This study aimed to analyze the economic feasibility of the reduction of working safety accidents in stow net fishery through the prevention education to fishing crews. The benefit was evaluated by estimating insurance payment amount that was reduced through prevention education. The decreasing rate of working safety accidents was presumed to follow the experience in Japan. The cost was assumed as the cost of textbook development. Results indicated that IRR was estimated to be 79.9% in case of scenario assuming no additional operating costs while IRR was 56.3% in case of scenario assuming 10% additional operating costs. In addition, the economic feasibility would be secured when annual operating costs increased to 274 million won according to the result of sensitivity analysis.

PURPOSES : In this study, the installation of drowsy rest areas and accidents are analyzed. The factors that affected the accidents caused by drowsy drivers in rest areas are analyzed to improve the safety of rest areas. METHODS : By comparing and analyzing the installation status of the rest areas for drowsy drivers, the accident status were analyzed. The logistic regression model was used to analyze the factors that affect accidents in the drowsy rest area. RESULTS : Most rest areas were installed below the installation criteria. Several accidents occurred when the vehicle entered the drowsy rest area. These rest areas had a short entry ramp, and no safety facilities were installed. The logistic regression model showed that the risk of an accident is lowered when the deceleration lane is longer than 215 m. Additionally, the risk of an accident is lowered when the rest area is installed in the straight section or the curve section, wherein the curve radius is greater than 2 km. CONCLUSIONS : In this study, we evaluated the installation status of the rest areas for drowsy drivers by comparing installation elements. Most rest areas for drowsy drivers were installed at different lengths of the ramp. Some of these were installed on the slope or curved sections of the road. We analyzed the accident status and developed an accident modal using the logistic regression model to identify the factors that affect accidents. It will be necessary to analyze accidents in drowsy rest areas continuously to improve safety for drowsy drivers.

PURPOSES : This study was purposed to identify the relationships between route characteristics and accident characteristics using the data of 124 routes collected from 78 of the 136 Seoul Neighborhood bus companies. METHODS : A structural equation modeling technique was employed for the analysis. The following four factors that were determined to influence the characteristics of Neighborhood bus accidents were implemented: driver characteristics, route characteristics, driver working conditions, and the management conditions of each company. Additionally, the two dependent variables were set as vehicle to vehicle accidents and vehicle to pedestrian accidents. RESULTS : The results of factor analysis revealed that the management conditions of each company had a negative effect on the working conditions, and that driver characteristics had a negative influence on accident characteristics in the three models. The effects of three major factors such as route characteristics, management conditions of the company, and working conditions on vehicle-to-vehicle accidents were likely to be opposite to the influences on vehicle-to-pedestrian accidents. CONCLUSIONS : Through the analysis of these results, we identified the characteristic causes of Neighborhood bus accidents. Specifically, a driver with more experience is less likely to be involved in a Neighborhood bus accident, and a narrower road is associated with higher accident risk. These results can be used as a reference to improve route and safety management for Neighborhood buses. Furthermore, this study is expected to contribute to the establishment of improved strategies to effectively reduce the number of Neighborhood bus accidents.

There has been a significant decline in the number of rail accidents in Korea since system safety management activities were introduced. Nonetheless, analyzing and preventing human error-related accidents is still an important issue in railway industry. As a railway system is increasingly automated and intelligent, the mechanism and process of an accident occurrence are more and more complicated. It is now essential to consider a variety of factors and their intricate interactions in the analysis of rail accidents. However, it has proved that traditional accident models and methods based on a linear cause-effect relationship are inadequate to analyze and to assess accidents in complex systems such as railway systems. In order to supplement the limitations of traditional safety methods, recently some systemic safety models and methods have been developed. Of those, FRAM(Functional Resonance Analysis Method) has been recognized as one of the most useful methods for analyzing accidents in complex systems. It reflects the concepts of performance adjustment and performance variability in a system, which are fundamental to understanding the processes of an accident in complex systems. This study aims to apply FRAM to the analysis of a rail accident involving human errors, which occurred recently in South Korea. Through the application of FRAM, we found that it can be a useful alternative to traditional methods in the analysis and assessment of accidents in complex systems. In addition, it was also found that FRAM can help analysts understand the interactions between functional elements of a system in a systematic manner.

Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.

이 연구의 목적은 중학생을 위한 시스템 사고 향상에 적합한 사전 교육 및 STEAM 교육 프로그램을 개발하고 중학생에게 적용하여 프로그램의 효과를 분석하는 것이다. 이 연구는 중학생을 대상으로 시스템 사고에 대한 사전 교육 프로그램과 시스템 사고를 향상시키기 위한 STEAM 교육 프로그램을 개발하는 것이다. 개발된 프로그램은 경상북도에 위치한 소규모 중학교 1학년 4명, 3학년 4명을 대상으로 투입하여 효과를 분석하였다. 시스템 사고의 분석은 Hung(2008)에 의해 개발된 루브릭이 활용되었다. 학생들의 시스템 사고에 대한 신뢰도와 루브릭의 타당도를 확인하기 위해 전문가들이 연구 결과를 검토하였다. 시스템 사고의 효과를 확인하기 위해 루브릭, 시스템 사고에 대한 학생들의 인지, 단어 간 관계 분석, 인과 지도의 검사를 체계적으로 적용하였다. 연구 결과를 정리하면 다음과 같다. 첫째, 시스템 사고 사전 교육 프로그램과 교사용 지도서를 개발하였다. 이는 학생의 시스템 사고에 대한 개념과 인과 지도 작성법에 대한 기초 지식을 학습시키기 위한 것이다. 개발된 사전 교육 프로그램은 ‘지구 온난화’를 주제로 한 무한도전이라는 친숙한 예능 프로그램을 이용하여 인과 지도 작성 방법을 학습하도록 구성되었다. 사전 교육프로그램은 대상 학생들이 친숙하게 접근할 수 있도록 지구 온난화를 주제로 한 예능 프로그램을 기반으로 하였으며, 이를 통해 인과 지도 작성 방법을 학습할 수 있도록 구성하였다. 효과성 검사를 적용한 결과, 학생들의 시스템 사고 향상을 위한 사전 교육 프로그램은 효과적인 것으로 분석되었다. 둘째, ‘분석-설계-제작-평가-시스템 사고’의 5단계로 구성된 ADBAS 모형을 적용하여 ‘공기 소화기’ 주제의 시스템 사고 기반 STEAM 교육 프로그램을 개발하였다. 개발된 프로그램은 시스템의 이해 능력, 시스템 내 관계 파악 능력, 시스템 일반화 능력에 긍정적인 효과가 있는 것으로 나타났다. 이 연구를 통해 개발된 사전교육 프로그램 및 STEAM 교육 프로그램은 학생의 시스템 사고 향상을 돕는데 적합하며, 시스템 사고와 STEAM 교육의 접목이라는 점에서 중요한 의미를 가진다. 또한 시스템 사고 향상을 위해 이 프로그램을 투입하기에 적절한 것으로 판단되어 ‘창의융합인재’를 양성하는데 기여할 것이다. 또한 시스템 사고 향상을 위한 위 프로그램의 적절한 투입은 창의융합형 인재를 양성하는 교육 목표를 달성하는 데 있어 기여를 할 것으로 판단된다.