accidents, fatalities and injuries have been decreasing, but the figures of children road traffic accidents have been increasing in Ho Chi Minh City of Vietnam. This fact strongly calls for implementing effective solutions to improve traffic safety for children by the local government. This paper presents the trends, patterns and causes of road traffic accidents involving children based on the analysis of road traffic accident data over the period 2010-2015 and the video-based observations of road traffic law violations at 15 typical school gates and 10 typical roads. The results could be useful for the city government to formulate solutions to effectively improve traffic safety for children in Ho Chi Minh City and other cities in Vietnam.

English

The primary objective of this article is to investigate how survival modelling can be used in traffic accident analysis to explain driver accident risk factors. Accident records of 398 drivers from 2007 to 2009 were obtained from Motor Traffic and Transport Department (MTTD), Ghana Police Service, Northern region. Cox proportional regression model was employed for the analysis using the SAS package. The conclusion was that Survival modelling promises to be a useful tool for road safety analysis and the most significant variables to the risks of accident were driver characteristics (age, gender, experience), their behaviour in traffic (speed, use of alcohol, use of safety belt), the nature of exposure (annual kilometreage, road surface condition) and vehicle characteristics (vehicle age, weight, tyres condition). Implementation of the findings of this study will enable policy makers put up better measures to reduce accident occurrence in the region in particular and the country as a whole.   Key words: Cox proportional model, accident risks, annual vehicle kilometreage, survival modelling, SAS package.

Analysis of Roadway Traffic Accidents Based on Rough Sets and Bayesian Networks

The paper integrates Rough Sets (RS) and Bayesian Networks (BN) for roadway traffic accident analysis. RS reduction of attributes is first employed to generate the key set of attributes affecting accident outcomes, which are then fed into a BN structure as nodes for BN construction and accident outcome classification. Such RS-based BN framework combines the advantages of RS in knowledge reduction capability and BN in describing interrelationships among different attributes. The framework is demonstrated using the 100-car naturalistic driving data from Virginia Tech Transportation Institute to predict accident type. Comparative evaluation with the baseline BNs shows the RS-based BNs generally have a higher prediction accuracy and lower network complexity while with comparable prediction coverage and receiver operating characteristic curve area, proving that the proposed RS-based BN overall outperforms the BNs with/without traditional feature selection approaches. The proposed RS-based BN indicates the most significant attributes that affect accident types include pre-crash manoeuvre, driver’s attention from forward roadway to centre mirror, number of secondary tasks undertaken, traffic density, and relation to junction, most of which feature pre-crash driver states and driver behaviours that have not been extensively researched in literature, and could give further insight into the nature of traffic accidents.

New systems-based method to conduct analysis of road traffic accidents

Road safety has become a major public issue in China. This study collected a total of 396 road traffic accident cases that occurred in 28 provinces from 1985 to 2014 in China. The type of vehicles involved in the accidents includes cargo vehicles (126), passenger vehicles (253), dangerous chemicals transport vehicles (128), and cars (9). A new systems approach that integrates the causal categories framework based on the human factor analysis and classification system (HFACS) and the contributory factor interactions model (CFIM) was applied to conduct analysis of road traffic accidents to determine whether systems approaches should be used during road accident analysis efforts. The analysis of results leads to the following conclusions. (i) According to the causal categories framework based on HFACS, the frequency of “unsafe behaviours” is highest at the category level; the frequency of “violations” is the highest at the subcategory level. “Overloading/overcrowding,” “speeding,” “failed to provide supervision,” and “fatigue driving” should receive attention at the special indicator level. (ii) The new systems-based method that integrated the HFACS and the CFIM, which highlights the interactions between all levels of the causal categories, is a suitable method to analyse road traffic accidents. (iii) All latent categories, including “outside factors,” “organizational influences,” “unsafe supervision,” and “preconditions for unsafe behaviours,” can affect “unsafe behaviours”; “outside factors,” “organizational influences,” “unsafe supervision,” and “preconditions for unsafe behaviours” can influence each other. These interactions have not been quantitatively examined in previous studies. The findings of this study also demonstrate that the OR is a suitable technique to quantitatively examine the interactions among contributory factors.

Fatalitas dan analisis apasial lokasi rawan kcelakaan lalu lintas di kabupaten Gunungkidul

Fatality and spatial analysis of road traffic accident in Gunung KidulPurposeThis study is aimed to conduct further analysis of road accidents fatality and accident-potential area using geographic information system.MethodsThis was an analytic observational study using cross-sectional study design. Samples are all traffic accident recorded in police departement accident registry from January 1st to December 31st 2015. Data will be analyzed using poisson regression with robust variance and accident location will be analyzed spatially using ArcGIS 10.4 software.ResultsThe result revealed that 06.00-11.59 a.m (PR 0.31, 95% CI 0.144-0.687) or 12.00-17.59 p.m (PR 0.40; 95% CI 0.184-0.865), uphill roadway geometric (PR 2.16, 95% CI 1.144-4.094) or winding roadway (PR 1.80, 95% CI 1.013-3.213) and single accident type (PR 3.59; 95% CI 1.953-6.592) were significant factors affecting road traffic fatalities. Accident-prone locations to traffic accidents in Gunungkidul are clustered on several streets, such as Yogyakarta-Wonosari Street, Karangmojo-Semin Road, Wonosari Semanu Street and Wonosari Baron Street..ConclusionsFatal traffic accident in Gunungkidul are influenced by environmental conditions and accident types. Multisectoral coordination was needed to improve intervention to population at risk and stakeholders need to make efforts to modify the environment related to road geometric conditions to minimize the occurrence of accidents.

Development of the technical vision algorithm

The purpose of the work is creation of a set of technical means (switches, sensors) for recognition of transport infrastructure facilities, including development of algorithms for autonomous operation of technical facilities under changing environmental factors. In this work, we used methods for determining the volume of a three-dimensional facilities from the data of photo and video recording of the surrounding situation. The algorithm of technical vision was obtained, which is implemented as a program on a mobile device for recognition by means of stereometry of transport infrastructure facilities and their defects and storage of transport infrastructure defects. The novelty of the research is building of decision algorithms based on devices and sensors that recognize changing road conditions, namely, defects in coverage. The data obtained can be used in the planning of road repairs, in the analysis of traffic accidents by road police, road users for processing complaints, etc.

Otvoreni podaci i baze podataka u analizi saobraćajnih nezgoda u gradu Beogradu

Otvoreni podaci i baze podataka u analizi saobraćajnih nezgoda u gradu Beogradu