• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.361-366
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• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.99-110
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• 2005

Total travel cost of route which connects origin with destination (O-D) is consist of the total sum of link travel cost and route perception cost. If the link perception cost is different according to the origin and destination, optimal route search has limitation to reflect the actual condition by route enumeration problem. The purpose of this study is to propose optimal route searching formulation and algorithm which is enable to reflect different link perception cost by each route, not only avoid the enumeration problem between origin and destination. This method defines minimum unit of route as a link and finally compares routes using link unit costs. The proposed method considers the perception travel cost at both origin and destination in optimal route searching process, while conventional models refect the perception cost only at origin. However this two-way searching algorithm is still not able to guarantee optimum solution. To overcome this problem, this study proposed an orign based optimal route searching method which was developed based on destination based optimal perception route tree. This study investigates whether proposed numerical formulas and algorithms are able to reflect route perception behavior reflected the feature of origin and destination in a real traffic network by the example research including the diversity of route information for the surrounding area and the perception cost for the road hierarchy.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.745-752
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• 2002

A* algorithm is widely used in optimal car route search which is a kind of informed search, since the locations of starting and ending points are known a priori. Unidirectional A* algorithm requires considerable search time but guarantees a optimal path, bidirectional A* algorithm does not guarantee a optimal path and takes even longer search time than unidirectional search to guarantee a optimal path. In this paper, a new bidirectional A* algorithm which requites less search time and guarantees a optimal path is proposed. To evaluate the efficiency of the proposed algorithm, several experiments are conducted in real road map and the results show that the algorithm is very effective in terms of finding a optimal path and search time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.565-569
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• 2007

To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.454-461
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• 2005

Car navigation system which is killer application fuses map management techniques into CPS techniques. Even if the existing navigation systems are designed for the shortest path, they are not able to cope efficiently with the change of the traffic flow and the bottleneck point of road. Therefore, it is necessary to find out shortest path algorithm based on time instead of distance which takes traffic information into consideration. In this paper, we propose a optimal path search algorithm based on the traffic information. More precisely. we introduce the system architecture for finding out optimal paths, and the limitations of the existing shortest path search algorithm are also analyzed. And then, we propose a new algorithm for finding out optimal path to make good use of the orientation of the collected traffic information.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.53-62
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• 2013

Cloud environment is one in the field of distributed computing and it consists of physical nodes and virtual nodes. In distributed cloud environment, an optimal path search is that each node to perform a search for an optimal path. Synchronization of each node is required for the optimal path search via fast data transmission because of real-time environment. Therefore, a quantization technique is required in order to guarantee QoS(Quality of Service) and search an optimal path. The quantization technique speeds search data transmission of each node. So a main server can transfer data of real-time environment to each node quickly and the nodes can perform to search optimal paths smoothly. In this paper, we propose the quantization technique to solve the search problem. The quantization technique can reduce the total data transmission. In order to experiment the optimal path search system which applied the quantized data transmission, we construct a simulation of cloud environment. Quantization applied cloud environment reduces the amount of data that transferred, and then QoS of an application for the optimal path search problem is guaranteed.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.585-586
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• 2009

홉필드 네트웍은 패턴 매칭과 더불어 최적화 문제를 푸는 도구로 사용될 수 있다. Ali에 의해 제안된 최적 경로 탐색 알고리즘을 개선하여 계산량을 대폭 줄이고 효과적으로 최적 경로를 탐색할 수 있다. 노드의 제곱인 브랜치수의 뉴런이 필요한 Ali 알고리즘은 탐색 네트워크가 커지면 많은 시간이 소요되는 단점이 있다. 본 논문은 계산량은 줄이면서 효과적으로 최적 경로를 탐색하는 방법을 제안한다.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.77-86
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• 2000

The shortest path problem is one of the mathematical Programming models that can be conveniently solved through the use of networks. The common shortest Path Problem is to minimize a single objective function such as distance, time or cost between two specified nodes in a transportation network. The sing1e objective model is not sufficient to reflect any Practical Problem with multiple conflicting objectives in the real world applications. In this paper, we consider the shortest Path Problem under multiple objective environment. Wile the shortest path problem with single objective is solvable in Polynomial time, the shortest Path Problem with multiple objectives is NP-complete. A genetic a1gorithm approach is developed to deal with this Problem. The results of the experimental investigation of the effectiveness of the algorithm are also Presented.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2918-2920
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• 2005

본 논문에서는 네비게이션 시스템 사용 시 교통 체증 등의 상황이 발생하여 최적 경로를 따라 가는 경우의 소요시간이 실제 예상시간보다 크게 증가하게 되는 경우 주변의 샛길을 이용하여 보다 빠른 시간에 체증 구간을 회피하여 목적지에 도착 할 수 있게 하는 알고리즘을 제안하고 이를 항법서버에 구현한다. 교통 체증상황이 발생하는 경우 경로 탐색시의 각 길에 대한 weighting 을 조절함으로써 원래 최적경로와 다른 우회로를 찾아 낼 수 있도록 한다. 상용화 되어있는 네비게이션 단말기를 사용하였으며 PC 시뮬레이터와 개발 서버를 이용하여 샛길 탐색 기능을 구현하였다. 최적경로 탐색에는 A* 알고리즘을 응용하였으며 최적경로에서 샛길 탐색구간을 구하여 전체 경로를 탐색하는 알고리즘을 구현하였다.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.91-102
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• 2005

When it comes to the process of information storage, people are likely to organize individual information into the forms of groups rather than independent attributes, and put them together in their brains. Likewise, in case of finding the shortest path, this study suggests that a Hierarchical Road Network(HRN) model should be selected to browse the most desirable route, since the HRN model takes the process mentioned above into account. Moreover, most of drivers make a decision to select a route from origin to destination by road hierarchy. It says that the drivers feel difference between the link travel tine which was measured by driving and the theoretical link travel time. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Stochastic Process model uses the historical patterns of travel time conditions on links. The HRN model has compared favorably with the conventional shortest path finding model in tern of calculated speeds. Even more, the result of the shortest path using the HRN model has more similar to the survey results which was conducted to the taxi drivers. Taxi drivers have a strong knowledge of road conditions on the road networks and they are more likely to select a shortest path according to the real common sense.