scholarly journals Critical Factors Analysis of Severe Traffic Accidents Based on Bayesian Network in China

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hong Chen ◽  
Yang Zhao ◽  
Xiaotong Ma
Keyword(s):  
Bayesian Network ◽  
Traffic Accidents ◽  
Critical Factors ◽  
Factors Analysis ◽  
Target Network ◽  
Accident Data ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Single Vehicle ◽  
Factor Combination

The purpose of this study is to minimize the negative influences of the severe traffic accidents in China by profoundly analyzing the complex coupling relations among accident factors contributing to the single-vehicle and multivehicle traffic accidents with the Bayesian network (BN) crash severity model. The BN model was established by taking the critical factors identified with the improved grey correlation analysis method as node variables. The severe traffic accident data collected from accident reports published in China were used to validate this model. The model’s efficiency was validated objectively by comparing the conditional probability obtained by this model with the actual value. The result shows that the BN model can reflect the real relations among factors and can be seen as the target network for the severe traffic accidents in China. Besides, based on BN’s junction tree engine, five-factor combination sequences for the number of deaths and three-factor combination sequences for the number of injuries were ranked according to the severity degree to reveal the critical reasons and reduce the massive traffic accidents damage.

Human Factors Analysis and Model of Accidents due to Driver Errors

2013 ◽  
Vol 438-439 ◽  
pp. 1944-1947 ◽  
Author(s):  
Wan Wan Lu ◽  
Xiu Shan Jiang ◽  
Jian Bin Bi
Keyword(s):  
Human Factors ◽  
Traffic Accidents ◽  
Analysis Method ◽  
Related Data ◽  
Index Model ◽  
Factors Analysis ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Driver Error ◽  
Human Factors Analysis

On the basis of human factors analysis of driver error accidents, this paper establishes the accident-causing index system due to driver errors and puts forward the use of trapezoidal fuzzy hierarchy - the grey correlation analysis method to analyze the accident-causing index model due to driver errors. Then this paper uses related data and proposed analysis method to obtain the weights order of accident-causing factors. The results reveal the main cause of accidents due to driver errors, and provide the reference for further research to prevent the traffic accidents.

scholarly journals Analysis of Road Accidents in Baghdad City

2019 ◽  
Vol 26 (1) ◽  
pp. 136-144
Author(s):  
Hasan H. Joni ◽  
Ali Majeed Al-Dahawi ◽  
Omar Jabbar Al-Tamimi
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Global Public Health ◽  
Road Accidents ◽  
Vehicle Accidents ◽  
Predominant Type ◽  
Accident Data ◽  
Single Vehicle ◽  
Health And Development ◽  
Major Factors

Road traffic accidents (RTAs) have turned out to be a huge global public health and development problem causing enormous economic and social costs. Therefore RTA has become a major concern and analyzing accident data has been an important look out to the analysts in order to find the major factors related to the accidents, and to predict the future road accidents in order to mitigate and/or eliminate them in the future.The study revealed that the main contributing factor is the human. The predominant type of crashes was run over with 53% of the total crashes.Approximately, 53% of crashes occurred on major roads, 58% of crashed occurred during day time, drivers with group ages between 24 – 29 years’ experience more crashes, and single vehicle accidents result in more casualty (fatality and injuries) compared to multi-vehicleaccidents. The most important resultobtainedfrom this study, a prediction model which link accidents with the number of registered vehicles and population.

Application of Gray Correlation Method Fracturing Effect Main Controlling Factors Analysis in JI006 Block

2015 ◽  
Vol 1092-1093 ◽  
pp. 1351-1355
Author(s):  
Jiao Jiao Guo ◽  
Wei Dong Liu ◽  
Jin Jun Liu ◽  
Jun Hua Ye ◽  
Xiao Chuan Tang ◽  
...  
Keyword(s):  
Pressure Effect ◽  
Influence Factors ◽  
Correlation Method ◽  
Analysis Method ◽  
Effect Analysis ◽  
Factors Analysis ◽  
Gray Correlation ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Influence Degree

JI006 block is a key blocks of improve productivity in the JI7 well area. This blocks development of well after fracturing,the fracturing effect are different. To further improve the block after the fracturing effect,should focus on the analysis of influence factors of productivity after fracturing. But have different influence factors and influence degree. In order to analyze the influence of various factors on the Fracturing effect influence degree. This paper uses the grey correlation analysis method to the JI 006 block 15 fracturing Wells formation parameters and fracturing parameters influence after the pressure effect is analyzed,To determine the factors influencing the Fracturing effect. Analysis results is more accurate, the method to choose well layer and the fracturing design and construction has certain guiding significance.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

Research on Combat Effectiveness Evaluation of Radar EW System Based on Bayesian Network

2011 ◽  
Vol 204-210 ◽  
pp. 1697-1700 ◽  
Author(s):  
Yu Jie Zheng
Keyword(s):  
Bayesian Network ◽  
Evaluation Model ◽  
Effectiveness Evaluation ◽  
Analysis Model ◽  
Key Factors ◽  
Bayesian Network Model ◽  
Simulation Data ◽  
Factors Analysis ◽  
Combat Effectiveness ◽  
Hidden Knowledge

Radar EW system combat effectiveness evaluation is a essential link to Radar system Demonstration, mainly give service to selection, optimization and key factors analysis of Weapon equipment scheme. In this paper, we introduce the Bayesian network model into the area of Radar EW system combat effectiveness evaluation and put forward the concept of combat effectiveness evaluation model based on Bayesian network. The ability to express complex relationship, the ability to express the uncertainty of probability, and the reasoning functions. By learning from Expertise and Simulation data, excavating the hidden knowledge included in both of them, we can build the combat efficiency Analysis model, and then carry out efficient analysis.

A causal factors analysis of helicopter accidents in New Zealand 1996-2005 and the United Kingdom 1986-2005

2009 ◽  
Vol 113 (1148) ◽  
pp. 647-660 ◽  
Author(s):  
A. Majumdar ◽  
K. Mak ◽  
C. Lettington ◽  
P. Nalder
Keyword(s):  
United Kingdom ◽  
New Zealand ◽  
Civil Aviation ◽  
Logical Scheme ◽  
The United Kingdom ◽  
Factors Analysis ◽  
Accident Data ◽  
Operational Failures ◽  
Attention Failure ◽  
Operational Failure

Abstract Helicopter accidents cause many fatalities, and their avoidance is a major area of work for Civil Aviation safety authorities around the World. This paper uses helicopter accident data from the United Kingdom between 1986 and 2005 for 566 accidents and from New Zealand between 1996 and 2006 for 230 accidents to analyse helicopter accidents according to five categories of causes: airworthiness failure (engine); airworthiness failure (non-engine), operational failure, maintenance failure and mixed failure (i.e. operational and airworthiness combined). Factors associated with accidents, e.g. the engine types and weights of the helicopters involved; the nature of the operations and the phase of flight of the helicopter are also analysed. Operational failures were further analysed by Human Factors Analysis and Classification Scheme (HFACS) and airworthiness failures by a logical scheme of helicopter components. The results indicate that operational failures, especially due to unsafe acts, are the major cause of accidents in both countries followed by airworthiness causes. Light single piston helicopters are by far the major group associated with accidents in both countries, with few accidents for twin turbine helicopters. The majority of accidents were in non-public operations with few in public operations and in both countries, the cruise/flight/circuit phase has the largest number of accidents. Further analyses indicated statistically significant associations: type of helicopter and the cause of accidents; type of helicopter and the phase of flight; cause of accidents and nature of flights; cause of accidents and phase of flights; training flights and inadequate supervision; landing and procedural error and cruise and attention failure.

scholarly journals Statistical Analysis of Traffic Accidents in Shanghai River Crossing Tunnels and Safety Countermeasures

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Linjun Lu ◽  
Jian Lu ◽  
Yingying Xing ◽  
Chen Wang ◽  
Fuquan Pan
Keyword(s):  
Statistical Analysis ◽  
Traffic Accidents ◽  
Temporal And Spatial Distribution ◽  
Urban Road ◽  
Spatial Distribution Characteristics ◽  
Road Tunnels ◽  
Accident Data ◽  
Tunnel Safety ◽  
Temporal And Spatial ◽  
Safety Countermeasures

A large number of traffic tunnel accidents have been reported in China since the 21th century. However, few studies have been reported to analyze traffic accidents that have occurred in urban road tunnels. This study aims to examine the characteristics of the temporal, spatial, and modality distributions of traffic in Shanghai river crossing tunnels using statistical analysis and comparative analysis. Employing these techniques tunnel accident data obtained from Shanghai center 110 was analyzed to determine temporal and spatial distribution characteristics of traffic accidents in river crossing tunnels in Shanghai. The results of this analysis are discussed and summarized in this paper. Identification of the characteristics of tunnel traffic accidents can provide valuable information for development of effective countermeasures to improve tunnel safety in China.

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 ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum
Keyword(s):  
School Environment ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
School Administrators ◽  
Road User ◽  
The Road ◽  
Road Users ◽  
Accident Data

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.

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