• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.186-192
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• 2014

In this paper, we analysed vessel traffic volume and patterns of traffic flow for ships using areas where included wind farm site and adjacent waters of Daejeong Offshore Wind Farm, and estimated traffic volume by classified navigational routes according to suggestion of rational routeing measures on the basis of classified patterns after installation of offshore wind facilities. Also, we assessed vessel traffic safety for each designed routeing measures on the basis of estimated traffic volume and proposed requisite countermeasures for the safe navigation of ships. With a result of analysing patterns of traffic flow, the current traffic flow was classified by 8 patterns and the annual traffic volume was predicted to 8,975 ships. On the basis of these, expected the vessel traffic volume according to designed four routeing mesaures after installation of wind farm. As result of assessing vessel traffic safety by using powered-vessel collision model of SSPA on the basis of the estimated traffic volume, the value of collision probability was less than safe criteria $10^{-4}$. Thereby we made sure usability of the designed routeing measures for the safe navigation of ships.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.155-156
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• 2022

Efficient operation of ships can transport cargo to ports safer and faster, and reduce fuel costs. Therefore, in this study, the pattern was analyzed using AIS data of ships passing near Busan Port, a representative port in Korea. The analysis of vessel traffic patterns was approached with a grid-based node generation method, which can be used for research such as optimal route and route prediction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.310-311
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• 2015

Ships' tracking data are being monitored and collected by vessel traffic service center in real time. In this paper, we intend to contribute to vessel traffic service operators' decision making through extracting ships' tracking patterns and models based on these data. Support Vector Machine algorithm was used for vessel track modeling to handle and process the data sets and k-fold cross validation was used to select the proper parameters. Proposed data processing methods could support vessel traffic service operators' decision making on case of anomaly detection, calculation ships' dead reckoning positions and etc.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.288-294
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• 2014

Understanding a ship's present position has been one of the most important tasks during a ship's voyage, in both ancient and modern times. Particularly, a ship's dead reckoning (DR) has been used for predicting traffic situations and collision avoidance actions. However, the current system that uses the traditional method of calculating DR employs the received position and speed data only. Therefore, it is not applicable for predicting navigation within the harbor limits, owing to the frequent changes in the ship's course and speed in this region. In this study, planned routes were applied for improving the reliability of the proposed system and predicting the traffic patterns in advance. The proposed method of determining the dead reckoning position (DRP) uses not only the ships' received data but also the navigational patterns and tracking data in harbor limits. The Mercator sailing formulas were used for calculating the ships' DRPs and planned routes. The data on the traffic patterns were collected from the automatic identification system and analyzed using MATLAB. Two randomly chosen ships were analyzed for simulating their tracks and comparing the DR method during the timeframes of the ships' movement. The proposed method of calculating DR, combined with the information on planned routes and DRPs, is expected to contribute towards improving the decision-making abilities of operators.

• Journal of the Korean Society of Marine Environment & Safety
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• v.6 no.2
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• pp.1-15
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• 2000

In world trade, the vessel traffic in major routes has been congested due to the rapid increase of cargoes and shipping tonnages. The patterns of vessel traffic have also been complicated and diversified. Therefore it was necessary that the Vessel Traffic Service(VTS) should be established in order to enhance the safety of navigation, to prevent the loss of life and damage to the environment. The first advanced radar surveillance system(LevelIII-VTS) was introduced in Pohang, Korea in 1993 and in 13 other ports later. While the hardware of Korea VTS is equal to that of an advanced country, the software, specially the operation manual, the recruitment and education of VTS operator, and the VTS service area is behind that of Russia, USA, Germany, Hong Kong, Singapore and others. After researching and investigating. the VTS equipment and service area of many countries, and analyzing the IMO regulations relevant to VTS and the traffic pattern and accident of Pohang port, the most efficient VTS service area should be established in Pohang. According to the analysis of the preceding studies and research on VTS, the worldwide VTS areas are recognized under the following conditions: First, the service area should be extended over at least radar coverage taking into account of traffic flow, traffic density, the degree of danger to navigation and harbour condition in order to provide all possible services. Second, the established service area should be subdivided and systematized to render reliable VTS services, such as the allocation of VHF frequency and reporting procedure in each area. In conclusion, the VTS service area of Pohang must be established and operated over 10 miles from shore(radar site) covering the radar coverage, so as to include the area of traffic congestion and high density traffic flow.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.634-643
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• 2020

Because of the continuous increase in the demand for and importance of marine space, marine exploration and survey activities are being actively conducted in Korea actively. Because the marine survey vessels used for these activities have special operational patterns depending on the purpose and probe vessels, research on maritime traffic risk is required. In this study, an attempt was made to determine the correlation of each factor with the effect of marine exploration and survey vessel operation on maritime traffic. The status of ocean exploration and survey vessels in operation in Korea was identified, as well as the special operational conditions of some of the ocean physical probes. Generally, the number of exploration and survey vessels involved per hour, total vessel length(including exploration equipment), operation, interval distance of exploration as per plan, and marine traffic conditions(traffic volume and speed) can be classified as operating factors. To compare the results of the environmental stress, a maritime traffic flow simulation based on the "ES" Model was performed with each of the identified operating factors as independent variables. The results of the analysis confirmed that the environmental stress significantly changed in the order of traffic volume, ship length and speed. In addition, it was confirmed that the environmental stress is reduced when the operation course is set at an angle with the nearby maritime traffic flow. Accordingly, it can help reduce the operator's burden if the survey vessel operator understands nearby maritime traffic conditions and reflects them in the operation method when setting the operation plan.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1195-1202
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• 2016

Recently, a lot of studies that applying the big data technology to various fields, are progressing actively. In the maritime domain, the big data is the meaningful information which makes and gathers by the navigation and communication equipment from the many ships on the ocean. Also, importance of the maritime safety is emphasized, because maritime accidents are rising with increasing of maritime traffic. To support prevention of maritime accidents, in this paper, we developed a vessel traffic display and statistic system based on AIS messages from the many vessels of maritime. Also, to verify the developed system, we conducted tests for vessel track display function and vessel traffic statistic function based on two test scenarios. Therefore, we verified the effectiveness of the developed system for vessel tracks display, abnormal navigation patterns, checking failure of AIS equipments and maritime traffic statistic analyses.

• 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 the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.402-409
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• 2016

Vessel traffic servies (VTS) control movements in ports and coastal areas 24 hours a day using VHF. Thus, we were able to check ship movements and the patterns followed by VTS officers in VTS areas using VHF communication analysis. This study is intended to identify control intervals for dangerous situations and provide VTS officers with basic data and guidelines to prevent these occurrences in advance. We listened to Busan port's VHF communication for seven days and obtained risk values using the Park model with reference to controlled ships. The probability of a dangerous situation arising under a controller's watch per unit of time was confirmed to follow a Poisson distribution. As a result, for each 3.50 hours that VTS directly controls an area, (and in daytime for each 2.85 hours) a ship communicates in a VTS area every 3.84 hours, and some of there communications exceed certain risk values in VTS areas.