• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.109-117
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• 2014

In navigation route planning systems using A* algorithms, the cardinality of an Open list, which is a list of candidate nodes through which a terminal node can be accessed, increases as the path length increases. In this paper, a method of alternately utilizing the Dijkstra's algorithm and the A* algorithm to reduce the cardinality of the Open list is investigated. In particular, by employing a depth parameter, named Level, the two algorithms are alternately performed depending on the Level's value. Using the hybrid searching approach, the Open list constructed in the Dijkstra's algorithm is transferred into the Open list of the A* algorithm, and consequently, the unconstricted increase of the cardinality of the Open list of the former algorithm can be avoided and controlled appropriately. In addition, an optimal or nearly optimal path similar to the Dijkstra's route, but not available in the A* algorithm, can be found. The experimental results, obtained with synthetic and real-life benchmark data, demonstrate that the computational cost, measured with the number of nodes to be compared, was remarkably reduced compared to the traditional searching algorithms, while maintaining the similar distance to those of the latter algorithms. Here, the values of Level were empirically selected. Thus, a study on finding the optimal Level values, while taking into consideration the actual road conditions remains open.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.887-890
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• 2007

For a integrated system to control several parking lots within a commercial district, it is required to guide a route to a nearest neighbor parking lot considering diverse realtime constraints such as realtime status of parking lots and changes of an access route. This paper proposes an optimized route-searching technique of integrated parking control system considering realtime contraints. In concrete, it proposes a method of researching a route in the surrounding area considering various status of parking lots that a customer designates (no parking, closed, under construction, no passing of a road) and deals with a route-searching technique optimized for each situation in detail.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.556-559
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• 2020

최근 태풍, 지진, 산불, 산사태, 전쟁 등 다양한 재난 상황으로 인한 인명피해와 자금 손실이 꾸준히 발생하고 있고 현재 이를 예방하고 복구하기 위해 많은 인력과 자금이 소요되고 있는 실정이다. 이러한 여러 재난 상황을 미리 감시하고 재난 발생의 빠른 인지 및 대처를 위해 본 논문에서는 인공지능 기반의 재난 드론 시스템을 설계 및 개발하였다. 본 연구에서는 사람이 감시하기 힘든 지역에 여러 대의 재난 드론을 이용하며 딥러닝 기반의 최단 경로 알고리즘을 적용해 각각의 드론이 최적의 경로로 효율적 탐색을 실시한다. 또한 드론의 근본적 문제인 배터리 용량 부족에 대한 문제점을 해결하기 위해 Ant Colony Optimization (ACO) 기술을 이용하여 각 드론의 최적 경로를 결정하게 된다. 제안한 시스템 구현을 위해 여러 재난 상황 중 산불 상황에 적용하였으며 전송된 데이터를 기반으로 산불지도를 만들고, 빔프로젝터를 탑재한 드론이 출동한 소방관에게 산불지도를 시각적으로 보여주었다. 제안한 시스템에서는 여러 대의 드론이 최적 경로 탐색 및 객체인식을 동시에 수행함으로써 빠른 시간 내에 재난 상황을 인지할 수 있다. 본 연구를 바탕으로 재난 드론 인프라를 구축하고 조난자 탐색(바다, 산, 밀림), 드론을 이용한 자체적인 화재진압, 방범 드론 등에 활용할 수 있다.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.59-66
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• 2002

The rapid change of industrial structure causes to increase distribution cost and requires necessity of physical distribution system urgently. Traffic situation is getting extremely worse and traffic jam has led to increasing expense of physical distribution delivery which dominates 20% of distribution cost. In this situation, the shortest and most suitable path search system is required by modern people who must waste a lot of time for moving with a car or on the street as well as many companies. for these reasons, we developed the shortest-path-searching system applying the dijkstra algorithm which is one of the effective shortest path algorithm to GIS, and it was constructed by considering realistic urban traffic and the pattern of street in a physical situation. Also, this system was developed to be updated weight data automatically, considering the dynamic change of traffic situation such as a traffic information service which will be served in real time. Finally, we designed this system to serve on web by using MapObjects IMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.827-830
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• 2008

The Center Based Navigation System(CBNS) used real time road data searches an optimal path. The other hand, the Terminal Based Navigation System(TBNS) used embedded road data searches a path that has less qualitative than the CBNS. But the TBNS has been favored, because it has no additional fees. Generally, TBNS has not used real time road data but it is recently able to use it with technique such as TPEG. However, it causes to increase a cost of exploring by using real time road data for improvement qualify of a path, because of limited performance. We propose a path-finding algorithm using a Maximum peed Dynamic Heuristic to improve quality and reduce a cost of exploring. Proposed method is to use a maximum road speed of appropriate region as dynamic heuristic for path-finding.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.273-282
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• 2016

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the ‘length’ factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra’s Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.457-465
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• 2001

■ 필요성 1. 교통 혼잡으로 인한 물류비 상승으로 국가 경쟁력 약화 2. 기존 최단경로 알고리즘(Dijkstra, Floyd-Warshall 등)의 한계 3. 대규모 네트워크(NP-hard문제)→정보 사용자가 제시하는 시간 내에 정보를 제공 필요 4. 교통 제약(회전금지, U턴, U턴 금지, P-턴) → 실제 교통 상황과 순환 노드 고려가 필요 ■목적 1. 교통제약을 포함한 대규모 교통네트워크에서 실시간 교통정보를 바탕으로 제한된 시간 내에 차별화 된 다수 최적경로 산출 함 2. 유전자알고리즘(GA)을 적용한 동적경로안내시스템 개발(중략)

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.51-56
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• 2004

인터넷 통신과 무선 이동 통신의 발달은 최적 경로 탐색이 인터넷 웹 페이지를 통하여 서비스될 수 있도록 하였으며, CNS(Car Navigation System)를 이용한 서비스도 가능하도록 하였다. 나아가 개인용 휴대통신 장비인 PDA나 핸드폰을 이용하여서도 그 서비스가 제공되고 있다. 기존의 양방향 A＊ 알고리즘에서는 현재 노드에서 목적지까지의 예상 비용을 직선 거리를 사용하였지만 본 논문에서는 현재 노드까지 지나온 경로에 대한 정보를 이용하였다. 지금까지 지나온 경로의 평균 경로 비용을 계산하여 이용함으로써, 직선 길이가 아닌 지금까지 지나온 경로의 정보를 이용할 수 있었고, 지나온 경로의 정보와 앞으로 탐색할 경로에 대한 애매한 정보들(도로의 속도, 날씨, 주행시간대)을 퍼지를 이용하여 계산하였다. 퍼지를 이용하여 도로의 애매한 정보들을 실시간으로 활용할 수 있는 알고리즘을 제안하고 제안한 알고리즘의 타당성을 실험을 통하여 검증하였다.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.161-172
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• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.