• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.7-11
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• 2004

Maritime safety and marine environmental protection are the most important topic in marine society. But, so many marine accidents rave been occurred with the development of marine transportation industry. On the other side, ship is being operated under a highly dynamic environment and many factors are related with ship's collision Nowadays, the increasing tendency to the human errors of ship's collision is remarkable, and the investigation of the human errors has been heavily concentrated. This study analysed on the human errors of ship's collision related to the negligence of lookout and classified basic error type using GEMS(Generic Error Modeling System) dynamic model.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.295-307
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• 2007

The statistics of Korean Maritime Safety Tribunal and Japan Marine Accidents Inquiry Agency shows that the major muses of collision at sea are Improper lookout and Non-compliance with marine traffic rules. Those two muses are occupying more than 70% of collision, and it's clear that those muses are undoubtedly closely related to simple human error. In this paper we tried to find out the root muses of this kind of human error of OOWs(officers on watch) through risk identification method and studied how to tackle them via risk control theory. In conclusion, the measures studied in this paper could be applied to help OOWs avoid their own human error as well as be used in shipping company for their fleets' safety management.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.19-29
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• 2019

Recently, autonomous vehicles have been studied actively. Autonomous vehicles can detect objects around them using their on board sensors, estimate collision probability and maneuver to avoid colliding with objects. Many algorithms are suggested to prevent collision avoidance. However there are limitations of complex and diverse environments because algorithm uses only the information of attached environmental sensors and mainly depends on TTC (time-to-Collision) parameter. In this paper, autonomous driving algorithm using I2V communication-based cooperative sensing information is developed to cope with complex and diverse environments through sensor fusion of objects information from infrastructure camera and object information from equipped sensors. The cooperative sensing based autonomous driving algorithm is implemented in autonomous shuttle bus and the proposed algorithm proved to be able to improve the autonomous navigation technology effectively.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.295-300
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• 2012

Various forward collision warning algorithms have studied in order to protect a car accident. For this, in general, algorithms using an external device such as a camera and sensor generate a forward collision warning. However, if using the external device, it can occur errors due to device characteristics when there is rain or fog. Also, the prevention of a chain-reaction collision is insufficient because the system generates a warning in case of only vehicle having a forward collision danger. If it combines the vehicle safety communications, the method becomes a solution to protect a chain-reaction collision. So, In this paper, we proposes a improved forward collision warning algorithm using the wireless communication technique, driver's information, breaking distance, and velocity. And we compare and analyze our algorithm and previous algorithms.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.346-351
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• 2018

The proportion of collision in the total marine accidents is high. The main causes of collisions are navigation rule violation, safety speed violation, neglected watch-keeping and improper collision avoidance action. There are two main ways of avoiding collision situations during maritime navigation: the method of altering course and reducing ship's speed. The purpose of this study is to analyze the result of the collision avoidance action of the reserve officer in case of encountering a multiple number of ships using the ship handling simulator. Full-mission ship handling simulator was used to experiment the situation scenarios that encountered multiple ships. After the experiment, the questionnaire about the experiment was investigated. A total of 50 subjects were participated in the experiment. Experimental results showed that the number of the experimenters who used the engine was 11 and the number of the experimenters who did not use the engine was 39. In the case of using the engine, there were 0 collision accident, 1 grounding accident, and 10 no accidents. However, when the engine was not used, there were 28 collision accidents, 2 grounding accidents, and 9 no accidents. The causes of these results can be found in the survey results. 74 % of the non used engine participants said they were hesitate to use the engine. As can be seen from these results, the reserve officer are hesitant to use the engine and need a way to get correct of it. Maritime course subject can emphasize the importance of using ship's engines and case study also can be it. So, It is considered that various case study scenario will need to developed by various tools in the future.

• Proceedings of KOSOMES biannual meeting
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• 2003.05a
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• pp.59-67
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• 2003

The prevention of marine accidents has been a major topic in marine society for long time and various safety policies and Countermeasures have been developed and applied to prevent those accidents. In spite of these efforts, however significant marine accidents have taken place intermittently. Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, the analysis on ship's collision causes are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that ‘ship's collision’ is occurred most frequently and the cause is closely related with human factor. The main purpose of this study is to propose risk control countermeasures of ship's collision. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision. FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the causes of ship's collision using FSM are performed. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and reduce marine accidents.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.175-183
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• 2022

The collision between a ship and bridge across a waterway may result in extremely serious consequences that may endanger the safety of life and property. Therefore, factors affecting ship bridge collision must be investigated, and the impact force should be discussed based on various collision conditions. In this study, a finite element model of ship bridge collision is established, and the peak impact force of a ship bridge collision based on 50 operating conditions combined with three input parameters, i.e., ship loading condition, ship speed, and ship bridge collision angle, is calculated via numerical simulation. Using neural network models trained with the numerical simulation results, the prediction model of the peak impact force of ship bridge collision involving an extremely short calculation time on the order of milliseconds is established. The neural network models used in this study are the basic backpropagation neural network model and Elman neural network model, which can manage temporal information. The accuracy of the neural network models is verified using 10 test samples based on the operating conditions. Results of a verification test show that the Elman neural network model performs better than the backpropagation neural network model, with a mean relative error of 4.566% and relative errors of less than 5% in 8 among 10 test cases. The trained neural network can yield a reliable ship bridge collision force instantaneously only when the required parameters are specified and a nonlinear finite element solution process is not required. The proposed model can be used to predict whether a catastrophic collision will occur during ship navigation, and thus hence the safety of crew operating the ship.

• Journal of the Korea Safety Management & Science
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• v.20 no.2
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• pp.1-8
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• 2018

This study aims to provide a real-time information to the driver by effectively operating the advanced safety device attached to the freight vehicle, thereby minimizing insecure behavior of the driver such as speeding, rapid acceleration, sudden braking, And improve driving habits to prevent accidents and save energy. Advanced safety equipment is a device that warns the driver that the vehicle leaves the driving lane regardless of the intention of the driver and reduces the risk of traffic accidents by mitigating or avoiding collision by detecting a frontal collision during driving.The main contents of this report are as follows: In case of installing a warning device on a lane departing vehicle (excluding a light vehicle) and a lorry or special vehicle with a total weight exceeding 3.5 tonnes, the driver must continue to operate unless the driver releases the function.In addition, when the automatic emergency braking system is installed, the structure should be such that the braking device is operated automatically after warning the driver when the risk of collision with the running or stopped vehicle in the same direction is detected in front of the driving lane.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.157-162
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• 2008

The ship's maneuverability is the important factor to avoid ship's collisions. The ship's maneuverability is usually measured in a deep water, and the turning ability is decreased and the course stability is improved in a shallow water. The variation of the turning ability could cause the risk of collision. In this paper, we proposes application technique of Variable Safe-Guard Ring to consider the shallow water effect and to be simple to estimate the grade of collision risk simultaneously. Through the mathematical simulation, the availability of new method was varified. Therefore this method is expected enough to support a maneuver for collision avoidance.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.17-23
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• 2013

This paper describes an algorithm for Advanced Emergency Braking(AEB) with tire-road friction coefficient estimation. The AEB is a system to avoid a collision or mitigate a collision impact by decelerating the car automatically when forward collision is imminent. Typical AEB system is operated by Time-to-collision(TTC), which considers only relative velocity and clearance from control vehicle to preceding vehicle. AEB operation by TTC has a limit that tire-road friction coefficient is not considered. In this paper, Tire-road friction coefficient is also considered to achieve more safe operation of AEB. Interacting Multiple Model method(IMM) is used for Tire-road friction coefficient estimation. The AEB algorithm consists of friction coefficient estimator and upper level controller and lower level controller. The numerical simulation has been conducted to demonstrate the control performance of the proposed AEB algorithm. The simulation study has been conducted with a closed-loop driver-controller-vehicle system using using MATLAB-Simulink software and CarSim Vehicle model.