• Proceedings of the KOR-KST Conference
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• 1996.12a
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• pp.81-108
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• 1996

첨단교통정보시스템(ATIS)의 핵심 요소라 할 수 있는 동적경로안내 시스템(Dynamic Route Guidance System : DRGS)은 운전자가 목적지에 도착하기까지 실시간 교통정보를 토대로 최적경로를 안내해 줌으로써 날로 심화되어 가고 있는 교통혼잡을 최소화할 수 있으리라 기대를 모으고 있다. 특히 교통사고나 긴급도로공사 등으로 인해 발생하는 돌발적 교통혼잡하에서는 DRGS의 역할이 더욱 커질 것으로 예상되고 있다. 본 논문은 돌발적 교통혼잡하에서 보다 효과적인 DRGS의 경로 안내 알고리즘을 개발하는 데 그 목적이 있다. 이를 위해서 우선 하부구조기반(Infrastructure Based) DRGS와 개인차량기반(In-vehicle Based)DRGS의 장단점을 운전자, 교통행정당국, 그리고 교통체계관점에서 비교하였고, 시스템 아키텍쳐와 경로안내 알고리즘간의 상호관계를 규명하였다. 또한 효율적인 경로안내를 위해 사용자 평형(User Equilibrium)경로안내전략과 시스템최적화(System Optimal) 경로안내전략을 이상형 교통망(Idealistic Network)을 통해 비교분석하였다. 여기에는 현재 ITS-America에서 System Architecture 평가를 위해 사용한 INTEGRATION이라는 ITS Simulation Model과 그 통행저항함수를 사용하였다. 이를 토대로 돌발적 교통혼잡상황 아래서 사용자평형 경로안내를 제공할 경우 야기될 수 있는 Braess` Paradox 문제와, 총통행시간을 최소화하기 위한 시스템최적 경로안내를 제공할 경우 일어날 수 있는 사용자 호응도(User Compliance)문제를 동시에 고려한 적응형 동적경로안내 알고리즘을 개발하였다. 여기에는 돌발적 교통혼잡하에서 통행시간을 동적으로 예측하기 위해 이산형 확정적 대기행렬모형(Discrete Deterministic Queueing Model)이 사용되었다. 한편 알고리즘의 효율성을 평가하기 위해 이상형 교통망과, 실제 미국 Virginia 주의 Fairfax County에 소재한 주간 고속도로 66번(I-66)과 인접 교통망의 교통자료를 사용하여 각종 돌발교통 혼잡 상황을 전제로 한 Traffic Simulation과 정보제공시나\리오를 INTEGRATION Model을 이용해 실행하였다. 그 결과 적응형 알고리즘이 개개인의 최단시간 경로를 제공하는 사용자 평형 경로안내전략에 비해 교통혼잡도와 정체시간의 체류정도에 따라 3%에서 10%까지 전체통행시간을 절약할 수 있다는 결론을 얻었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.775-778
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• 2016

로봇 주행 기술은 전통적인 로봇요소 기술 외에도 여러 기술로 대상 응용서비스에 따라 IT 기술과 적극적인 융합을 통해 다양한 주행방법과 주행성능이 향상되고 있다. 본 논문에서는 대표적인 실내 모바일 로봇인 로봇 청소기를 대상으로 기존의 방법인 적외선과 카메라 방법이 아닌 보통 가정에도 쉽게 존재하는 AP를 이용해 목표를 설정하여 포섭구조 이론을 기반으로 동적인 환경에서도 충전 스테이션 까지 자율 주행이 가능한 로봇 알고리즘을 설계하였다. 그 결과 동적인 환경을 설정하여 로봇이 AP를 찾아가는 것을 확인하였고 주행 경로와 경과 시간을 표로 도출하여 다른 경우를 예측할 수 있게 하였다. 향후 행동 기반 로봇과 다양한 센서를 이용하여 로봇의 위치와 목표점 사이의 최단거리 경로를 구하여 주행하는 것이 목표이다.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.167-176
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• 2006

An minimum path algorithm for integrated networks with departure time constraints require considering arrival time of arriving mode, transfer time. waiting time, and departure time of next mode. Integrated network with diverse modes commonly include departure time constraints. Because public mode suck as train and airplane have fixed service schedule which provide passengers. This study developed the k-path algorithm in integrated network with time varying conditions and departure time constraints. We proposed the extended method based on entire path deletion method, and examined the application of the proposed algorithm through case study.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.171-179
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• 2013

The primary function of navigation system is to provide route search and road guidance for safe driving for drivers. However, the existing route search system provides a simple service that looks up the shortest route using a safe driving DB without considering different road characteristics for the safety of the drivers. In order to maintain the safe driving, rather than searching the shortest path, a navigation system, in which the danger areas and/or the dangerous time zones have been considered, is required. Therefore, in this paper we propose a strategy of searching a navigation path to avoid danger areas for safe driving by using the A* algorithm. In the strategy, when evaluating the path-specific fitness of the navigation nodes, different heuristic weights were assigned to different types of risk areas. In particular, we considered three kinds of danger areas, such as accident-prone sections where accidents occur frequently, school zones, and intersection regions, as well as the time slots when the probability of danger is high. From computer simulation, the results demonstrate that the proposed scheme can provide the way to avoid danger areas on the route searching and confirm the possibility of providing the actual service.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.821-824
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• 2014

선박경제운항이란 예보된 기상정보를 활용하여 연료소모량을 최소화하도록 선박을 운항하는 것으로서 최근 다양한 방법론이 연구되고 있다. 성공적인 경제운항시스템을 구현하기 위해서는 기상을 고려하여 지리적 운항경로를 바꾸거나 적절하게 엔진 출력을 조절하는 방법이 필요하다. 그러나 항해 시각에 따라 연료소모량이 변하는 동적 비용 문제임을 고려할 때 지리적 운항 경로의 결정은 최적의 해를 찾기가 어렵다. 이에 이 논문에서는 매우 많은 지리적 후보 경로들 중에서 우수한 품질의 해를 효과적으로 탐색하기 위한 진화전략 기반 경로탐색 알고리즘을 제안하였다. 제안된 방법을 5개 노선에 대해 실험한 결과 최단거리 운항 방법에 비해 운항소요시간은 거의 차이가 없으면서도 연료소모량을 평균 1.41%, 최대 1.45% 개선시킬 수 있었다.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.

• Journal of Korean Society of Transportation
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• v.21 no.6
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• pp.77-88
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• 2003

This paper proposes a solution algorithm for solving a multi-class analytical DTA model. In the DTA model, three traveler classes are classified according to different assumptions of traveler's route choice behavior: including fixed route, Stochastic Dynamic User Optimum(SDUO), and Dynamic User Optimum(DUO). To solve this DTA model, variables of link flow and exit flow are represented solely by inflow. The resulting Linear Program(LP) subproblem in the inner iteration is solved as a typical time-dependent shortest route problem over a physical network. Accordingly, the required time-space network expansion in solving DTA models is no longer needed.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.117-126
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• 2013

Path planning is an essential problem to make virtual characters navigate in many applications including computer games. In many cases, multiple characters move in a group and qualitative aspects of planned paths are emphasized rather than optimality unlike Robotics. In this paper, we propose a two-level path planning algorithm in which the global path is planned for a single character specified as a leader and then the local path is planned to avoid dynamic obstacles while the group following this path. The space for group movement is achieved in the form of square grid array called a grid window. Member characters are located relatively to the leader within a space and moved. The static environment is reduced to the configuration space of this grid window to generate a roadmap on which a grid window can move. In local path planning, only the leader avoids dynamic obstacles by using an artificial potential field and the rest of members are located relatively to the leader in the grid window, which reduces computational load. Efficient algorithms to implement the proposed planning methods are introduced. The simulation results show that a group can handle with dynamic obstacles effectively while moving along the planned path for a static environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2635-2643
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• 1997

In this paepr, a routing algorithm is proposed in order to reduce average end-to-end delay and congesting in the high speed network. The algorithm proposed here uses the existing one which adaptively modifies routes and the amount of traffic allocated to each link as user traffic partterns flutuate. This algorithm is ELB(Equitable Load Balancing). Also, the new algorithm considers the proportional to the distance between source and destination. It reduces congestion from the ELB and average end-to-end delay from the propagation dealy concepts respectively. Through the simulation, it shows that the algorithm proposed here reduces average end-to-end delay over low load to high load, and it also guarantees the congestion control.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.