PURPOSES : To prevent an increasing number of drowsiness-related accidents, considering driver fatigue is necessary, which is the main cause of drowsiness accidents. The purpose of this study is to propose a methodology for selecting drowsiness hotspots using continuous driving time, a variable that quantifies driver fatigue. METHODS : An analysis was conducted by dividing driver fatigue, which changes according to time and space, into temporal and spatiotemporal scenarios. The analysis technique derived four evaluation indicators (precision, recall, accuracy, and F1 score) using a random forest classification model that is effective for processing large amounts of data. RESULTS : Both the temporal and spatiotemporal scenarios performed better in models that reflected the characteristics of road sections with changes in time and space. Comparing the two scenarios, it was found that the spatiotemporal scenario showed a difference in precision of approximately 10% compared with the temporal scenarios. In addition, [Model 2-2] of the spatiotemporal scenario showed the best predictive power by assessing the model’s accuracy via a comparison of (1-recall) and precision. This shows better performance in predicting drowsy accidents by considering changes in time and space together rather than constructing only temporal changes. CONCLUSIONS : To classify hotspots of drowsiness, spatiotemporal factors must be considered. However, it is possible to develop a methodology with better performance if data on individuals driving vehicles can be collected.

The construction industry stands out for its higher incidence of accidents in comparison to other sectors. A causal analysis of the accidents is necessary for effective prevention. In this study, we propose a data-driven causal analysis to find significant factors of fatal construction accidents. We collected 14,318 cases of structured and text data of construction accidents from the Construction Safety Management Integrated Information (CSI). For the variables in the collected dataset, we first analyze their patterns and correlations with fatal construction accidents by statistical analysis. In addition, machine learning algorithms are employed to develop a classification model for fatal accidents. The integration of SHAP (SHapley Additive exPlanations) allows for the identification of root causes driving fatal incidents. As a result, the outcome reveals the significant factors and keywords wielding notable influence over fatal accidents within construction contexts.

PURPOSES : The primary objective of this study is to analyze the relationship between the factors that affect traffic incident duration in the mainline, tunnel, and ramp segments of an expressway. In addition, this study derived the most suitable statistical prediction model based on various incident duration distributions. METHODS : South Korean expressway crash data for 11 years, from 2011 to 2021, were analyzed. The incident durations on the mainline, tunnel, and ramp segments were selected using the accelerated failure time model, which is a parametric survival analysis approach. RESULTS : The mainline segment showed that the incident duration increased during accidents, including guard pipe collisions, multivehicle collisions, and snowfall. In particular, collisions in a tunnel with shoulder facilities increase the incident duration, while decreasing the time in the ramp segment. CONCLUSIONS : The incident duration model for each segment type yielded the most accurate results when applying a log-logistic distribution.

The preliminary study was conducted on the use of navigation instruments and programs conducted in the previous demonstration and experiment of the training ship SAEBADA, real-time sharing and accuracy of land and sea information, and the development of real-time effective information transmission and reception and management system programs. Based on this, this study used the training ship CHAMBADA, which is similar in length to the tonnage of the fishing boat. The purpose is to present errors in ship situation-specific information data, alarm systems for marine information, and land and ship transmission and reception programs collected using intelligent information management systems to find out whether they can be applied and used in fishing boats. It plans to conduct research on direct and indirect safety and ship’s stability when the intelligent information management system operates in real time in the operation of ships considering the characteristics of small fishing boats and the characteristics of fishing.

This study aims to understand the current status of exemptions for traffic accidents during the return of emergency vehicles and to provide suggestions for improvement. A survey was conducted on 3,500 firefighters to investigate the perception of traffic accidents during the return of emergency vehicles, and responses from 505 participants were analyzed. Based On the demographic characteristics and perception of the participants, frequency analysis and variance analysis were used as research methods to analyze basic statistics and the current situation. The results showed that firefighters have concerns and anxieties about traffic accidents during the return of emergency vehicles, and the need for applying exemptions and enacting explicit legal provisions was statistically confirmed. Based on these results, we suggest a policy for exemptions to improve the preparation for re-deployment and to alleviate the concerns and anxieties of firefighters.

This study would analyze a survey conducted with 609 workers to use the results as materials for the settlement of safety culture for the characteristics of the establishment by assessing the status of the workers’ exposure to harmful risks and the impact on safety culture to present the following conclusions. This study has significance in that it found that exposure to harmful/dangerous factors in the establishment and the workers’ experiences of occupational accidents affect their perception of safety culture and that in particular, ‘worker safety priority’ of the safety cultural factors was an important factor, and it is judged that continuous studies are necessary so that the perceptions of safety culture will spread in the establishment.

Ensuring the safe arrival of delivery cargo at its intended destination is of utmost importance. Truck drivers play a crucial role in guaranteeing the secure delivery of cargo without any mishaps. However, there are various factors that may lead to delayed arrival of trucks at their destination, such as late departures or prolonged loading operations. The timely departure of cargo transportation is contingent upon several variables, including the driver's experience, cargo volume, and loading time. If the transportation commencement is delayed, it may increase the risk of accidents due to an elevated operating speed. Consequently, we conducted a study to investigate the correlation between cargo loading time, cargo volume, driving experience, and the likelihood of accidents. Our findings indicate that both cargo volume and driver experience can impact the likelihood of vehicle accidents. Furthermore, all factors can have an interactive effect on the occurrence of accidents. However, extending the loading time may mitigate the impact on the likelihood of accidents.

The delivery truck is traveled around the delivery area for a long time. Truck drivers cause traffic accidents because of long hours of driving, fatigue, and speeding, etc. In this study, we will test the factors for preventing accidents of drivers. We would like to find factors that affect accidents and improve that can prevent accidents. As in the results of the study, accidents occur when traffic increases and profits increase among driver age, career, and profit factors. In addition, if the volume of traffic increases during the season, the number of accidents increases further. Therefore, in order to prevent truck accidents, a stable cargo quantity must be allocated to truck and cargo must be delivered.

Recently, the crisis of demographic extinction is rising in Korea more than any other country, and it is difficult for industrial sites to maintain without 'foreign workers'. Industrial accidents and accident deaths of foreign workers account for 7.6% and 12.3% of the total, through an in-depth analysis of fatal accidents in the manufacturing industry, differences and similarities between fatal accidents of foreign workers and all fatal accidents were confirmed in terms of occurrence type, workplace size, length of service, employment type, etc. In this study, customized countermeasures were found.

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.

PURPOSES : This study aims to conduct a sensitivity analysis to determine the major factors affecting traffic accidents involving elderly pedestrians. METHODS : In this study, a regression tree model was built based on a non-parametric statistical model using data on traffic accidents involving elderly pedestrians. Using this model, we analyzed the degree of change in the probability of pedestrian fatalities. RESULTS : Results of the model analysis show that the first major factor combination affecting traffic accidents involving elderly pedestrians is speeding, night time, and road markers. The second combination is night time and arterial roads (national and local highways). The last combination that may lead to such accidents is heavy vehicles and federally funded local highways. CONCLUSIONS : Preventive measures, such as speed control, proper lighting, median strips, designation of pedestrian protection zones, and guidance of detours, are necessary to manage high-risk combinations causing accidents of the elderly.

해양을 이용하려는 수요자 증가에 따라, 해양공간을 합리적으로 배분하기 위해 해양공간계획(Marine Spatial Planning)제도가 도 입되었다. 이 중 어업활동보호구역은 수산자원보호 등 어업활동 보호를 위해 지정되었다. 그러나, 어업활동보호구역을 주로 항해하는 어 선은 우리나라에서 발생하는 해양사고의 약 70 %를 차지할 정도로 위험에 노출되어 관리가 필요하다. 본 연구의 목적은 어업활동보호구 역 내 어선 통항 안전 확보를 위해 어업활동보호구역과 항만·항행구역에서 발생하는 해양사고를 분석하는 것이다. 이를 위해 해양용도구 역의 교통량을 조사하고 선종별, 사고 유형별, 톤수별, 사고원인별, 인명피해별로 해양사고를 조사하였다. 분석 결과 각 유형별 단위 면적 당 해양사고는 대부분 항만·항행구역에서 더 많이 발생하였으나 전체적으로 발생한 해양사고는 어업활동보호구역이 높았다. 특히 인명사 고가 많이 발생하여 통항 안전관리가 필요한 것으로 식별되었다.

이 연구는 교도관들이 직무수행 중 경험하는 교정사고와 폭력피해의 유형과 규모를 측정하고, 교정사고와 폭력피해의 경험이 교도관들의 직무스트레스와 직무만족도에 미치는 영향에 대해 알아보고자 하는 목적으로 진행하였다. 4개 지방교정청 산하의 15개 교정시설을 선정한 후 총 385명의 교도관을 대상으로 그들의 각종 교정사고 경험에 대한 데이터를 수집하였으며 더불어서 직무스트레스 와 직무만족도를 측정하였다. 먼저 12개의 교정사고 유형별로 경험빈도를 측정하였는데, 빈도와 비율이 가장 높 은 것부터 5개를 순서대로 나열해 보면, 수용자 간 언어적 폭력, 수용자 간 정서적 폭력, 교도관에 대한 수용자의 언어적 폭력, 교도관에 대한 수용자의 정서적 폭력, 수 용자들의 소란과 난동의 순이었다. 교도관에 대한 수용자의 신체적 폭력은 수용자들 의 자해와 비슷한 빈도와 비율을 보였으며(60% 내외), 교도관의 직접 경험담을 통해알아 본 교도관의 폭력피해의 구체적 사례를 감안하면 교도관을 향한 수용자들의 폭 력의 심각성이 상당히 크다는 사실을 알 수 있었다. 교정사고 경험과 수용자로 부터의 폭력피해가 교도관의 직무스트레스와 직무만족도 에 미치는 영향에 대한 분석결과, 선행연구들의 결과와 일치하는 경향을 보였다. 다시 말해, 수용자들이 교정시설 안에서 일으키는 각종사고와 교도관에 대한 폭력은 교도 관들의 직무스트레스에 부정적인 영향을 준다는 것이 입증되었다. 특히 교도관들의 폭력피해가 직무스트레스에 미치는 영향이 상대적으로 크다는 것도 알 수 있었다. 교정사고 경험과 폭력피해가 직무만족도에 미치는 과정에서 직무스트레스의 효과 여부를 확인하기 위해 시행한 분석에서 직무스트레스는 교정사고 경험과 폭력피해 경 험이 직무만족도에 미치는 영향을 매개한다는 것도 경험적으로 지지되었다. 이러한 결과를 기반으로 교도소의 안전을 달성하고, 교도관들의 직무 위험을 낮추 며, 폭력피해의 트라우마를 회복하도록 도와주기 위해서는 교도소의 각종 폭력에 대 한 보다 본격적인 연구와 연구결과에 기반한 근거기반 정책의 수립과 집행이 필요하 다는 것을 제언하였다.