When a fire breaks out in a distribution center, it causes a lot of damage. And the most casualties are caused by Fire accidents. Therefore, training for fire prevention should be mandatory at the distribution center. Also, the contents of education should be different in room temperature warehouses and low temperature warehouses. Fire education in low-temperature warehouses should be more emphasized. This is because many fires occur in low-temperature warehouses. In this study, a study was conducted to determine the important order of training hours and contents for fire prevention education according to the type of distribution center. The importance of time and content for safety education in all types of warehouses did not differ significantly. It was first decided that safety prevention training should be conducted periodically in all types of warehouses

In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

국토교통부는 2020년 '결빙 취약구간 평가 세부 배점표’에 따라, 전국의 고속국도와 일반국도를 대상으로 410개 구간의 결빙 취약구 간을 선정하였다. 그러나, 2021년 감사원의 결빙 취약구간 지정 적정성 감사 결과에서 감사원은 현재 지정ㆍ관리 중인 결빙 취약구간 및 결빙 취약구간 평가 세부 배점표의 적정성에 문제를 제기하였다. 이에, 국토교통부는 결빙 취약구간을 재지정하여 발표하였으나 그 에 대한 평가 및 지정 적정성 검증이 아직 이루어지지 않았다. 본 연구에서는 결빙 취약구간과 결빙사고 데이터의 위치정보를 수집하여 GIS(Geographic Information System) 데이터로 구축하고 맵핑(Mapping)하여 결빙 취약구간 내 결빙사고이력을 확인함으로서 결빙 취약구간의 결빙사고 예측성능을 평가하였다. 또한, 각 결빙 사고 발생지점에서 도로시설, 교통, 선형구조, 환경인자 데이터를 수집하여 분석한다. 이를 통해 결빙사고와 각 인자 간의 상관성을 파 악하고, 그 결과에 따라 결빙 취약구간 평가 세부 배점표의 평가항목 및 각 항목별 배점을 수정하고 보완함으로써 결빙 취약구간의 신뢰성을 제고한다.

겨울철 국내 도로 결빙으로 인한 교통사고가 증가하는 추세를 보이고 있으며 2018년~2022년까지 총 4,609건의 결빙 교통사고가 발 생하였다. 결빙 교통사고의 치사율은 2.3으로 일반적인 교통사고와 비교하여 높은 치사율을 보이며 최근 5년(2018~2022)동안 결빙 교 통사고로 인하여 107명이 사망자와 7,728명의 부상자가 발생하였다. 현재 국토교통부에서 제시한 결빙 취약구간 평가기준표에 따라 결 빙 위험 구간을 지정하고 있으나, 해당 기준은 결빙의 주요 요인으로 고려되는 기상조건을 충분히 반영하지 못하고 있다. 도로 결빙은 노면온도가 0℃ 이하이며 노면에 수분이 공급될 때 형성되며 기온, 구름량, 풍속, 풍향, 상대습도, 강수량 등의 기상인자들이 복합적으 로 작용하여 결빙이 발생한다는 점을 고려하였을 때, 기상 특성은 도로 결빙의 주요 인자로 판단된다. 따라서 국내 결빙 취약구간 평 가기준의 개선이 필요하며 본 연구의 목적은 국내 결빙 교통사고 데이터를 분석하고 결빙이 형성되는 기상 조건을 구체화하는 것이다. 분석을 위한 데이터로 2018년~2022년까지 5년동안 발생한 결빙사고 사례와 기상청 방재기상관측소(AWS)에서 제공하는 기상 데이터 를 적용하였다. 이후, 박스도표, 확률밀도함수 등의 통계분석을 적용하여 결빙 형성 기상 조건을 구체화하였다. 이를 통하여 기존 결빙 취약구간 평가기준의 기상학적 개선 방향성을 제시할 수 있으며 더 나아가 도로 결빙 예측 로직 개발을 기대할 수 있다.

PURPOSES : This study aimed to identify factors affecting the duration of traffic incidents in tunnel sections, as accidents in tunnels tend to cause more congestion than those on main roads. Survival analysis and a Cox proportional hazards model were used to analyze the determinants of incident clearance times. METHODS : Tunnel traffic accidents were categorized into tunnel access sections versus inner tunnel sections according to the point of occurrence. The factors affecting duration were compared between main road and tunnel locations. The Cox model was applied to quantify the effects of various factors on incident duration time by location. RESULTS : Key factors influencing mainline incident duration included collision type, driver behavior and gender, number of vehicles involved, number of accidents, and post-collision vehicle status. In tunnels, the primary factors identified were collision type, driver behavior, single vs multi-vehicle involvement, and vehicles stopping in the tunnel after collisions. Incidents lasted longest when vehicles stopped at tunnel entrances and exits. In addition, we hypothesize that incident duration in tunnels is longer than in main roads due to the reduced space for vehicle handling. CONCLUSIONS : These results can inform the development of future incident management strategies and congestion mitigation for tunnels and underpasses. The Cox model provided new insights into the determinants of incident duration times in constrained tunnel environments compared to open main roads.

현대 해양 산업은 기술적 발전을 통해 신속한 발전을 이루고 있다. 이러한 발전을 주도하는 주요 기술 중 하나는 데이터 처리 기술이며, 이 중 자연어 처리 기법은 사람의 언어를 기계가 이해하고 처리할 수 있도록 하는 기술이다. 본 연구는 자연어 처리 기법을 통해 해양안전심판원의 재결서를 분석하여 이미 재결이 이루어진 선박 충돌사고의 원인 제공 비율을 학습한 후, 새로운 재결서를 입력 하면 원인 제공 비율을 예측하는 모델을 개발하고자 하였다. 이 모델은 사고 당시 적용되는 항법과 원인 제공 비율에 영향을 주는 핵심 키워드의 가중치를 이용하여 사고의 원인 제공 비율을 계산하는 방식으로 구성하였다. 이 연구는 이러한 방식을 통해 제작한 모델의 정 확도를 분석하고, 모델의 실무 적용 가능성을 검토함과 동시에 충돌사고 재발 방지 및 해양사고 당사자들의 분쟁 해결에 기여할 것으로 기대한다.

우리나라에서는 연간 250건 이상의 해양 기름유출사고가 발생하고 있으며, 이는 지역 사회 및 환경에 큰 영향을 미친다. 국제 협약 및 국내법에서는 오염자부담의 원칙을 바탕으로 기름유출에 대한 피해 배상을 유출 당사자에게 책임지도록 하고 있으며, 민·형사적 책임 규명을 위해 유출 행위자에 대한 적극적인 조사가 이루어지고 있다. 기름 유출사고의 행위자 조사의 중요성 확대에 따라서 CEN 15522-2, ASTM D 3248 등의 표준을 이용해 기름 시료 간의 유사성 판정을 하고 있다. 이 중 가장 활발히 활용되고 있는 유럽표준인 CEN 15522-2가 2023년 EN 15522-2로 3차 개정되었다. 본 연구는 EN 15522-2를 이용하여 국내 발생한 해양 기름유출사고 시료를 분석하고, 적용 성에 대하여 확인하였다. 그 결과 경질유 유출사고가 40% 이상을 차지하는 국내 유출사고의 특징을 비춰볼 때 Adamamtanes와 같은 저비 점의 물질이 추가된 EN 15522-2의 적용은 효용성이 높은 것으로 확인되었다.

PURPOSES : This study aims to identify the thresholds at which various factors affecting traffic crashes lead to actual traffic crashes METHODS : To verify the thresholds, we created scenarios and ran simulations with a combination of factors that affect traffic crashes. Lateral offset and minimum TTC were used to evaluate whether an incident occurred. RESULTS : In the first scenario, the most significant factor affecting traffic crashes is curvature, and it was found that the smaller the curvature(200 meters or less), the greater the deviation from the lane. And in the second scenario, especially the passenger car scenario, no accidents occurred when the curvature was greater than 90 meters and the speed was 40 km/h or less. The smaller the curvature and the higher the speed, the more accidents occurred. Similarly, in the bus scenario, no accidents occurred when the curvature was 120 meters or more and the speed was 30 km/h or less. Also, accidents tended to occur when the curvature was smaller and the speed was higher. CONCLUSIONS : Through this study, we derived the thresholds of factors that influence traffic crashes. The results are expected to help design and operate roads in the future and contribute to reducing traffic crashes.

PURPOSES : This study aims to understand the characteristics of accidents involving autonomous vehicles and derive the causes of accidents from road spatial information through autonomous vehicle accident reports. METHODS : For this study, autonomous vehicle accident reports collected and managed by the CA DMV were used as data sources. In addition, spatial characteristics and geometric data for accident locations were extracted by Google maps. Based on the collected data, the study conducted general statistics, text embedding, and cross-analysis to understand the overall characteristics of autonomous vehicle accidents and their relationship with road spatial features. RESULTS : The analysis results for characteristics of autonomous vehicle accidents, applying statistical analysis and text embedding techniques, reveal that the damages caused by autonomous vehicle accidents are often minor, and approximately half of the accidents are triggered by other vehicles. It is noteworthy that accidents where autonomous vehicles are at fault are not uncommon, and when the cause of the accident is within the autonomous vehicle, the accident risk can increase. The accident analysis results using spatial data showed that the severity of accidents increases when on-street parking is present, when dedicated lanes for bicycles and buses exist, and when bus stops are present. CONCLUSIONS : Through this study, geometric and spatial elements that appear to have an impact on autonomous driving systems have been identified. The findings of this study are expected to serve as foundational data for improving the safety of autonomous vehicle operations in the future.

PURPOSES : The purpose of this study is to statistically analyze the meteorological factors that contribute to the formation of road surface icing based on actual cases of icing accidents and provide directions for improving icing evaluation criteria. METHODS : In this study, we collected cases of domestic road icing accidents by searching news articles with the keyword ‘icing collision accidents’. Subsequently, we determined the latitude, longitude, and altitude of accident locations using satellite map service. We applied the Inverse Distance Weighting (IDW) method and temperature lapse rate to estimate meteorological data at each location. Finally, statistical analysis was conducted for temperature, humidity, and precipitation occurrence using probability density functions. RESULTS : As a result, road icing accident data points with identifiable location coordinates were collected. Among these, temperature, humidity, and precipitation occurrence from Automated Weather Stations (AWS) data were selected for analysis. During the process of correcting meteorological factors using the Inverse Distance Weighting (IDW) method, the optimal Weighting Exponent (p) that minimizes the error was determined and applied. The results showed that accidents occurring in the morning indicated the highest accident occurrence rate. The average temperature at the time of the accidents was -1.4°C, with a humidity level of 85.1%. Precipitation was observed at the time of the accident in 19 cases. CONCLUSIONS : Icing on pavement can occur not only under extreme weather conditions but also under typical meteorological conditions. Typically, icing can occur when the relative humidity is above 70%. Accordingly, for future improvements in the evaluation criteria for icing-prone areas by the Ministry of Land, Infrastructure and Transport, it is possible to incorporate the temperature and humidity ranges that generally lead to icing, taking into account climate characteristics.

This study analyzed the factors affecting the effectiveness of the Chemical Hazard Risk Management (CHARM). A survey was conducted on 104 learners who participated in the Risk Assessment training course at Occupational Safety and Health Training Institute. Through a self-administered questionnaire, the effect of personal characteristics, corporate characteristics, and safety and health level of the company on the effectiveness of chemical risk assessment was investigated. As a result of statistical analysis, the safety and health level of the company had a positive (+) effect on the effectiveness of Chemical Hazard Risk Management(CHARM), but personal characteristics and corporate characteristics had no relation to it. This study can be used as basic data for further research related to chemical risk assessment in workplaces.

이 연구는 대학생의 불확실성에 대한 인내력 부족과 취업 스트레스 의 관계에서 희망적 사고와 심리적 안녕감의 순차 매개효과를 확인하 기 위한 목적에서 수행되었다. 이를 위해 2023년 8월 한 달 동안 서울 및 경기도 소재 4년제 대학교 3곳에 재학 중인 대학생 298명을 대상으 로 자료를 수집하고 SPSS 26.0 및 Process Macro 4.1 프로그램을 활용하여 기술 통계 및 상관분석, 개별 매개효과 및 순차 매개효과 분 석을 수행하였다. 분석 결과, 대학생의 불확실성에 대한 인내력 부족과 취업 스트레스의 관계에서 희망적 사고와 심리적 안녕감 각각의 개별 매개효과는 통계적으로 유의했다. 또한 희망적 사고와 심리적 안녕감을 순서대로 투입한 순차 매개효과 또한 통계적으로 유의했다. 즉 대학생 의 불확실성에 대한 인내력이 부족할수록 희망적 사고가 감소하여 심 리적 안녕감을 저해함으로써 결과적으로 취업 스트레스를 증가시키는 것이 확인되었다. 이를 토대로 현재 취업으로 인해 상당한 스트레스를 경험하고 있는 한국의 대학생들을 도울 수 있는 개입 또는 중재 방안 이 취업 지원 시 중요하게 고려되어야 함을 제언하였다.

스페인은 1992 CLC와 1992 FC 체약국임에도 불구하고, 스페인 대법원은 협 약과 국내법을 혼용하는 방법을 통해 선주의 책임제한권을 부인하는 한편 P&I 보험자가 보험계약상의 담보한도까지 항변권 없이 보상해야 한다고 판결하였 다. 이는 선주의 책임제한권이 배제되는 경우에도 책임보험자는 선주책임한도 액까지만 보상책임이 있다는 1992 CLC의 명시적 규정을 무력화한 판결이다. 스페인이 1992 CLC와 1992 FC 체약국임에도 불구하고 협약과 달리 판결하 고 이의 집행을 추진하는 것에 대해 많은 P&I보험자들은 물론 ICS와 같은 선주단체에서도 선주책임제한 제도의 붕괴를 우려하고 있다. 스페인 대법원 판결이 나온 직후 IMO에서는 선주책임제한 규정의 통일해석 결의안을 채택하였다. 통일해석 결의안은 1992 CLC나 1976 LLMC를 기초할 때 에 선주책임한도액의 인상 대가로 선주책임제한이 사실상 조각되지 않도록 의 도하였다는 점을 인정하여 채택한 것이다. 이 결의안은 선주책임제한 배제사유 의 해석이 국가에 따라 또는 지역에 따라 편의적으로 해석되지 않게 하여 선주 책임제한 제도의 붕괴를 막으려는 조치로 다행스러운 일이다. 향후 이 IMO 통 일해석 결의안이 의도한 대로 해석되도록 P&I보험자와 선주 및 이들을 상대로 손해배상을 청구할 당사자들과 각국의 법원이 함께 노력해야 한다. 왜냐하면, 선주책임제한 제도 없이는 특히, 유류오염손해와 관련한 선주책임제한 제도 없 이는 선박활동이나 무역이 온전히 유지될 수 없고 무역 없이는 현대사회도 지 금처럼 지속될 수 없기 때문이다. 스페인 정부가 협약에서 정한 금액보다 훨씬 많은 금액을 회수하기 위해 사고발생 20년이 지난 지금도 P&I Club을 상대로 소송을 계속하고 있는 것 자체가 협약의 통일적인 해석기준과 지침이 국제적으로 절실히 필요함의 방 증이다. 한편, 이 사건에서 영국의 London P&I Club은 보험계약규정상의 조합원선 지급원칙을 통해 스페인 정부의 직접청구를 방어 중인데, 만일 Korea P&I Club을 상대로 직접청구를 시도한다면 우리나라 법원은 이를 승인할 것인 가? 우리나라가 1992 CLC 체약국인데 이 협약을 무력화한 스페인 대법원의 판결은 외국판결의 승인요건 제외사유인 “우리나라의 선량한 풍속이나 사회 질서에 어긋난” 판결에 해당하기 때문에 우리 법원이 이의 집행을 승인하지 않아야 할 것이다. “선주의 고의 또는 무모한 행위”를 근거로 선주책임제한이 배제되는 경우, 보험보상 역시 “피보험자의 고의적 불법행위”를 근거로 보험자 면책에 해당 될 수 있으므로 선주의 책임제한을 배제하려는 시도는 무조건 추진될 일은 아니다.

PURPOSES : This study aims to analyze the causes of pedestrian traffic accidents on community roads. METHODS : This study collected variables affecting pedestrian traffic accidents on community roads based on field surveys and analyzed them using negative binomial regression and zero-inflated negative binomial regression models. RESULTS : Model analysis results showed that the negative binomial regression model is more suitable than the zero-inflation negative binomial regression model. Additionally, the segment length (m), pedestrian volume (persons/15 min), traffic volume (numbers/15 min.), the extent of illegal parking, pedestrian-vehicle conflict ratio, and one-way traffic (one: residential, two: commercial) were found to influence pedestrian traffic accidents on community roads. Model fitness indicators, comparing actual values with predicted values, showed an MPB of 1.54, MAD of 2.57, and RMSE of 7.03. CONCLUSIONS : This study quantified the factors contributing to pedestrian traffic accidents on community roads by considering both static and dynamic elements. Instead of uniformly implementing measures, such as pedestrian priority zones and facility improvements on community roads, developing diverse strategies that consider various dynamic factors should be considered.

PURPOSES : This study investigates the factors affecting extra-long tunnel accidents by integrating data on tunnel geometry, traffic flow, and traffic accidents and derives the underlying implications to mitigate the severity of accidents. METHODS : Two processes centered on three key data points (tunnel geometry, traffic flow, and traffic accidents) were used in this study. The first is to analyze the spatial characteristics of extra-long tunnel traffic accidents and categorize them from multiple perspectives. The other was to investigate the factors affecting extra-long tunnel traffic accidents using the equivalent property-damage-only (EPDO) of individual accidents and the aforementioned data as the dependent and independent variables, respectively, by employing an ordered logistic regression model. RESULTS : Gyeonggi-do, Gyeongsangnam-do, and Gangwon-do are three metropolitan municipalities that have a significant number of extra-long tunnel accidents; Busan and Seoul have the most extra-long tunnel accidents, accounting for 23.2% (422 accidents) and 18.6% (339 accidents) of the 1,821 accidents that occurred from 2007 to 2020, respectively. In addition, approximately 70% of extra-long tunnel traffic accidents occurred along tunnels with lengths of less than 2 km, and Seoul and Busan accounted for over 60% of the top 20 extra-long tunnels with accidents. Most importantly, the Hwangryeong (down) tunnel in Busan experienced the most extra-long tunnel traffic accidents, with 77 accidents occurring during the same period. As a result of the ordered logistic regression modeling with EPDO and multiple independent variables, the significant factors affecting the severity of extra-long tunnel traffic accidents were determined to be road type (freeway, local route, and metropolitan city road), traffic flow (speed), accident time (year, summer, weekend, and afternoon), accident type (rear end), traffic law violations (safe distance violation and center line violation), and offending vehicles (van, sedan, and truck). CONCLUSIONS : Based on these results, the following measures and implications for mitigating the severity of extra-long tunnel traffic accidents must be considered: upgrading the emergency response level of all road types to that of freeways and actively promoting techniques for regulating high-speed vehicles approaching and traversing within extra-long tunnels are necessary. In addition, the emergency response and preparation system should be reinforced, particularly when the damage from extra-long tunnel traffic accidents is more serious, such as during the summer, weekends, and afternoons. Finally, traffic law violations such as safe distance and centerline violations in extra-long tunnels should be prohibited.

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.