• Journal of the Korean Society of Safety
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• v.32 no.4
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• pp.107-113
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• 2017

This paper deals with the traffic factors related to the collisions of circular intersections. The purpose of this study is to develop traffic accident models by type of collision based on land use. In pursuing the above, the traffic accident data from 2010 to 2014 were collected from the "Traffic Accident Analysis System (TAAS)" data set of the Road Traffic Authority. A multiple regression model was utilized in this study to develop the traffic accident models by type of collision. 17 explanatory variables such as geometry and traffic volume factors were used. The main results are as follows. First, the null hypothesis that the type of land use does not affect the number of accidents by type of collision is rejected. Second, 10 accident models by type of collision based on land use are developed, which are all statistically significant. Finally, the ADT, inscribed circle diameter, bicycle lane, area of central island, number of speed hump, circulatory roadway width, splitter island, area of circulatory roadway, mean number of entry lane and mean width of entry lane are analyzed to see how they affect accident by type of accident based on land use.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.31-39
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• 2008

Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. The accurate traffic accident prediction model requires not only understanding of the factors that cause the accident but also having the transferability of the model. So, this paper suggest the traffic accident diagram using CART(Classification And Regression Tree) analysis, developed Model is compared with the existing accident prediction models in order to test the goodness of fit. The results of this study are summarized below. First, traffic accident prediction model using CART analysis is developed. Second, distance(D), pedestrian shoulder(m) and traffic volume among the geometrical factors are the most influential to the traffic accident. Third. CART analysis model show high predictability in comparative analysis between models. This study suggest the basic ideas to evaluate the investment priority for the road design and improvement projects of the traffic accident blackspots.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.841-851
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• 2019

This study presents risk ranking by accident types at intersections, crosswalk and tunnel sections. An ordered logit model was used to estimate the accident severity of traffic accidents based on 58,868 accident records that have occurred on the Seoul and Gyeonggi-do over the period 2014-2017. The factors affecting the injury severity were identified by the estimated model first, and risk ranking was proposed according to conditions of accident occurrence using relative ratio analysis later. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. Furthermore, there are severe injury cases in terms of the injury severity despite the small number of occurrence of traffic accident, or there are severe injury cases in terms of the injury severity despite the high frequency of occurrence of traffic accident.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.50-59
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• 2021

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.73-91
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• 1998

The ratio of Industrial Accident in Korea has been inclined to decrease for recent ten years since industrialization beginnings of Korea. But it is still in high level viewed from international comparison. Up to now, we depended on classical method Accident as the phenomenical and inductive result. And we searched for the counter plan in the basis of the result by this method. But, in this research, we analyzed the distinctions which the structure of the occurrence of Industrial Accident using new model in order to approach the cause of Industrial accident of Korea more basically. In this new model, I am going to arrange the controllable variables in the factors of Industrial Accident and to analyze the effect of these controllable variables in the structure of Industrial Accident.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.142-143
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• 2023

A contact accident with gantry cranes involving the container ship MV Milano Bridge in Busan New Port took place on 6 April 2020. The report concluded that the pilot unreasonably piloted the ship with impaired maneuverability and without a proper pilotage plan. Analyzing the entire system by CAST model gives a holistic approach in linking all the key components and their roles as well as violations that led to the accident, stepping away from placing the blame on only one component in the system. Furthermore, analyzing the accident as an system theory gives a clear overview of the relationships between system components and how these interactions led to the accident.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2483-2491
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• 2013

In order to identify and understand the crucial factors to induce traffic accident, causal relationships between diverse factors and traffic accident occurrence have been investigated continuously. It is one of most important issues all over the world to reduce the number of traffic accidents and deaths by them. Korea government is also stepping up their effort to reduce the number of traffic accidents and mitigate the severity of the accidents by establishing various traffic safety strategies. By introducing the five-day work week and increasing concern of leisure activities, the differences of trip characteristics between weekday and weekend is getting greater. According to this, the patterns and crucial factors of traffic accident occurrence in weekend appear differently from those in weekday. This study aims to understand major different factors affecting accident severity between weekday and weekend using 12,042 incident data occurred on freeways of Korea from 2006 to 2011. The model developed in this study estimated relationships among various exogenous factors of traffic accident by each type using SEM(Structural Equation Model). The result provides that road factors are related to the accident severity for weekday model, while environment factors affects on accident severity for weekend.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.49-57
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• 2011

This study deals with the traffic accident of arterial link sections in the case of Cheongju. The purpose of the study is to develop the traffic accident model by the function of arterial links. In pursuing the above, this study gives particular attentions to developing the appropriate models using the accident data of main and minor arterial roads divided by 472 small link sections. The main results analyzed are as follows. First, as the t test on the accident characteristics of main and minor arterial roads shows that there are differences in the number of accident and EPDO(equivalent property damage only) between two roads, the development of models by function is analyzed to be appropriate. Second, it is analyzed that ZINB models are all statistically suitable to the number of accident and EPDO of main arterial roads. Third, the analysis shows that EPDOs of minor arterial roads fit to ZINB, and the number of the accident fit to ZIP model. Finally, the common variables of main arterial roads are evaluated to be the traffic volume and the number of inflection point, and those of minor be the average grade.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.482-490
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• 2017

This study is a railway accident investigation statistic study with the purpose of prediction and classification of accident severity. Linear regression models have some difficulties in classifying accident severity, but a logistic regression model can be used to overcome the weaknesses of linear regression models. The logistic regression model is applied to escalator (E/S) accidents in all stations on 5~8 lines of the Seoul Metro, using data mining techniques such as logistic regression analysis. The forecasting variables of E/S accidents in urban railway stations are considered, such as passenger age, drinking, overall situation, behavior, and handrail grip. In the overall accuracy analysis, the logistic regression accuracy is explained 76.7%. According to the results of this analysis, it has been confirmed that the accuracy and the level of significance of the logistic regression analysis make it a useful data mining technique to establish an accident severity prediction model for urban railway casualty accidents.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.137-150
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• 2011

Nationally and internationally reported statistics on marine accidents show that 80% or more of all marine accidents are caused fully or in part by human error. According to the statistics of marine accident causes from Korean Maritime Safety Tribunal(KMST), operating errors are implicated in 78.7% of all marine accidents that occurred from 2002 to 2006. In the case of the collision accidents, about 95% of all collision accidents are caused by operating errors, and those human error related collision accidents are mostly caused by failure of maintaining proper lookout and breach of the regulations for preventing collision. One way of reducing the probability of occurrence of the human error related marine accidents effectively is by investigating and understanding the role of the human elements in accident causation. In this paper, causal factors/root causes classification systems for marine accident investigation were reviewed and some typical human error analysis methods used in shipping industry were described in detail. This paper also proposed a human error analysis method that contains a cognitive process model, a human error analysis technique(Maritime HFACS) and a marine accident causal chains, and then its application to the actual marine accident was provided as a case study in order to demonstrate the framework of the method.