• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.2
• /
• pp.113-118
• /
• 2017

Various studies on the method of ship collision risk assessment for alarm have been reported constantly, and the result of the studies is applied to navigation devices. However, it is known that navigators ignore or turn off frequent alarms from the devices of predicting collision risk, because they may avoid collisions in the most of situations. In oder to make the prediction of ship collision risk more useful, it is necessary to consider the customary actions of ship collision avoidance. This paper proposes a system of analyzing collision avoidance measures of ships according to the types of encounter and managing the avoidance history of each ship. The core module of the system is designed as a neuro-fuzzy based inference system, and the test of the module validates the proposed system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2010.10a
• /
• pp.180-181
• /
• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2004.11a
• /
• pp.73-80
• /
• 2004

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out if them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability if casualty. In this study, the risk of collision is evaluated by two kinds if method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk if collision is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.3B
• /
• pp.248-253
• /
• 2011

Collision avoidance algorithm of vessels have been studied to avoid collision and grounding of a vessel due to human error. In this paper, We propose a collision avoidance algorithm using bayesian estimation theory for safety sailing and reduced risk of collision accident. We calculate collision risk for efficient collision avoidance using bayesian algorithm and determined the safest and most effective collision risk is predicted by using re-planned with re-evaluated collision risk in the future(t=t'). Others ship position is assumed to be informed from AIS. Experimental results show that we estimate the safest and most effective collision risk.

• Journal of Navigation and Port Research
• /
• v.32 no.6
• /
• pp.447-452
• /
• 2008

In this paper, the automatic depth control system and the collision avoidance system of the Manta UUV have been established in vertical and horizontal plane. The PID control theory and the Fuzzy theory are adopted in this system. The 6-DOF MMG model had been established by theoretical calculations and captive model test results. The depth control simulation results have been fully presented. The collision risks of the UUV had calculated by the fuzzy theory with the virtual sonar system. Finally, the automatic depth control system and the collision avoidance simulation system of Manta UUV have been fully developed and simulated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2009.10a
• /
• pp.62-63
• /
• 2009

A monitoring system of collision risk among multiple ships is newly-designed in order to reduce human error and make vessel traffic control more effective. By using AIS data as ships' navigational information, an estimation algorithm of collision risk among multiple ships is newly-designed. To consider ships' course of now and future, collision risks of multiple ships can be calculated by using fuzzy algorithm. To test the performance of new algorithm, replay simulations are carried out on actual AIS data collected from VTS center of Ulsan harbor in Korea. The AIS data include 25 ships' information for two hours. In this paper, the features of newly-designed estimation algorithm of collision risk and the results of replay simulation are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2011.06a
• /
• pp.164-166
• /
• 2011

기존 연구에서 다중선박의 충돌위험도를 추정하는 알고리즘을 개발한 바 있다. 본 연구에서는 이를 기반으로, 실제 선박에 온보드형으로 설치하여, 운용할 수 있도록 전자해도 기반의 충돌위험도 표시 시스템을 설계하고, 그 표시 프로그램을 구현하였다. 국립해양조사원에서 배포하는 전자해도(IHO S-57) 파일을 이용할 수 있으며, 실시간으로 입력되는 해상교통 정보를 받아 충돌위험도를 계산하여, 표시할 수 있도록 구성하였다. 그리고, 개발된 프로그램의 성능을 검증하기 위하여, 선박운항 시뮬레이터를 이용하여, 실제 선박충돌사고의 AIS 데이터를 이용한 재생시뮬레이션을 수행하였다.

• Journal of Broadcast Engineering
• /
• v.20 no.3
• /
• pp.440-448
• /
• 2015

A pedestrian collision warning system which makes a judgement of pedestrian's intention to help avoiding hitting accidents is proposed. This system uses the image sequences obtained from a car black box as well as vehicle's speed obtained from a GPS. It detects pedestrians, if any, based on the Histogram of Gradient method and extracts several information such as the pedestrian's relative positions, the direction of motion vectors, and distance between vehicle and pedestrian . A fuzzy logic based on these extracted information is applied to analyze the pedestrian's safety levels. When the safety level is determined to be danger, an alarm is triggered to the driver. The performance of the proposed algorithm is tested under various driving scenarios, which shows it works successfully in real-time.

• Journal of Navigation and Port Research
• /
• v.26 no.1
• /
• pp.8-14
• /
• 2002

The collisions of vessel at sea show high among the whole marine accidents. Especially, the accidents of fishing vessels take the largest portion of the collisions. Therefore, a technique to reduce these accidents should be developed. The automatic control for avoiding collision suggested in this study consists of two steps. The first is recognizing collision risk with fuzzy Theory and the other is maneuvering the model ship on the basis of collision risk calculated from the first step. The information form the position and estimated time of collision point(DCPA and TCPA) is used to assess the collision risk. To verify this system, a fishing vessel was simulated according to MMG mathematical model. The simulations result shows quite good application in avoiding the collision of ship.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.12 no.1
• /
• pp.15-22
• /
• 2009

Auto-navigation algorithm have been studied to avoid collision and grounding of a ship due to human error. There have been many research on collision avoidance algorithms but they have been validated little on the real coastal traffic situation. In this study, a Collision Avoidance algorithm is developed by using Fuzzy algorithm and the concept of Changeable Action Space Searching (CAS). In the first step, on a basis of collision risk calculated from fuzzy algorithm in the current time(t=to), alternative Action Space for collision avoidance is planned. In the second step, next alternative Action Space for collision avoidance in the future($t=to+{\Delta}t$) is corrected and re-planned with re-evaluated collision risk. In the third step, the safest and most effective course among Action Space is selected by using optimization method in real time. In this paper, the main features of the developed collision avoidance algorithm (CAS) are introduced. CAS is implemented in the ship-handling simulator of MOERI. The performance of CAS is tested on the situation of open sea with 3 traffic ships, whose position is assumed to be informed from AIS. Own-ship is fully autonomously navigated by autopilot including the collision avoidance algorithm, CAS. Experimental results show that own-ship can successfully avoid the collision against traffic ships and the calculated courses from CAS are reasonable.