• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.259-276
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• 2010

This study shows how Incheon will advance into roadmap as multi-transport hub in Northeast Asia hereafter and be proposed an urgent tasks and roles to construct a multi-transportation system for Incheon, which has both an international airport and port. The multi-transportation point of view of inter-major cities competitiveness of total scores was proposed 1. Shanghai(64.8 points), 2 in Hongkong(64.5), 3 in Incheon(62.9), and 4 in Busan(60.4) and Incheon was estimated to have enough competitiveness to be the international multi-transport hub in Northeast Asia. Sea & Air transportation revealed the most important multi-transportation in the Incheon region. In conclusion, this research suggests a development plan for multi-transportation in Incheon. Firstly, it proposes construction of sea & air transportation distribution center and agreement that simplifies logistic process between Incheon and Tianjin, secondly, suggests to activate project for the purpose of creating a better sea-land transportation system between Incheon and Shanghai.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4125-4133
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• 2023

The transportation of spent nuclear fuel is an important process that involves road and sea transport from an interim storage facility to storage and final disposal sites. As spent nuclear fuel poses a significant risk, carefully evaluating its vibration and shock characteristics under normal transport conditions is essential. In this regard, full-scale multi-modal transport tests (MMTT) have been conducted domestically and internationally. In this paper, we discuss the process of developing a multi-body dynamics (MBD) model to analytically simulate conditions that cannot be considered in tests. The MBD model is based on the KORAD-21 transportation system was validated using the Korean MMTT results from 2020 to 2021. This paper summarizes the details of the development and verification of the MBD model for the KORAD-21 transportation system under normal transport test conditions. This approach can be applicable to various transportation scenarios and systems, and the results of this study will help to ensure that nuclear fuel transportation is conducted safely and effectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.36-45
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• 1993

This paper presents a model and a heuristic procedure to design production planning and transportation scheduling systems of critical items, components and products on the basis of material requirement planning concept and transportation planning model. These systems are stemmed from a multi-site multi-product production company in a international economic zone. An example is provided to validate the heuristic procedure developed.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Advances in robotics research
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• v.1 no.2
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• pp.171-183
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• 2014

Distributed planning and decision making can be beneficial from the robustness, adaptability and fault tolerance in multi-robot systems. Distributed mechanisms have not been employed in three dimensional transportation systems namely aerial and underwater environments. This paper presents a distributed cooperation mechanism on multi robot transportation problem in three dimensional environments. The cooperation mechanism is based on artificial capital market, a newly introduced market based negotiation protocol. In the proposed mechanism contributing in transportation task is defined as asset. Each robot is considered as an investor who decides if he is going to invest on some assets. The decision is made based on environmental constraint including fuel limitation and distances those are modeled as capital and cost. Simulations show effectiveness of the algorithm in terms of robustness, speed and adaptability.

• Journal of Navigation and Port Research
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• v.33 no.4
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• pp.271-275
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• 2009

A strategic decision making on location selection for product transportation includes many tangible and untangible factors. To choose the best locations is a difficult job in the sense that objectives usually conflict with each other. In this paper, we consider a multi stage multi criteria transshipment problem with different types of items to be transported from the sources to the destination points. For the optimization of the problem, a goal programming formulation will be presented in which the location selection for each product type will be determined under the multi objective criteria. In the study, we generalize the transshipment model with a variety of product types and finite number of different intermediate nodes between origins and destinations. For the selection of the criteria we selected the costs(fixed cost and transportation cost), location numbers, and unsatisfied demand for each type of products in multi stage transportation, which are the main goals in transshipment modelling problems. The related conditions are also modelled through linear formats.

• Advances in robotics research
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• v.2 no.3
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• pp.247-257
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• 2018

Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.

• Transportation Technology and Policy
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• v.9 no.4
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• pp.53-58
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• 2012

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.