• 대한인간공학회지
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• 제29권2호
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• pp.241-248
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• 2010

In accident analysis, it is essential to understand the causal pathways of the accident. Although numerous accident models have been developed to help analysts understand how and why an accident occurs, most of them do not include all elements related to the accident in various fields. Thus analysis of human error accidents in railway operations using these existing models may be possible, but inevitably incomplete. For a more thorough analysis of the accidents in railway operations, a more exhaustive model of accident causation is needed. This paper briefly reviews four recent accident causation models, and proposes a new model that overcomes the limitations of the existing models for the analysis of human error accidents in railway operations. In addition, the usefulness and comprehensiveness of the proposed model is briefly tested by explaining 12 railway accident cases with the model. The proposed accident causation model is expected to improve understanding of how and why an accident/incident occurs, and help prevent analysts from missing any important aspect of human error accidents in railway operations

• 한국안전학회지
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• 제32권5호
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• pp.179-185
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• 2017

Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.

• 한국재난정보학회 논문집
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• 제13권4호
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• pp.570-576
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• 2017

고속도로에서 화물차는 승용차에 비해 도로의 많은 부분을 점유한다. 이로 인해 도로의 용량은 상대적으로 감소하며, 국소적으로 주변 운전자에게 위협적인 요소로 작용한다. 화물차 사고는 일반적인 사고와 달리 사고 특성이 다르므로 분석 방법 또한 일반적인 사고와 다르게 적용해야 한다. 사고 분석 방법 중 사고예측모형은 특정 구간에 대한 사고건수를 예측하며 교통계획을 수립할 때 사고 예방을 위한 대책 수립과 도로의 위험성을 진단할 때 활용된다. 이에 본 연구는 고속도로의 화물차 간 사고 비율을 적용하여 사고예측모형에 투입될 수 있는 보정계수를 산출하는 것을 목적으로 한다. 연구를 위해 고속도로를 대상으로 사고 자료를 수집하였으며 2014~2016년까지 3개 년도의 교통량 및 사고 자료를 활용하였다. 연간 사고건수를 토대로 사고예측모형을 개발하였으며, 본 연구를 통해 화물차 간 사고 비율에 따른 사고예측모형을 비교함으로써 실질적인 고속도로 사고예측모형을 확인하고 그에 대한 대책을 제시하고자 한다.

• 한국안전학회지
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• 제29권5호
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.

• Journal of Advanced Marine Engineering and Technology
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• 제40권8호
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• pp.721-725
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• 2016

This paper reviews the analysis of a given scenario according to the Hybrid Model, and why accident causation models are necessary in casualty investigations. The given scenario has been analyzed according to the Hybrid Model using its main five components, fallible decisions, line management, psychological precursors to unsafe acts, unsafe acts, and inadequate defenses. In addition, the differences between the SHEL and the Hybrid Model, and the importance of a safety barrier during an accident investigation, are shown in this paper. One unit of SHEL can be linked with another unit of SHEL. However, it cannot be used for the analysis of an accident. Therefore, we must use an accident causation model, which can be a Hybrid Model. This can explain the "How" and "Why" of accident, so it is a suitable model for analyzing them. During an accident investigation, the reason we focus on a safety barrier is to create another safety barrier or to change an existing safety barrier if that barrier fails. Hence, the paper shows how a sea accident can be investigated, and we propose a preventive way of avoiding the accident through combining the methods of different models for the future.

• 산업경영시스템학회지
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• 제40권1호
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• pp.87-94
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• 2017

Many industrial accidents have occurred continuously in the manufacturing industries, construction industries, and service industries of Korea. Fatal accidents have occurred most frequently in the construction industries of Korea. Especially, the trend analysis of the accident rate and fatal accident rate is very important in order to prevent industrial accidents in the construction industries systematically. This paper considers forecasting of the accident rate and fatal accident rate with static and dynamic time series analysis methods in the construction industries. Therefore, this paper describes the optimal accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM), and kalman filtering model (KFM) with existing accident data in construction industries. In this paper, microsoft foundation class (MFC) soft of Visual Studio 2008 was used to predict the accident rate and fatal accident rate. Zero Accident Program developed in this paper is defined as the predicted accident rate and fatal accident rate, the zero accident target time, and the zero accident time based on the achievement probability calculated rationally and practically. The minimum value for minimizing SSE in the construction industries was found in 0.1666 and 1.4579 in the accident rate and fatal accident rate, respectively. Accordingly, RAM and ARIMA model are ideally applied in the accident rate and fatal accident rate, respectively. Finally, the trend analysis of this paper provides decisive information in order to prevent industrial accidents in construction industries very systematically.

• 한국안전학회지
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• 제25권4호
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• pp.90-95
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• 2010

This study deals with the accident model of arterial link section in Cheongju. The objective is to develop the accident model of arterial link section using the logistic regression. In pursuing the above, the study uses the 258 accident data occurred at the 322 arterial link section. The main results are as follows. First, Nagellerke $R^2$ of developed accident model is analyzed to be 0.309 and t-values of variable that explains goodness of fit are evaluated to be significant. Second, the variables adopted in the model are AADT, the number of exit and entry. These variables are all analyzed to be statistically significant. Finally, the analysis of correct classification rate shows that the total accident of correct classification rate is analyzed to be 72.7% at the arterial link section.

• 자동차안전학회지
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• 제13권3호
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• pp.69-77
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• 2021

Although accident data from the National Police Agency and insurance companies do not know the vehicle safety, the damage level information can be obtained from the data managed by the bus credit association or the bus company itself. So the accident severity was analyzed based on the side impact accidents using accident repair cost. K-means clustering analysis separated the cost of accident repair into 'minor', 'moderate', 'severe', and 'very severe'. In addition, the side impact accident severity was analyzed by using an ordered logit model. As a result, it is appeared that the longer the repair period, the greater the impact on the severity of the side impact accident. Also, it is appeared that the higher the number of collision points, the greater the impact on the severity of the side impact accident. In addition, oblique collisions of the angle of impact were derived to affect the severity of the accident less than right angle collisions. Finally, the absence of opponent vehicle and large commercial vehicles involved accidents were shown to have less impact on the side impact accident severity than passenger cars.

• 대한안전경영과학회지
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• 제8권2호
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• pp.13-23
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• 2006

The present study has investigated the patterns and the causes of safety -accidents on the accident-data in semiconductor Industries through near miss report the cases in the advanced companies. The ratio of incomplete actions to incomplete state was 4 to 6 as the cases of accidents in semiconductor industries in the respect of Human-ware, Hard- ware, Environment-ware and System-ware. The ratio of Human to machine in the attributes of semiconductor accident was 4 to 1. The study also investigated correlation among the system related to production, accident, losses and time. In semiconductor industry, we found that pattern of safety-accident analysis is organized potential, interaction, complexity, medium. Therefore, this study find out that semiconductor model consists of organization, individual, task, machine, environment and system.

• 한국도로학회논문집
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• 제16권3호
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• pp.101-107
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• 2014

PURPOSES : This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS : To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS : The optimal model for pedestrian accidents is evaluated to be Tobit model.