• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.4
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• pp.305-310
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• 2016

This study identified necessary navigational support services to prevent accidents through an examination and a survey on the navigation and communication systems of non-SOLAS ships. The functional and operational requirements for the identified navigational support services were discussed accordingly. Among the navigational support services proposed are an Electronic Navigational Chart (ENC) service, a route planning service, an operation monitoring service, and collision prevention support services for ships in coastal areas. To facilitate the identified navigational support services, ship navigation system, shore supporting centre and maritime communication network were discussed as a digital infrastructure. The operational methode for the digital infrastructure were discussed in the service scenarios for ships carrying dangerous cargo, large ships over 200 meters in length and high speed passenger ships over 15 knots in speed. This study will facilitate the development of policies for the improvement of ship operation management in Korean coastal waters and will contribute to improving the navigational safety of non-SOLAS ships.

• 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.

• Journal of Navigation and Port Research
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• v.45 no.1
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• pp.9-15
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• 2021

According to IMO, MASS is defined as a vessel operated at various levels independent of human interference. The safety navigation support service for MASS is designed to improve the safety and efficiency of MASS by developing public services on shore for ship arrivals/departures and for cargo handling. The safety navigation support service consists of a total of six types of services: autonomous operation, berthing/unberthing/mooring, cargo handling and ship arrival/departure service, PSC inspection, condition monitoring, and accident response support services. In order to support accident response service, the relative importance of a bridge navigational equipment was assessed by stratifying the navigation system to provide safe and efficient support services by objective judgment through specific and quantitative methods using AHP, one of decision-making methods used by an expert group. The survey was conducted by dividing the bridge navigational equipment into depth, location, and speed information. As a result of applying the AHP method, the importance of depth, location, and speed information was assessed. The relative importance of each equipment for providing location information was also assessed in order of Radar, DGPS, ECDIS, Gyro compass, Autopilot, and AIS. This was similar to survey results on the utilization of each operator's preference and its impact on marine accidents.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.115-116
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• 2017

In this paper, we propose a standardization strategy for next generation electronic navigational chart which can be classified as S-100 Universal Hydrographic Data Model, to accept various requirements arising from various marine information and services as well as support e-navigation service strategies. IMO uses the next generation electronic chart standard, S-100 as Common Maritime Data Structure. It means that a common data model is needed as a key element for realization of e-Navigation and also points out that a new ICT convergence paradigm is needed not only for marine safety but also for maritime information and services. this paper considers he model-based data representation and reference model in order to understand the content and use of the S-100 standard and also considers the interconnectivity and role of the ISO/TC211 standards, which are being used as base standards for profiling to develop S-100 standard. Finally, we look at what standardization items are required for standardization of next generation electronic navigational chart supporting multi-purpose and how they are used mutually.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.285-286
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• 2016

We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.212-220
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• 2013

Recently, there has been tremendous increase in human-computer/machine interaction system, where the goal is to provide with an appropriate service to the user at the right time with minimal human inputs for human augmented cognition system. To develop an efficient human augmented cognition system based on human computer/machine interaction, it is important to interpret the user's implicit intention, which is vague, in addition to the explicit intention. According to cognitive visual-motor theory, human eye movements and pupillary responses are rich sources of information about human intention and behavior. In this paper, we propose a novel approach for the identification of human implicit visual search intention based on eye movement pattern and pupillary analysis such as pupil size, gradient of pupil size variation, fixation length/count for the area of interest. The proposed model identifies the human's implicit intention into three types such as navigational intent generation, informational intent generation, and informational intent disappearance. Navigational intent refers to the search to find something interesting in an input scene with no specific instructions, while informational intent refers to the search to find a particular target object at a specific location in the input scene. In the present study, based on the human eye movement pattern and pupillary analysis, we used a hierarchical support vector machine which can detect the transitions between the different implicit intents - navigational intent generation to informational intent generation and informational intent disappearance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.828-835
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• 2023

Vessel traffic service operators (VTSOs) need to quickly and accurately analyze the maritime traffic situation in the vessel traffic service (VTS) area and provide information to the vessels. However, if traf ic increases rapidly, the workload of VTSOs increases, and they may not be able to provide adequate information. Therefore, it is essential to develop VTSO support technologies that can reduce their workload and provide consistent information. In this paper, we propose a model for automatically detecting abnormal vessels in the VTS area. The proposed model consists of a positional model and a contextual model and is specifically optimized for the traffic characteristics of the target area. The implemented model was tested by using real-world data collected at a test center (Daesan Port VTS). Our experiments confirmed that the model could automatically detect various abnormal situations, and the results were validated through expert evaluation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.3
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• pp.219-225
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• 2008

Since July 2006, marine traffic safety management system have been enforced to support the vessels transiting across the coastal area and the vessels coming in and out of ports in southwestern coastal area where heavy traffic density and marine casualties occurred frequently. The marine traffic volume for the marine traffic environmental assessment was measured by the information from RADAR and AIS system in the area. The distributions of marine casualties were analyzed in the main routes and traffic separation schemes during the last five years and the navigational dangerous elements were investigated with the influence of natural environment, the distribution of fisheries and survey questionnaire. Marine accidents of merchant ships have a tendency to decrease gradually but in case of fishing boats, the rate of marine accidents have a contrary results in this area during the last five years. The dangerous elements on navigation appeared to be the dense force from June to August, fisheries activities and the vessels which not follow the compulsory watch on VHF-band radio communication equipments.

• 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 Navigation and Port Research
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• v.47 no.4
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• pp.212-219
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• 2023

Vessel Traffic Service (VTS) area presents a complex traffic pattern due to ships entering or leaving the port to utilize port facilities, as well as ships passing through the coastal area. To ensure safe and efficient management of maritime traffic, VTS operators continuously monitor and control vessels in real time. However, during periods of high traffic congestion, the workload of VTS operators increases, which can result in delayed or inadequate VTS services. Therefore, it would be beneficial to predict traffic congestion and congested areas to enable more efficient traffic control. Currently, such prediction relies on the experience of VTS operators. In this paper, we defined vessel traffic congestion from the perspective of a VTS operator. We proposed a method to generate traffic networks using historical navigational data and predict traffic congestion and congested areas. Experiments were performed to compare prediction results with real maritime data (Daesan port VTS) and examine whether the proposed method could support VTS operators.