• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.43-55
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• 2002

Vessel traffic safety management means the managerial technical measures for improving the marine traffic safety in general terms. The main flow of vessel traffic safety management is that: 1) Traffic Survey, 2) Replay by Marine Traffic Flow Simulation, 3) Quantitative Assessment, 4) Policy Alternatives, 5) Prediction·Verification. In the management of vessel traffic safety, it is most important to establish assessment models that can numerically estimate the current safety level and quantitatively predict the correlation between the measures to be taken and the improvement of safety and the reduction of ship handling difficulties imposed on mariners. In this paper, the replay model for traffic flow simulation was made using marine traffic survey data, and the present traffic situation became replay in the computer. An attempt was made to rate the current safety of ports and waterways by applying the Environmental Stress model. And, as a countermeasure for traffic management, by taking of, the promotion of total traffic congestion in early morning rush hour, the correlation between traffic control rate and the reduction in ship handling difficulties imposed on mariners was predicted quantitatively.

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

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 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.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.135-142
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• 2016

When video service is performed in simulation using NS-2(Network Simulation-2), the video replay is performed as the received frame order. In the existing video replay method based on the received frame order, as the frame orders of receiver and transmitter are different, the receiver buffer does not have the effect that the packets between the frames of transmitter buffer holds a regular size and packet dense and sparsity phenomenon in the receiver buffer is made by the irregular packet size due to the unpredictable reversed order of received partial frames. The above dense and sparsity phenomenon increases the probability of buffer overflow and underflow generation. To prevent these problems, the proposed frame receive order relocation method adds an extra replay buffer which rearranges the order of receive frame as the order of transmit frame, so it has the effect that the packets between the transmit frames keeps a regular size. Through the simulation using NS-2 and JSVM(Joint Scalable Video Model), the generation number of buffer overflow and underflow, and PSNR(Required Peak Signal to Noise Ratio) performance between the existing method and proposed method were compared. As a result, it was found that the proposed method would have better performance than the existing method.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.365-371
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• 2015

In wireless network, the amount of video streaming packet information in receiver replay buffer can be varied according tothe wireless network condition. By the effect, unforeseeable delay and jitter are generated and then busty video traffics can be made. If the amount of buffer information coming in receiver replay buffer is larger than the amount of a specific buffer information, buffer overflow is generated. Such a problem makes the image skip effect and packet loss, and then causes the quality degradation and replay discontinuity of the video streaming service in destination receiver. To solve the buffer overflow problem, this paper applies the token bucket for the busty traffic to the receiver terminal and analyzes the effect of the token bucket. The simulation result using NS-2 and JSVM shows that the proposed scheme with the token bucket has significantly better performance than the conventional scheme without the token bucket in terms of overflow generation number, packet loss rate and PSNR.

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

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.157-162
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• 2019

The video game Tetris is one of most popular game and it is well known that its game rule can be modelled as MDP (Markov Decision Process). This paper presents a DQN (Deep Q-Network) based game agent for Tetris game. To this end, the state is defined as the captured image of the Tetris game board and the reward is designed as a function of cleared lines by the game agent. The action is defined as left, right, rotate, drop, and their finite number of combinations. In addition to this, PER (Prioritized Experience Replay) is employed in order to enhance learning performance. To train the network more than 500000 episodes are used. The game agent employs the trained network to make a decision. The performance of the developed algorithm is validated via not only simulation but also real Tetris robot agent which is made of a camera, two Arduinos, 4 servo motors, and artificial fingers by 3D printing.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.7 s.262
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• pp.747-755
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• 2007

To improve the reality of motion simulator, the method of data-driven motion generation has been introduced to simply record and replay the motion of real vehicles. We can achieve high quality of reality from real samples, but it has no interactions between users and simulations. However, in character animation, user controllable motions are generated by the database made up of motion capture signals and appropriate control algorithms. In this study, as a tool for the interactive data-driven driving simulator, we proposed a new motion generation method. We sample the motion data from a real vehicle, transform the data into the appropriate data structure(motion block), and store a series of them into a database. While simulation, our system searches and synthesizes optimal motion blocks from database and generates motion stream reflecting current simulation conditions and parameterized user demands. We demonstrate the value of the proposed method through experiments with the integrated motion platform system.

• The Magazine of the IEIE
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• v.30 no.9
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• pp.1002-1011
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• 2003

In this paper, we introduce an integrated SoC front-end design & verification environment which can be practically used in the embedded 32-bit processor-core SoC VLSI design. Our introduced SoC design & verification environment integrates two most important flows, such as the RTL power estimation and code coverage analysis, with the functional verification (chip validation) flow which is used in the conventional simulation-based design. For this, we developed two simulation-based inhouse tools, RTL power estimator and code coverage analyzer, and used them to adopt them to our RTL design and to increase the design quality of that. Our integrated design environment also includes basic design and verification flows such as the gate-level functional verification with back annotation information and test vector capture & replay environment.