Maritime autonomous surface ships (MASS) has been developed over the years. But, there are many unresolved problems. To overcome these problems, this study proposes connected ship navigation system. The system comprises a slave ship and a master ship that leads the slave ship. To implement this system, communication network, route planning algorithms, and controllers are designed. The communication network is built using the transmission control protocol/Internet protocol (TCP/ IP) socket communication method to exchange data between ships. The route planning algorithms calculate the course and distance of the slave ship using the middle latitude sailing method. Nomoto model is used as the mathematical model of the slave ship maneuvering motion. Then, the autoregressive with exogenous variables (ARX) model is used to estimate the parameters of Nomoto model. Based on the above model, the automatic steering controller is designed using a proportional-derivative (PD) control. Also, the speed controller is designed for the slave ship to maintain constant distance from the master ship. Sea experiments are conducted to verify the proposed system with two remodeled boats.

선박의 조종운동특성은 선종뿐만 아니라 같은 선박이라 할지라도 속도나 흘수에 의해서도 달라진다. 최근에 초대형선박이 크게 증가하고 있어 해양사고 발생 시 막대한 물적, 환경적 피해가 발생할 수 있으며, 이에 따라 선박조종의 중요성은 더욱 커지고 있다. IMO는 STCW 95 개정협약서를 통해서 해기사들이 시뮬레이터를 이용한 교육을 받도록 강제하고 있다. 그러나 Full Mission Ship Handling Simulator(FMSS)는 고가일 뿐만 아니라 사용하는 데에 제한이 많고, PC기반의 시뮬레이터는 서로 다른 사용자가 함께 시뮬레이션을 할 수 없다는 단점이 존재한다. 본 연구는 네트워크를 기반으로 두 사람이 각자의 PC를 이용하여 함께 시뮬레이션을 할 수 있도록 하여 FMSS와 PC기반의 시뮬레이터가 갖는 단점을 해결하고자 Nomoto 응답모델의 해석 및 수치계산과 레이더 기능 구현, 데이터통신 프로토콜 설계, Graphic User Interface(GUI) 구축 등을 통해 네트워크 기반의 시뮬레이터를 구현하였다. 그리고 개발된 시뮬레이터의 유효성을 검증하기 위해 한국선급, IMO의 선박조종성기준에 따라 시뮬레이션 결과와 한국해양대학교 한바다호의 실선시험결과를 비교·분석하였다. 항목별 시험결 과를 정리하면 상대오차 범위는 0∼32.1%, 평균 13.7% 이었으며, IMO 선박조종성기준을 모두 만족하였다.

In this paper new enhanced post-process predicting the speaker's intention was suggested to implement the real-time control module for ship's autopilot using speech recognition algorithm. The parameter was developed to predict the likeliest wheel order based on the previous order and expected to increase the recognition rate more than pre-recognition process depending on the universal speech recognition algorithms. The values of parameter were assessed by five certified deck officers being good at conning vessel. And the entire wheel order recognition process were programmed to TMS320C5416 DSP so that the system could recognize the speaker's orders and control the autopilot in real-time. We conducted some experiments to verify the usefulness of suggested module. As a result, we have confirmed that the post-recognition process module could make good enough accuracy in recognition capabilities to realize the autopilot being operated by the speech recognition system.

Usually marine traffic survey has been conducted by some methods like an ocular observation using portable RADAR, a questionnaire, etc. But these should have expended a lot of manpower and expenses. In this paper, we have developed new observation module which could capture the RADAR image using PC camera simply, and allowed as to track targets on the PC monitor directly. And it has been programmed to make a database of RADAR image, target's track and information, and analyze the marine traffic tendency in various ways like vessel number crossed over gate line, vessel's velocity distribution in gate line, traffic density distribution, etc. We have confirmed that this module could observe and analyze the marine traffic efficiently and economically through several on-the-spot experiments.