• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Journal of Navigation and Port Research
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• v.40 no.1
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• pp.27-34
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• 2016

For the prevention of marine casualties, international bodies have mainly focused on strengthening ship's stability and design, maritime education and training, and improving maritime traffic environment. Statistics analysis on marine casualties showed that most of casualties occurred in coastal waters, especially by human elements. In order to review the conformity of existing prevention measures with the result of the statistics analysis, the IMO's SHELL model was applied to the established measures. As a result, ergonomic approaches were needed for the prevention of human errors in coastal waters, so that the priority should be given to the interface between ship's operator and navigational environment. For this study, Rasmussen's SRK pyramid, which showed decision making mechanism of human, and the US Coast Guard's investigation manual on marine casualties concerning the collapse of safe maritime transportation system were reviewed, and the merits and demerits within the risk assessment tools such as IWRAP, PAWSA, ES model, PARK model, and NURI model were also studied. Although the effectiveness of the existing risk assessment models was proved in ports and approaching channels, it is concluded that the need of new models for converting Korean seafarers' qualitative risk to quantitative risk was proposed so as to print hazard maps which make seafarers instinctively recognize comparative hazard levels of coastal waters.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.483-491
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• 2021

The identification of regional collision risks in water areas is significant for the safety of navigation. This paper introduces a new method of collision risk assessment that incorporates a clustering method based on the distance factor - hierarchical clustering - and uses real-time data in case of several surrounding vessels, group methodology and preliminary assessment to classify vessels and evaluate the basis of collision risk evaluation (called HCAAP processing). The vessels are clustered using the hierarchical program to obtain clusters of encounter vessels and are combined with the preliminary assessment to filter relatively safe vessels. Subsequently, the distance at the closest point of approach (DCPA) and time to the closest point of approach (TCPA) between encounter vessels within each cluster are calculated to obtain the relation and comparison with the collision risk index (CRI). The mathematical relationship of CRI for each cluster of encounter vessels with DCPA and TCPA is constructed using a negative exponential function. Operators can easily evaluate the safety of all vessels navigating in the defined area using the calculated CRI. Therefore, this framework can improve the safety and security of vessel traffic transportation and reduce the loss of life and property. To illustrate the effectiveness of the framework proposed, an experimental case study was conducted within the coastal waters of Mokpo, Korea. The results demonstrated that the framework was effective and efficient in detecting and ranking collision risk indexes between encounter vessels within each cluster, which allowed an automatic risk prioritization of encounter vessels for further investigation by operators.

• Journal of the Korean Geosynthetics Society
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• v.13 no.1
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• pp.85-92
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• 2014

Structures that have constructed in soft clay might suffer from many issues related to consolidation settlement or lateral movement of soft-clay during long-term period. Therefore, it is important to establish proper design and construction processes related to site investigation, soil improvement, construction management, and so on. This case study focused on the construction of the rahmen structure supported by pile foundations. Especially, the structure in this case had been constructed without improving underlying soft clay and before constructing backfill embankment due to the limited construction time and the traffic connection of the old road crossing new highway. Therefore, in order to satisfy the structural stability, the construction processes and countermeasure methods were carefully planned based on the results of preliminary numerical analyses and monitoring of ground behaviors. Through the trial and error precess during the construction, the structures had been successfully constructed.