• Journal of the Korean Institute of Navigation
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• v.12 no.2
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• pp.43-55
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• 1988

The amount of cargoes and fishery production have increased continuously during the last decade due to the great growth of the Korean economy. These increasements have made our coastal traffic congested, and the future coastal traffic is also expected to increase considerably. The increased traffic can be a cause of large sea pollution as well a s greater sea casualties us as properties and human lives, which could result in a big national loss. In order to prevent the sea casualties and promote the safety of coastal traffic, the Vessel Traffic Management System (VTMS) along the Korean coastal waterway is inevitably introduced. But, the precise evaluation is necessary required prior to the implementation of VTMS because this system necessitates a huge amount of budgets. This paper aims to propose the model of evaluation process, but the evaluation as to the urgency of establishment is not only very complicated and fuzzy but also affected by the subjectivity of human. Therefore, fuzzy integral is adopted as the mathematical model of evaluation in which decision-maker can intervence by making decision considering the calculated membership-function. Four aspects, namely, the frequency of sea-casualities, the traffic volume, the frequency fuzzy day, and the complexity of waterway are selected as the item of evaluation, and the fuzzy measure are applied to the evaluation of 8 candidated regions such as the adjacent area to the port Inchen, Kunsan, Mokpo, Wando, Yosu, Pusan, Pohang, Donghae. As a result of evaluation, the priority as to the candidated regions is obtained, and the following prior execution regions, namely, the adjacent area to the port Pusan, Yosu, Mokpo & Wando are selected by considering the present situation, but, in the long run, the VTMS should be executed in the whole coast of the nation, through the cost-effectiveness analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.462-469
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• 2023

In this study, we propose a method for evaluating the risk of collision between ships to support determination on the risk of collision in a situation in which ships encounter each other and to prevent collision accidents. Because several uncertainties are involved in the navigation of a ship, must be considered when evaluating the risk of collision. We apply the Dempster-Shafer theory to manage this uncertainty and evaluate the collision risk of each target vessel in real time. The distance at the closest point approach (DCPA), time to the closest point approach (TCPA), distance from another vessel, relative bearing, and velocity ratio are used as evaluation factors for ship collision risk. The basic probability assignments (BPAs) calculated by membership functions for each evaluation factor are fused through the combination rule of the Dempster-Shafer theory. As a result of the experiment using automatic identification system (AIS) data collected in situations where ships actually encounter each other, the suitability of evaluation was verified. By evaluating the risk of collision in real time in encounter situations between ships, collision accidents caused by human errora can be prevented. This is expected to be used for vessel traffic service systems and collision avoidance systems for autonomous ships.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.367-375
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• 2023

This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.