• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.131-133
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• 2010

2000년부터 예부선 등록 척수가 급증하고 있으며, 예부선 대부분이 10년 이상의 노후선박으로 사고의 위험성이 크다. 전체 해양사고 건수는 점차 줄어드는 추세이나, 예부선 관련 사고는 줄어들지 않고 있으며, 2010년 상반기 해양사고 분석보고서에 의하면 예부선 사고는 전년 동기대비 84.4% (32척->59척) 증가했고 이 중 충돌사고 다수인 것으로 나타났다. 예부선 사고의 근본 원인 중 예부선 종사자(선원)의 수급 어려움과 이로 인한 종사자의 고연령 저학력 경향이 뚜렷하다. 본 발표에서는 고령 예부선 운항자의 안전운항 교육을 위해 승선환경을 고려한 다양한 콘텐츠 개발 및 활용방안에 대해 제안하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.160-161
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• 2018

ITU-R Study Group Working Party 5B에서는 해상에서 자율운항선을 안전하게 운항하기 위해 자율운항선을 통한 제어센터-VTS, 제어센터-유인선 간의 정보교환이 이루어 질 수 있도록 Vessel traffic control voice relay의 기능을 제시하였다. 이에 자율운항선을 통해 제어센터-VTS, 제어센터-유인선 간의 원활한 정보교환이 가능하도록 사용자 기능 요구사항, 사용자 비기능 요구사항, 인터페이스 요구사항으로 분석함으로써 통신중계시스템 설계 및 각 운용 기기별 정보교환 체계를 구축하였다. 하지만 자율운항선-타 선박간의 충돌 위험성을 감지할 경우 충돌회피를 위한 흐름 및 통신중계시템을 활용한 메시지 처리과정은 설계되지 아니한 실정이다. 이에 본 연구에서는 액티비티, 제어흐름, 작업 흐름 등의 표현이 가능한 UML(unified modeling language)을 활용함으로써 항해단계 중 발생할 수 있는 상황별 시나리오를 제어 흐름 형태로 표현한 정보교환 메시지 처리 알고리즘을 제안하고자 한다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.5
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• pp.527-534
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• 2019

Several types of mathematical analysis methods are used for port waterway risk assessment based on marine traffic volume. In Korea, a marine traffic congestion model that standardizes the size of the vessels passing through the port waterway is applied to evaluate the risk of the waterway. For example, when marine traffic congestion is high, risk situations such as collisions are likely to occur. However, a scientific review is required to determine if there is a correlation between high density of maritime traffic and a high risk of waterway incidents. In this study, IWRAP Mk2(IALA official recommendation evaluation model) and a marine traffic congestion model were used to analyze the correlation between port waterway risk and marine traffic congestion in the same area. As a result, the linear function of R2 was calculated as 0.943 and it was determined to be significant. The Pearson correlation coefficient was calculated as 0.971, indicating a strong positive correlation. It was confirmed that the port waterway risk and the marine traffic congestion have a strong correlation due to the influence of the common input variables of each model. It is expected that these results will be used in the development of advanced models for the prediction of port waterway risk assessment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.269-269
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• 2019

The ships are turning for the purpose of collision avoidence and change of course. It is possible that ships have capsizing accident when improper loading of cargo and excessive use rudder angle in turning. It is difficult for navigation officers to recognize the danger of heeling during a turn, because the dynamic state of the ship changes in real time. Thus, in this study, ship's heeling angle was predicted during turning using the maneuverability indices estimated from the ship's autopilot. The maneuverability indices estimated through the Kalman filter of Autopilot is real-time predictable. The turning radius was obtained from the estimated Index of turining ability and calculations of the heeling angle were possible in turning. It is intended to be used as a basic data on the prevention of danger heeling angle during turning.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.209-215
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• 2022

On the Jeju coast, international cruise ships, passenger ships, and other ships pass frequently, as well as many fishing boats. Thus, there is a high risk of marine accidents and frequent ship collisions. Accordingly, it is urgent to establish a coastal VTS for systematic safety management of ships passing through the coastal waters of Jeju. The purpose of this study was to set the area of the VTS to be newly established. In this study, to calculate the workload of the VTS operators, a formula was proposed that reflects the monitoring workload considering the monitoring frequency and required time for target as well as non-target ships and the workload for ship collision situations. The proposed formula was applied to the newly established VTS area in Jeju. Three control sectors were set up in each VTS center. The average number of workstations per hour was approximately 1, so the division between sectors was appropriate. Thus, it was deduced that there would be no workload for the VTS operators. It is expected that the method proposed in this study can be used as primary data for calculating the appropriate number of workstations for the current VTS, and setting the VTS area for a new coastal VTS in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.519-524
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• 2009

Although it is expected to provide fundamental data for advanced VTS system by analyzing traffic accidents in VTS area, there is no quantitative analysis to find it.. In this research, it is examined and analyzed marine casualties records(1999-2004), data of Port-MIS and data of each VTS center. The results of this research are as below. 1) It is necessary to reduce traffic accident and to improve VTS operating system. 2) It is discovered for statistical discrepancy between vessels controlled by VTS and vessels not controlled by VTS in accident cause, visibility, perception distance and cause of late perception in collision accidents 3) It is necessary for VTS assistance to be positive and to made in ample time consecutively. 4) As the result of traffic accident prediction model, it is necessary to develop a system improving VTS operators' ability to identify dangerous ships.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.209-216
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• 2004

In A bridge which connects Mokpo North Harbor and Com Island is going to be constructed until 2009. For the bridges being built in the navigable water area, it is indispensible to carry out vessel traffic safety assessment from the viewpoint of shiphandlers, however, there exist no specific guidelines for the necessary conditions whim the bridge designers can rely on. In this paper, traffic safety assessment procedures for the layout of the bridge is briefly introduced, and the conditions whim should be taken into account at the initial design stage of the bridge is surveyed. For the safety assessment of the bridge design, ship navigation simulations, such as RTS(real time simulation} and FTS(fast time simulation), are carried out, the results of which are statistically analysed to estimate the probability of collision between the ship and the pier of the bridge.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.74-81
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• 2024

In the near future, autonomous ships, ships controlled by shore remote control centers, and ships operated by navigators will coexist and operate the sea together. In the advent of this situation, a method is required to evaluate the safety of the maritime traffic environment. Therefore, in this study, a plan to evaluate the safety of navigation through ship control simulation was proposed in a maritime environment, where ships directly controlled by navigators and autonomous ships coexisted, using autonomous operation technology. Own ship was designed to have autonomous operational functions by learning the MMG model based on the six-DOF motion with the PPO algorithm, an in-depth reinforcement learning technique. The target ship constructed maritime traffic modeling data based on the maritime traffic data of the sea area to be evaluated and designed autonomous operational functions to be implemented in a simulation space. A numerical model was established by collecting date on tide, wave, current, and wind from the maritime meteorological database. A maritime meteorology model was created based on this and designed to reproduce maritime meteorology on the simulator. Finally, the safety evaluation proposed a system that enabled the risk of collision through vessel traffic flow simulation in ship control simulation while maintaining the existing evaluation method.