• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.133-138
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• 2015

This paper presents a modified task structure of coupled-constraints consensus based bundle algorithm especially to resolve the cooperative transportation problem. The cooperative transportation mission has various types of constraints. A modified framework to generate activities and subtasks to solve time and task constraints of the transportation mission by using coupled-constraints consensus based bundle algorithm is suggested. In this paper modifications on task structure, reward function and arrival time calculation are suggested to handle the constraints of cooperative transportation mission.

• Journal of Mechanical Science and Technology
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• v.19 no.9
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• pp.1720-1730
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• 2005

Automatic guided vehicle in the factory has an important role to advance the flexible manufacturing system. In this paper, we propose a novel object-transportation control algorithm of cooperative AGV systems to apply decentralized control to multiple AGV systems. Each AGV system is under nonholonomic constraints and conveys a common object-transportation in a horizontal plain. Moreover it is shown that cooperative robot systems ensure stability and the velocities of augmented systems convergence to a scaled multiple of each desired velocity field for cooperative AGV systems. Finally, the application of proposed virtual passivity-based decentralized control algorithm via system augmentation is applied to trace a circle. Finally, the simulation and experimental results for the object-transportation by two AGV systems illustrates the validity of the proposed virtual-passivity decentralized control algorithm.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.391-393
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• 2005

Automatic guided vehicle(AGV) in the factory has an important role to advance the flexible manufacturing system. In this paper, we propose a novel object-transportation control algorithm of cooperative AGV systems to apply decentralized control scheme based on virtual-passivity. It is shown that the cooperative AGV systems ensure stability and the convergence to scaled multiple of each desired velocity field for multiple AGV systems. Finally, the application of proposed virtual passivity-based decentralized control algorithm via system augmentation is applied to be the tracking a circle. Also. the simulation results for the object-transportation by two AGV systems illustrate the validity of the proposed control scheme.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.6
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• pp.261-263
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• 2006

Automatic guided vehicle(AGV) in the factory has an important role to advance the flexible manufacturing system. In this paper, we propose a novel object-transportation control algorithm of cooperative AGV systems to apply decentralized control scheme based on virtual-passivity. It is shown that the cooperative AGV systems ensure stability and the convergence to scaled multiple of each desired velocity field for multiple AGV systems. Finally, the application of p reposed virtual passivity-based decentralized control algorithm via system augmentation is applied to be the tracking a circle. Also, the simulation results for the object-transportation by two AGV systems illustrate the validity of the proposed control scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.62-77
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• 2022

A cooperative driving automation system is imperative to overcome the limitation of the stand-alone automated driving technology. By definition, a cooperative driving automation system refers to a technology in which an automated vehicle cooperates with other vehicles or infrastructure to increase driving efficiency and safety. Specifically, in this study, the technical elements necessary for the cooperative driving automation technology and the technological research trends were investigated. Subsequently, implications for future cooperative driving automation technology development were drawn through the research trends. Finally, the importance of cooperative driving automation technology and infra-guidance service for automated vehicles were discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.258-272
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• 2022

The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.

• Transportation Technology and Policy
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• v.11 no.5
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• pp.72-77
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• 2014

• Korean Management Science Review
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• v.27 no.3
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• pp.15-31
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• 2010

We consider a reverse logistics network design problem for recycling. The problem consists of three stages of transportation. In the first stage products are transported from retrieval centers to disassembly centers. In the second stage disassembled modules are transported from disassembly centers to processing centers. Finally, in the third stage modules are transported from either processing centers or a supplier to a manufacturer, a recycling site, or a disposal site. The objective is to design a network which minimizes the total transportation cost. We design a cooperative coevolutionary algorithm to solve the problem. First, the problem is decomposed into three subproblems each of which corresponds to a stage of transportation. For subproblems 1 and 2, a population of chromosomes is constructed. Each chromosome in the population is coded as a permutation of integers and an algorithm which decodes a chromosome is suggested. For subproblem 3, an heuristic algorithm is utilized. Then, a performance evaluation procedure is suggested which combines the chromosomes from each of two populations and the heuristic algorithm for subproblem 3. An experiment was carried out using test problems. The experiments showed that the cooperative coevolutionary algorithm generally tends to show better performances than the previous genetic algorithm as the problem size gets larger.

• Transportation Technology and Policy
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• v.12 no.1
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• pp.83-92
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• 2015

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.81-93
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• 2011

This research deals with the multi-modal continuous network design problem to resolve the transportation policy problems for constructing and operating transportation facilities with considering the mutual decision-making process between transportation operator and user in the multi-modal network. Particularly, in the consideration of changes in travel pattern between transport modes due to the changes in transportation policy, road network for passenger car and transit network for public transportation are considered together. In the development of network design model, more rational Stackelberg equilibrium(cooperative game) rather than more general Nash equilibrium(non-cooperative game) approach is used and sensitivity analysis considering transport mode is used. A multi-modal continuous network design model in this study is developed for the arbitrary continuous network design parameters(${\epsilon},\hat{\epsilon},p$) of transportation policy decisions. As examples of application and evaluation for these design parameters, the developed model is applied to calculate 1)the optimal capacity of road link in the road transport policy, 2)the optimal frequency of transit line in public transport policy and 3)the optimal modal split in transport modal share policy.