Abstract:
플래툰의 차량의 속도를 적응시키기 위한 방법, 컴퓨터 프로그램, 및 장치, 차량, 교통 제어 엔티티 실시형태는 차량, 교통 제어 엔티티, 플래툰의 차량의 속도를 적응시키기 위한, 방법, 컴퓨터 프로그램, 및 장치를 제공한다. 플래툰의 차량의 속도를 적응시키기 위한 방법(10)은 플래툰의 차량의 필요한 최소 차량간 거리의 미래의 코스에 관련되는 정보를 획득하는 것(12)을 포함한다. 방법(10)은 필요한 최소 차량간 거리의 미래의 코스에 관련되는 정보, 및 플래툰의 차량의 연료 소비에 기초하여 플래툰의 차량의 속도를 적응시키는 것(14)을 더 포함한다.
Abstract:
PROBLEM TO BE SOLVED: To provide an energy-saving automatic guided carrier and a carrier route determination method thereof for automatically determining a carrier route without monitoring a detailed position or a passing time of the carrier device, without requiring a sensor, a communication path, and a calculation device for monitoring, and without highly precise forecast, while selecting an appropriate route even if congestion prediction fails. SOLUTION: A storage device 17 stores a graph in which a transfer point of the carrier device 11, a branching point, a merging point, a conveyance source or a conveyance destination are defined as "points", a route from each point to any adjacent point to which the carrier can be moved directly is defined as an "arrow", and a sum obtained by adding a temporal load proportional to the passing time for each arrow to an energy load proportional to consumption energy is defined as "weight". A carrier control device 18 determines a route having the minimum total weight of each arrow constituting the carrier route from the conveyance source to the conveyance destination as a scheduled route for each article. COPYRIGHT: (C)2010,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To provide a system capable of setting safe paths where the danger of collisions is lessened. SOLUTION: After a grid map is generated from a geometric map (S102), a weighted Voronoi graph is generated from the grid map (S104). The weighted Voronoi graph uses weighted distances according to uncertainties of positions and attitudes of objects. One designated target object is taken out (S106), and a boundary sub-graph consisting of Voronoi nodes being on the boundary of a Voronoi area of the target object is extracted (S108). The most suitable observation paths allowing observation of the target object are obtained in the boundary sub-graph of the present target object, and movement paths between the observation paths (S112) are obtained. After movement paths from each node in the boundary sub-graph of the target object to terminal points of all paths are obtained (S116), path retrieval is performed by a composite graph resulting from alternately linking the movement paths and observation paths obtained till then. Finally, obtained paths are optimized. COPYRIGHT: (C)2005,JPO&NCIPI