• Korean Journal of Construction Engineering and Management
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• v.21 no.1
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• pp.87-98
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• 2020

As the construction industry accounts for 28.5% of industrial accidents in Korea and 29.6% of industrial accident deaths in 2017, it is necessary to search for a priority disaster reduction scheme for the construction industry in order to reduce the industrial accident rate. Therefore, this research suggested improvement direction for construction accidents reduction based on factors affecting construction accidents occurring in the construction site by DEMATEL analysis. As a result of the analysis, the 4M factors with the highest Prominence and Relation is 'Management', and the detailed analysis of the 4M factors were Personal characteristics of workers, Defects such as machinery and equipment, Inadequate inspection of machinery and equipment, Insufficient safety management plan, Inappropriate work orders from supervisors and field managers. The analysis results of this research can be used as a basic data for establishing direction of reduction and improvement of construction accidents.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.10-19
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• 1996

In order to build a model to predict accidents in a complicated man-machine sytem, human errors and mechanical reliability can be viewed as the most important factors. Such factors are explicitly included in a generic model. Another point to keep in mind is that the model should be constructed so that the data in a type of accident can be utilized to predict other types of accidents. Based on such a generic prediction model, we analyze the effects of system reliability. When we improve the system reliability, in other words, when there are changes in model parameters, the predicted time to next accidents should be modified influencing the effects of system reliability improvements. We apply Bayesian approach and finds the formula to explain how a change on the machine reliability or human error probability influences the time to next accident.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.157-165
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• 2011

With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of Korean society of Dental Hygiene
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• v.14 no.5
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• pp.757-764
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• 2014

Objectives : The purpose of this study was to investigate the oral health impact profile (OHIP) in the industrial accident injury patients, and the effect of subjective perception and attitude of oral health on the oral health-related quality of life in industrial injury patients. Methods : A self-reported questionnaire was filled out by 496 industrial accident injury patients from October 29 to November 30, 2013. Data were analyzed using SPSS ver 20.0 program for chi-square test, t-test, ANOVA, Scheffe test, and Pearson's correlation coefficient. Results : The OHIP-14 was higher oral health-related quality of life in young people, women, highly educated persons, and those having high income and frequent scaling service. The subjective perception and attitude of oral health was closely correlated to the OHIP-14. The factors influencing on the oral health-related quality of life were the subjective perception and attitude toward oral health. Conclusions : It is necessary to emphasize the oral health promotion program for industrial injury patients. The government should pay more attention to the policy for the improvement of the oral health of industrial accident injury patients in the future.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.1-7
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• 2009

Traffic accident by aging drivers is expected to be on the rise rapidly as the number of aging drivers is rising along with the aging trend being progressed. In this study, traffic accident features depending on the classification of aging population and non aging one was evaluated. As a result of this evaluation, effect factors influencing over the aging population was found to be expressed differently from that of the non aging one. Odds ratio between the aging population and non aging one was evaluated through logit model and a model with potential accident probability of the aged drivers was developed. Accident risk of the aged drivers under the condition of curved road, cutting section and moistured road was revealed to be higher than that of the non aging population.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2859-2864
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• 2013

Recently, a great attention has been paid to a car black box device in the automobile markets besides it provides an accident re-construction based on the data which contains audio, video, and some meaningful driving information. Also, it is expected that the device will get to promote around public transit and the market will greatly grow within a few years. Thus, this research conducted of preference the influencing factors in decisions purchase of auto black box. Factors influencing in decisions purchase of black box were divided safety, functionality, differentiation, economics. A questionnaire survey was conducted to those who worked in a black box company. This study suggests practical and theoretical implications of factors influencing purchase decisions based on the results.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.116-129
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• 2020

Resilience is defined as the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations or functions with the related systems under both expected and unexpected conditions. Resilience engineering is a relatively new paradigm for safety management that focuses on how to cope with complexity under pressure or disturbance to achieve successful functioning. This study aims to develop a quantitative resilience model for severe accident response organizations of nuclear power plants using the Analytic Hierarchy Process (AHP) method. First, we investigated severe accident response organizations based on a radiation emergency plan in the Korean case and developed a qualitative resilience model for the organizations with resilience-influencing factors, which have been identified in the author's previous studies. Then, a quantitative model for entire severe accident response organizations was developed by using the Analytic Hierarchy Process (AHP) method with a tool for System Dynamics. For applying the AHP method, several experts who are working on implementing, regulating or researching the severe accident response participated in collecting their expertise on the relative importance between all the possible relations in the model. Finally, a sensitivity analysis was carried out to discuss which factors have the most influenceable on resilience.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.13-22
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• 2018

Buses, one of the representative public transportation modes, are divided into a vareity of service types according to the purpose of operation, operating distance, and management agencies. Although bus-involved crashes may cause large amount of damage due to the higher number of passengers boarded on a bus, prior research has little focused on crash severity according to bus service types. This study aims to investigate factors influencing crash severity in bus-involved crashes and to present policy implications to reduce crash severity by bus service type. To do this, bus-involved crash data from the Traffic Accident Analysis System (TAAS) during five-year period are used. Ordered probit models for three types of bus service, i.e., city bus, suburban and express buses, and charter buses, are estimated to analyze the factors of accident severity. The results show that there are significant differences of factors affecting crash severity among the types of bus services while speed and road surface influence all the types of buses. In case of local buses, time of day, roadway alignment, and installation of a traffic signal are found to be statistically significant factors. Seat belt and road class have significant effects on injury severity of the intercity and express buses. Chartered buses have time of day, driving experience, seatbelt, traffic signal, and day of week as the significant factors. The results of this study are expected to contribute to the reduction of the crash severity by each bus service type.

• The Korean Journal of Health Service Management
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• v.13 no.3
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• pp.13-26
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• 2019

Objectives: To investigate whether medical institutions can prevent accidents by analyzing the root cause of a medical accident and identifying the tendencies. Methods: A total of 345 medical cases were used for the RCA(Root Cause Analysis). The root causes were classified using the SHELL model. The suitability of the model was confirmed by SPSS's MDPREF and Euclidean distance. An SPSS20.0 hierarchical regression analysis was used as an influencing factor on the degree of injury resulting from medical accidents. Results: The SHELL model was suitable for classification. The rates of accident causes were LS49%, L34%, LL10.2%, LE3.7%, LH2.3%. The order in which the degree of a patient's injury was affected were: Risk Threshold (${\beta}=.180$), Time (${\beta}=.175$), Surgical stage (${\beta}=-.166$), Do not use procedure (${\beta}=.147$). Conclusions: Health care institutions should remove priorities through system improvement and training. For patients' safety, the five factors of the SHELL model should be managed in harmony.