The key features of maritime accidents are the change of their attributes by new risks from time to time. To prevent maritime accidents in Korea, the impacts by new risks on domestic safety environments should be identified or predicted. The purpose of this paper is to find the hazard factors by new risks on maritime safety in Korea. The meaning of new risks is the elements of accident hazard which is compiled from new or rare or unprecedented events in the worldwide maritime transportations. The problems of new risks are the lacks of optimum countermeasures to mitigate accident risks. Using the questionnaires with 152 event scenarios classified by 20 accident causes, the hazard identification and risk analysis of new risks was performed based on the Formal Safety Assessment (FSA) by IMO. A total of 22 Influence Diagrams, which is to depict the transit flows between accident causes to consequences, is used in the construction of 152 event scenarios. A total of 20 accidents causes is the same contents as the causation factors represented in Statistical Year Book for Maritime Accidents of Korean Maritime Safety Tribunals. After defining the evaluation equations to the response results of questionnaires by 46 experts, the work for risk analysis is carried out. As results from the analysis of 152 scenarios, it is known that the root cause to affect on maritime safety in Korea is the pressure of business competition and it led to the lacks of well experienced crews, the overload of vessel operations and crew's fatigue. In addition, as results from the analysis of 20 accident causes, the three accident causes are to be candidate as main issues in Korea such as the inadequate preparedness of departure, the neglecting of watch keeping in bridge and the inadequate management of ship operations. All of the results are thought to be as basic hazard factors to safety impediments. It is thus found that the optimum Risk Control Options to remove the hazard factors and to mitigate consequences required are the following two factors: business competition and crewing problems.

본 연구는 인적오류 예방을 위해 선박 충돌위험 가능성이 높은 여섯 가지 선박조우상황(Head on, 045°, 090°, 135°, Overtaking, Overtaken)에 대해서 양 선박의 거리가 점차 감소될 때 항해 당직자가 느끼는 충돌위기체감지수(Collision Risk Perception Index, CRPI)를 획득하고 통계분석을 통하여 신뢰도분석 및 가설을 검증한 후 곡선근사과정을 통해 다항 계수로 모델링하는 것이 목적이다. 해상에서 실제 경비함 두 척과 항해당직 승조원 총 30명을 대상으로 CRPI 데이터 획득 실험을 하였으며 데이터 분석결과 각 조우상황에서 높은 신뢰도를 나타냈고 유의미한 결과를 나타냈다. 또한 타 선박 조우시 양 선박간 거리가 가까워지는 상황에서 항해당직자의 승선경력과 연령이 많고, 상위면허를 보유 할수록 CRPI에 음(-)의 영향을 미친다는 것을 알았다. 또한 3차 다항식 모델로 CRPI를 추정한 결과 평균제곱오차(RMSE)는 Head on에서 1.19, 045°에서 0.87, 090°에서 0.81, 135°에서 0.71, Overtaking에서1.29, Overtaken에서 0.87로 나타나서 CRPI 곡선근사가 유용함을 알았다.

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

선박이 발달함에 따라 국제해사기구(IMO)에서는 인적과실에 의한 해양사고 예방을 위하여 기존의 선박운항·조선기술에 ICT를 융·복합한 차세대 해상안전종합관리체계인 e-Navigation 도입을 추진 중에 있으며, 세계 각 국에서는 네트워크를 통한 원격조종시스템을 활용한 무인선박(Unmmanded vessel)의 개발이 활발하게 진행되고 있다. 무인선박은 선박-육상간 통신체계 구축을 통한 원격조종시스템과 통합 센서를 활용한 자율항해시스템을 갖춘 선박이다. 그러나 개발로 인해 예상되는 해운환경에 대한 고찰은 이루어지지 않고 있는 상황이다. 본 연구에서는 무인선박의 출현으로 예상되는 해운환경의 변화를 살펴보고 무인선박이 실제 투입되기 전 갖추어져야할 규정과 법 제도, 또한 투입 후에 수반되는 상황에 대한 대책 등을 조사하며, 가장 효과적인 무인 선박투입 시기 및 범위, 방법 등을 다루고자 한다.

This paper describes the application method of bumper area defined in the ship domain theory and it is to identify risky sectors in VTS(Vessel Traffic Services) area. The final goal of this work is to develop early warning system providing the location information with high traffic risks in Mokpo VTS area and to prevent the human errors of VTS Officer(VTSO). The current goal of this paper is to find evaluation and detection method of risky sectors. The ratio between overlapped bumper area of each vessels and the summing area of a designated sector, Ratio to Evaluate Risk(RER) r is used as one of evaluation and detection parameter. The usability of overlapped bumper area is testified through three kinds of scenarios for various traffic situations. The marine traffic data used in the experiments is collected by AIS(Automatic Identification System) receiver and then compiled in the SQL(Structured Query Language) Server. Through the analysis of passing vessel‘s tracks within the boundary of Mokpo VTS area, the total of 11 sectors are identified as evaluation unit sector. As experiment results from risk evaluation for the 11 sectors, it is clearly known that the proposed method with RER r can provide the location information of high risky sectors which are need to keep traffic tracks of vessel movements and to maintain traffic monitoring by VTSO.