• Journal of the Korea Society for Simulation
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• v.8 no.4
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• pp.61-72
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• 1999

This paper presents an estimation method of container handling capacity and selection of resource allocation strategies of container terminals using the computer simulation models. Simulation models are developed to model container terminal consisting of 4 berths considering the berth allocation strategies, crane allocation strategies and the total number of container cranes using Arena simulation package. The proposed models do not consider the yard operations and gate operations. All the input parameters for the models are estimated on the basis of the existing container terminal operation data and the planning data for the automated container terminal planned by Korean government. Four berth allocation strategies and three crane allocation strategies are considered. The total number of container cranes considered ranges from 12 to 15. Non-terminating simulation techniques are utilized for the performance comparison among alternatives. The performance measures such as average ship turnaround time, average ship waiting time, average ship service time, the number of containers handled per year, and the number of ships processed per year are used. The result shows that the berth allocation strategy minimizing the sum of the number of ships waiting, the number of busy container cranes and number of ships handled performs better than any other berth allocation strategies. In addition, the crane allocation strategy allocating up to 5 container cranes per berth performs better than any other crane allocation strategies. Finally there are no significant performance differences among the alternatives consisting of different total number of container cranes allocated.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.303-312
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• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.195-202
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• 2020

The production of larger of ships is a survival strategy for global shipping companies to pursue the economics of scale. According to this strategy, to respond to this situation, many containers are loading/unloading simultaneously in the hub port. Additionally, the container terminals are promoting the introduction of automation to expand the terminal facilities and increase efficiency/productivity of the container yards. European ports have introduced automation to address rising labor costs and shortages of labor. Recently, the construction of fully automated container terminals is increasing in the United States and China to resolve problems such as the slow growth of the global economy, the emergence of large ships, air pollution, and safety accidents. Domestic ports are at an early stage compared to the world's advanced container terminals, and countermeasures are being prepared to respond to the changing ports. However, research on the recognition difference analysis that examines the opinions of stakeholders is insufficient. As a result of analyzing the recognition among the groups, it was found that container terminal operators reduced labor costs, improved shipping services for shipping companies, prevented safety accidents for port union labor, and increased service for port authority and government agencies. Thus, to closely examine the perception among the groups, one-way ANOVA was performed, and then the implications were deduced as the basic data for the smooth introduction of automation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.223-230
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• 2004

In this paper, we will introduce a control strategy based on the permanent magnet linear synchronous motor (PMLSM) container transfer system using soft-computing algorithm. Linear motor-based container transport system (LMCTS) is horizontal transfer system for the yard automation, which has been proposed to take the place of automated guided vehicle in the maritime container terminal. LMCTS is considered as that the system is changed its model suddenly and variously by loading and unloading container. The proposed control system is consisted of two DR-FNNs that act the role of controller and system emulator. Consequently, the system had the predictable structure and an ability to adapt for a huge variation of rolling friction, detent force, and sudden changes of its weight by loading and unloading.

• Journal of Information Technology and Architecture
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• v.9 no.1
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• pp.1-10
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• 2012

To promote process effectiveness and efficiency, it is necessary that port logistics employ automated equipments for handling containers. There exists a system for automatically managing the container flow, called Control Module. However, it has limitation to assign the execution order to the machine and monitor the container flow in real time process. Business process management (BPM) provides a suitable and effective framework to address this problem including controlling and monitoring the flow of each container. Since the nature of container handling process is different with the common process in BPM that is conducted by human performer, it is necessary to adjust the BPM framework in the domain of port logistic management. This study presents a BPM framework corresponds with both human-based and machine-based activity to enhance the efficiency of port process flow including container flow. This framework is introduced as an integrated approach and mechanism of BPM application into the container handling system for the purpose of port logistics process automation.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.510-517
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• 2005

In this paper, an open architecture control system for automated container cranes is investigated. The hardware architecture for automating cranes is first discussed. A standard reference model for cranes based upon the OSACA platform is proposed, in which three modules are suggested: hardware module, operating system module, and application software module. Finally, a hybrid control system combining deliberative and reactive controls for autonomous operations of the cranes is implemented.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.459-464
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• 2004

In this paper, an autonomous navigation system for autonomous guided vehicles (AGVs) operated in an automated container terminal is designed. The navigation system is based on the sensors detecting the range and bearing. The navigation algorithm used is an interacting multiple model (IMM) algorithm to detect other AGVs and avoid other obstacles using informations obtained from multiple sensors. As models to detect other AGVs (or obstacles), two kinematic models are derived： Constant velocity model for linear motion and constant speed turn model for curvilinear motion. For constant speed turn model, an unscented Kalman filter (UKF) is used because of drawbacks of the extended Kalman filter (EKF) in nonlinear system. The suggested algorithm reduces the root mean squares error for linear motions, while it can rapidly detect possible turning motions.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.653-657
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• 2005

AGV is very useful equipment to transfer containers in automated container terminal. AGV must have Obstacle Detection System (ODS) for port automation. ODS needs the function to classify some specified object from background in acquired data. And it must be able to track classified moving objects. Finally, ODS could determine its next action for safe driving whether it should do emergency stop or speed down, or it should change its deriving lane. For these functions, ODS can have many different kinds of algorithm. In this paper, we present one of AGV to be used in automated container terminal.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.315-320
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• 1999

Obstacle Detection System(ODS) is a essential system for automated vehicle, such as AGV(Automatic Guided Vehicle), mobile robot. Automated vehicle must have a capability to detect and to avoid obstacles to guarantee a safe driving condition. To implement obstacle detection system, virtual bumper concept adapted. Like real bumper in a car, such as in the truck, it protects vehicle from collision using laser distance sensor. When an obstacle(such as other vehicle, building, etc) intrudes this virtual bumper area, a virtual force is calculated and produces necessary strategy to be able to avoid collision. In this paper, simplified virtual bumper concept is presented, and various problems when happens to implement are discussed.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.