• 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.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11b
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• pp.1237-1240
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• 2002

본 논문에서는 ATM과 같은 연결 지향적 고속네트워크에서, 가중치를 가진 Flow들의 대역폭 할당과 라우팅문제에 있어 공정성과 처리량에 대하여 고려해 보았다. 가중치클 고려치 않은 Flow들에 대한 최적경로설정문제에 대하여, 기존의 QoS 서비스와 Best-Effort 서비스에서 연구된 라우팅알고리즘에서 벗어나, 본 논문은 가중치를 가진 Flow들에 대하여 Soft-QoS서비스를 지원함에 있어서 공정성과 최대 처리량을 정의하고, 또한 이를 바탕으로 가중치 최소극대 대역폭 할당과 가중치 최소극대 공정라우팅 알고리즘을 제안한다. 종단간 최적경로를 설정하는데, 최소비용으로 Bottleneck-Link를 구하고 대역폭을 할당하기 위하여 그래프 상의 노드에 두 가지 색을 사용하는 그래프문제(Graph Coloring)와 최악의 경우를 감안하면서 경로를 선택하는 최소극대화 문제(Maxmin)를 결부시켜 살펴본다. 나아가 Soft-QoS 서비스의 최대값과 최소값을 고려한 가중치를 가진 Weighted-Flow들의 대역폭 할당과 경로설정에 있어, 동적인 네트워크 환경에 보다 효율적으로 접근 가능한 근사 알고리즘을 제안한다.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.99-107
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• 2000

Path-based assignment(PBA) is valuable to dynamic traffic control and routing in integrated ITS framework. As one of widely studied PBA a1gorithms, Gradient Projection(GP) a1gorithm typically fields rapid convergence to a neighborhood of an optimal solution. But once it comes near a solution, it tends to slow down. To overcome this problem, we develop more efficient path-based assignment algorithm by combining Conjugate Gradient method with GP algorithm. It determines more accurate moving direction near a solution in order to gain a significant advantage in speed of convergence. Also this algorithm is applied to the Sioux-Falls network and verified its efficiency. Then we demonstrate that this type of method is very useful in improving speed of convergence in the case of user equilibrium problem.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.81-88
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• 2009

In this paper, I suggested a way for searching a path of the intelligent character in an action game by using a genetic algorithm. This realized the algorithm which enables not only to chose the nearest path but also to search the optimum path by using genetic algorithm. In this case, if the codes of chromosomes are applied as they are, a lot of lethal genes could occur. In order to solve such a problem, I used a splicing method, one of the DNA's behavior characteristics. The intelligent character searched out a optimum pass as well as a shortcut path with one treatment by using the characteristic of a genetic algorithm which generates multiple candidate solutions in the search process.

• Spatial Information Research
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• v.17 no.3
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• pp.361-370
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• 2009

As the increasing interests of spatial information for different application area such as disaster management, there are many researches and development of indoor spatial data models and real-time evacuation management systems. The application requires to determine and optical paths in emergency situation, to support evacuees and rescuers. The optimal path in this study is defined to guide rescuers, So, the path is from entrance to the disaster site (room), not from rooms to entrances in the building. In this study, we propose a time-dependent optimal routing algorithm to develop real-time evacuation systems. The network data that represents navigable spaces in building is used for routing the optimal path. Associated information about environment (for example, number of evacuees or rescuers, capacity of hallways and rooms, type of rooms and so on) is assigned to nodes and edges in the network. The time-dependent optimal path is defined after concerning environmental information on the positions of evacuees (for avoiding places jammed with evacuees) and rescuer at each time slot. To detect the positions of human beings in a building per time period, we use the results of evacuation simulation system to identify the movement patterns of human beings in the emergency situation. We use the simulation data of five or ten seconds time interval, to determine the optimal route for rescuers.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.278-282
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• 2010

모바일 애드혹 네트워크에서의 멀티패스 라우팅 프로토콜은 기존의 단일패스 라우팅 프로토콜에 비하여 대역폭을 효율적으로 사용할 수 있고 혼잡을 완화시킬 수 있으며, 데이터 전달의 신뢰성을 제공할 수 있다. 하지만 멀티패스 라우팅 프로토콜에서의 경로 탐색 과정은 오버헤드가 크고 계산의 복잡도 또한 높다. 본 논문에서는 무선 애드혹 네트워크에서의 멀티패스 라우팅을 위한 효율적인 노드디스조인트 경로 탐색 알고리즘을 제안한다. 제안하는 알고리즘은 지연된 RREP(Route Reply) 패킷을 사용하여 최적의 노드 디스조인트 경로를 탐색하고 그중 간섭 및 충돌의 영향이 적은 경로 집합을 선택한다. 이를 통해 빠르게 트래픽을 분산시킬 수 있고 충돌로 인한 오류의 발생을 낮추어 신뢰성을 높일 수 있다. 실험을 통하여 제안하는 경로 탐색 알고리즘이 최적의 멀티패스를 선택함을 확인하였다.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.5
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• pp.609-617
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• 2013

This paper presents a near-minimum time path planning algorithm for autonomous driving. The problem of near-minimum time path planning is an optimization problem in which it is necessary to take into account not only the geometry of the circuit but also the dynamics of the vehicle. The path planning algorithm consists of a candidate path generation and a velocity optimization algorithm. The candidate path generation algorithm calculates the compromises between the shortest path and the path that allows the highest speeds to be achieved. The velocity optimization algorithm calculates the lap time of each candidate considering the vehicle driving performance and tire friction limit. By using the calculated path and velocity of each candidate, we calculate the lap times and search for a near-minimum time path. The proposed algorithm was evaluated via computer simulation using CarSim and Matlab/Simulink.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.5
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• pp.379-387
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• 2019

The complexity of path planning for visiting multiple mission points is even larger than that of single pair path planning. Deciding a path for visiting n mission points requires conducting $n^2+n$ times of single pair path planning. We propose Multiple Mission $D^*$ Lite($MMD^*L$) which is an optimal path planning algorithm for visiting multiple mission points in dynamic environments. $MMD^*L$ reduces the complexity by reusing the computational data of preceding single pair path planning. Simulation results show that the complexity reduction is significant while its path optimality is not compromised.