Multi-agent based path planning for first responders among moving obstacles

被引:23
作者
Wang, Zhiyong [1 ]
Zlatanova, Sisi [1 ]
机构
[1] Delft Univ Technol, Julianalaan 134, NL-2628 BX Delft, Netherlands
关键词
Path planning; Multi-agent system; Spatial data model; Algorithms; Moving obstacles; EMERGENCY RESPONSE; SIMULATION;
D O I
10.1016/j.compenvurbsys.2015.11.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Natural or man-made disasters can cause different kinds of moving obstacles (e.g., fires, plumes, floods), which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. In this paper, we present a novel approach for using a multi-agent system for navigating one or multiple responders to one or multiple destinations in the presence of moving obstacles. Our navigation system supports information collection from hazard simulations, spatio-temporal data processing and analysis, connection with a geo-database, and route generation in dynamic environments affected by disasters. We design and develop a set of software geospatial agents that assist emergency actors in dealing with the spatio-temporal data required for emergency navigation, based on their roles in the disaster response. One of the key components of the system is the path planning module, which combines the modified A* algorithm, insertion heuristics, and auction algorithm to calculate obstacle-avoiding routes for multiple responders with multiple destinations. A spatial data model is designed to support the storage of information about the tasks and routes produced during the disaster response. Our system has been validated using four navigation cases. Some preliminary results are presented in this paper and show the potential of the system for solving more navigation cases. (c) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:48 / 58
页数:11
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