• Journal of the Ergonomics Society of Korea
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• v.35 no.3
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• pp.155-163
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• 2016

Objective: This study aims to draw the characteristics of occupational accidents occurred in cabling work, and assess accident severity based on occupational injury data. Background: Accident factors and accident risk are different by the place of work in cabling work. Field managers require information on accident prevention that can be easily understood by workers. However, there has been a lack of studies that focus on cabling work in Korea. Method: This study classifies 450 injured persons caused in cabling work by process, and analyzes the characteristics of occupational injuries from the aspects of age, work experience and accident type. This study also analyzes accident frequency and severity of injury. Results: Results show that preparing/finishing (33.3%) was the most common type of cabling process in injuries, followed by maintenance (28.4%), routing/income (23.1%) and wiring/installation (15.1%) process. The critical incidents in the level of risk management were falls from height in the routing/incoming process, and falls from height in the maintenance process. And, incidents ranked as 'High' level of risk management were slips and trips, fall from height and vehicle incident in the preparing/finishing process, and fall from height in the wiring/installation process. Conclusion and Application: The relative frequency of accident and its severity by working process serve as important information for accident prevention, and are critical for determining priorities in preventive measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• Journal of Korean Medicine Rehabilitation
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• v.24 no.1
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• pp.65-76
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• 2014

Objectives The purpose of this study is to investigate the corelation between traffic accident severity and treatment period and cost by traffic accident. Methods Outpatients who visited Jaseng Korean medicine hospital traffic accident clinic were investigated by hospital computer system about period and cost of treatment. And we requested for repair cost of car, a sort of car groups and agreement date with car insurance company to insurance company. Therefore we could analysis statistical correlation of traffic accident severity (repair cost of car) with period of treatment, cost of treatment, number of treatment in same sort of car groups. For statistics, we used SPSS version 18.0 for windows. Results A significant positive correlation was found between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment in semi-midsize car, midsize car group. But, any significant correlation wasn't found between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment in small car, full-sized car group. In SUV (sport utility vehicle) car group some significant correlation was found, but it isn't between traffic accident severity (repair cost of car) with repair cost of car, cost of treatment and number of treatment. Conclusions It was found that traffic accident severity (repair cost of car) had an effect on cost of car, cost of treatment and number of treatment by statistical analysis. But, it was also suggested strongly that other factors like a cost of car and ages had an effect on them.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.85-95
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• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.215-225
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• 1996

We studied the factors that would affect the severity of psychiatric symptoms of the Sampoong accident survivors. In this study, the analyzed factors are sex, age, marital status, educational level, loss of consciousness, witness of death, death of related person, duration until the rescue, duration of hospitalization, and psychiatric treatment after the accident. Although our study has some limitations, we found some factors that affect the severity of psychiatric symptoms after the severe traumatic accident.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.354-362
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• 2000

Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.111-117
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• 2017

The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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• pp.50-51
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• 2017

The safety accident of construction industries occur variously in other industries, including other industries, resulting in significant losses of human and material losses. In particular, General worker represents the highest safety accident rate each year, and the various types of accidents are the ones that show the greatest interest in the field, which is the most interesting job in the field. This study aims to identify trends in safety hazards and to analyze the accident severity for major types and influence factors.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• Journal of the Korean Society of Safety
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• v.26 no.2
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• pp.89-98
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• 2011

The traffic accidents at a construction site, which happen due to construction vehicles' frequent access to a construction site, its subsequent conflicts with ordinary vehicles and pedestrians, and inappropriate installation & management of traffic security facilities, have not many proportions in all traffic accidents, but obviously, the accident damage is quite serious when comparing the level of the fatal per one accident. This research conducted an analysis of traffic accident injury severity using Ordered Probit Model in relation to 241 traffic accident cases that occurred caused by construction sites among the traffic accidents that took place in Seoul and Gyeoggi-do region for two years from 2006 until 2007. As a result, the significant variables enough to explain traffic accident injury severity were analyzed to be the state of road surface, linear shape of an accident spot & whether the damaging car belongs to the vehicle for construction, and whether vehicles have access to a construction site at the time of an accident. Through this, this research found out some fact as follows: first, there need to be more aggressive management of the vehicles for construction and a year-round placement of the manpower who can control vehicular access to a construction site. Second, it is necessary to get drivers to recognize the fact that there exists a construction site on the construction section which is on the border of curved roads in advance to prevent a traffic accident, helping to reduce socioeconomic loss & costs incurred by a traffic accident.