• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.144-145
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• 2023

육상, 철도, 항공 등 타 교통분야에서 지속적으로 사고와 인명피해가 줄어든 반면, 해양분야는 해양사고가 증가하며 실효적 해양교통안전관리에 대한 필요성이 대두되고 있다. 최근 3년간 국내 해상에서 발생한 충돌사고 중 어선을 포함한 충돌사고가 전체의 약 84%를 차지하며, 해상교통의 주요 변수인 어선을 포함한 국가의 해상교통량 파악은 반드시 필요한 실정이다. 본 연구에서는 현 정부 국정과제인 '디지털 해상 교통망 구축'과 더불어 해양교통안전관리체계 마련의 일환으로 국내 전체 선박위치발신장치(AIS, V-PASS) 데이터를 활용하여 해상교통량을 분석하고 예측 모델을 개발한다. 이를 위해 선박 밀집도를 통한 그리드별 공간가산분석과 항적 데이터 전처리 및 선형화, 선박 길이에 따른 점용면적 산정을 통한 단위 그리드별 해상교통량을 분석한다. 또한, 과거 교통량 데이터는 딥러닝 기반의 시계열 특성을 지닌 RNN과 LSTM 모델을 활용하여 교통량 예측 모형을 개발한다. 본 연구의 결과는 해상교통량과 해양사고의 연관성 분석 및 속력제한구역 등 해상정책 수립의 정량적 근거를 제공하며, 국민에게 해상교통정보 제공을 통해 교통복지 증진에 기여할 수 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.133-135
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• 2013

장래의 해상교통량에 대한 정확한 예측은 항로설계 및 해상교통의 안전성 평가 측면에서 중요한 요소이다. 본 연구는 신뢰성 있는 해상교통량을 추정하기 위해 시계열 모델의 지수평활법과 ARIMA 모형을 이용하여 모형의 식별 및 진단 방안을 제시하였다. 제시된 방법의 효과를 검증하기 위하여 주요항만인 부산항, 광양항, 인천항, 평택항의 해상교통량을 예측하였다. 그 결과로 부산항은 ARIMA 모형, 광양항은 Winters 승법 모형, 인천항은 단순계절 모형, 평택항은 ARIMA 모형이 더 적합한 모형으로 알 수 있었으며, 각 항만별 계절에 따라 월별 교통량의 차이를 보이는 것으로 분석되었다. 본 연구 결과는 향후 항로 및 항만설계 또는 해상교통 안전성 평가에 보다 신뢰성 있는 추정치를 제공할 수 있을 것으로 보인다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.249-251
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• 2013

해상교통안전에 영향을 미치는 여러 가지 해상 개발사업으로 인하여 발생할 수 있는 항해안전의 위험요인을 전문적으로 측정하고 평가하는 것으로 '해상교통안전진단제도'가 있다. 이제도의 주요 평가항목에는 해상교통 현황조사, 해상교통 현황측정, 해상 교통시스템 적정성 평가 및 해상교통 안전대책이 있다. 특히 해상교통 현황측정의 세부 항목 중에는 진단 대상 항만 또는 항로가 추정된 미래의 해상교통량을 수용할 수 있는지를 평가하고 필요 시 관련 해역의 교통 흐름을 조정할 목적으로 수행하는 해상교통혼잡도 평가 있다. 이 연구는 현재 교통혼잡도 평가를 위한 미래 해상교통량 추정기법의 문제점의 현황과 이를 개선하여 신뢰도 있는 교통량 예측이 가능한 통계기법을 개발하고자 하는 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.271-272
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• 2018

부산항 신항은 현재 21개의 선석 규모에서 2030년까지 총 40선석까지 확대할 계획을 갖고 있다. 항만의 확대에 따라 선박 통항량 증가가 예상되며, 이를 대비해 해상교통관제도 해상교통량을 기반으로 집중관제구역을 설정할 필요가 있다. 본 연구는 부산항 신항을 대상으로 해상교통위험도 모델을 이용해 위험구역을 정량화하고 집중적으로 관제가 필요한 구역을 도출하는 것을 목적으로 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.127-132
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• 2006

Maritime transportation engineering is a technical field that observes the flow of vessel's traffic in accurate and describes the feature of ship's movement statistically, then contributes to the improvement of traffic flow and the safety of traffic. The flow of marine traffic can be controlled by carrying out assessment and analysis of vessel's traffic. It can realize the safety of marine traffic by accurate research and analysis of vessel's traffic, understanding its flow and analysis data of vessel traffic. This study the analysis system of marine traffic connected with Radar, AIS based on ENC(Electronic Navigational Chart). The marine traffic analysis system contributes to safety of marine traffic through the design of marine traffic route, harbour facilities and improvement of vessel's traffic flow.

• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.43-48
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• 2007

Maritime traffic engineering is a technical field that observes the flow of vessels' traffic in accurate and describes the feature of ship's movement statistically, then contributes for the improvement of traffic flow and the safety of traffic. The flow of marine traffic can be controlled by carrying out assessment and analysis of vessel's traffic. It can realize the safety of marine traffic by accurate research and analysis of vessel's traffic, understanding its flow and analysis data of vessel traffic. This study shows the analysis system of marine traffic connected with Radar, AIS based on ENC(Electronic Navigational Chart). The marine traffic analysis system contributes to the safety of marine traffic through the design of marine traffic route, harbour facilities and improvement of vessels' traffic flow.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.381-388
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• 2018

This study proposes marine traffic volume estimation method considering ship speed, a factor excluded from the existing method. Ten days of GICOMS marine traffic data from Pyeongtaek and Dangjin ports was applied to this study. As a result, converted traffic volume with the proposed estimation method showed an increase of 4.41 (${\pm}0.99$) times or decrease of 0.59 (${\pm}0.04$) at most, compared with the existing estimation method. Average marine traffic congestion for each time applying the proposed estimation method showed an increase of 1.43 (${\pm}0.10$) compared with the existing estimation method. The maximum marine traffic congestion for each time was 1.62 (${\pm}0.34$) times higher compared with the existing estimation method. Marine traffic peak time, defined as the highest point of marine traffic congestion, was evaluated to be different from that of the existing method because of distribution of vessel speed. In conclusion, considering ship speed is necessary when estimating marine traffic volume to produce a practical estimate of marine traffic capacity.

• Proceedings of KOSOMES biannual meeting
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• 2008.05a
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• pp.173-176
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• 2008

It is very important to protect life, property at sea and marine environments from any pollution AIS, which was been carried out July 1st, 2002 by SOLAS ch. 5, is an communication system to enhance navigational safety by transmitting and receiving vessel information automatically. In this paper, we investigated the positive factors expected by introducing AIS. For this, ship's collision accidents were analyzed. Finally, we suggest methods to solve several problems related to operation in AIS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.33-41
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• 2014

Unlike the existing regression analysis, this study anticipated future marine traffic volume using time series analysis and artificial neural network model. Especially, it tried to anticipate future marine traffic volume by applying predictive value through time series analysis on artificial neural network model as an additional input variable. This study used monthly observed values of Incheon port from 1996 to 2013. In order for the verification of the forecasting of the model, value for 2013 is anticipated from the built model with observed values from 1996 to 2012 and a proper model is decided by comparing with the actual observed values. Marine traffic volume of Incheon port showed more traffic than average for May and November by 5.9 % and 4.5 % respectably, and January and August showed less traffic than average by 8.6 % and 4.7 % in 2015. Thus, it is found that Incheon port has difference in monthly traffic volume according to the season. This study can be utilized as a basis to reflect the characteristics of traffic according to the season when investigating marine traffic field observation.

• 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.