Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions

<p>Task allocation under uncertain conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent-based simulation to investigate task allocation considering appropriate spatial strategies to manage uncertainty in urban search and re...

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Autores principales:	N. Hooshangi, A. A. Alesheikh, M. Panahi, S. Lee
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/682f5ad398084015b9ed71279db88059
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spelling	oai:doaj.org-article:682f5ad398084015b9ed71279db880592021-11-15T11:09:15ZUrban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions10.5194/nhess-21-3449-20211561-86331684-9981https://doaj.org/article/682f5ad398084015b9ed71279db880592021-11-01T00:00:00Zhttps://nhess.copernicus.org/articles/21/3449/2021/nhess-21-3449-2021.pdfhttps://doaj.org/toc/1561-8633https://doaj.org/toc/1684-9981<p>Task allocation under uncertain conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent-based simulation to investigate task allocation considering appropriate spatial strategies to manage uncertainty in urban search and rescue (USAR) operations. The proposed method is based on the contract net protocol (CNP) and implemented over five phases: ordering existing tasks considering intrinsic interval uncertainty, finding a coordinating agent, holding an auction, applying allocation strategies (four strategies), and implementing and observing the real environment. Applying allocation strategies is the main innovation of the method. The methodology was evaluated in Tehran's District 1 for 6.6, 6.9, and 7.2 magnitude earthquakes. The simulation began by calculating the numbers of injured individuals, which were 28 856, 73 195, and 111 463 people for each earthquake, respectively. Simulations were performed for each scenario for a variety of rescuers (1000, 1500, and 2000 rescuers). In comparison with the CNP, the standard duration of rescue operations with the proposed approach exhibited at least 13 % improvement, with a maximal improvement of 21 %. Interval uncertainty analysis and comparison of the proposed strategies showed that increased uncertainty led to increased rescue time for the CNP and strategies 1 to 4. The time increase was less with the uniform distribution strategy (strategy 4) than with the other strategies. The consideration of strategies in the task allocation process, especially spatial strategies, facilitated both optimization and increased flexibility of the allocation. It also improved conditions for fault tolerance and agent-based cooperation stability in the USAR simulation system.</p>N. HooshangiA. A. AlesheikhM. PanahiM. PanahiS. LeeS. LeeCopernicus PublicationsarticleEnvironmental technology. Sanitary engineeringTD1-1066Geography. Anthropology. RecreationGEnvironmental sciencesGE1-350GeologyQE1-996.5ENNatural Hazards and Earth System Sciences, Vol 21, Pp 3449-3463 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5
spellingShingle	Environmental technology. Sanitary engineering TD1-1066 Geography. Anthropology. Recreation G Environmental sciences GE1-350 Geology QE1-996.5 N. Hooshangi A. A. Alesheikh M. Panahi M. Panahi S. Lee S. Lee Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
description	<p>Task allocation under uncertain conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent-based simulation to investigate task allocation considering appropriate spatial strategies to manage uncertainty in urban search and rescue (USAR) operations. The proposed method is based on the contract net protocol (CNP) and implemented over five phases: ordering existing tasks considering intrinsic interval uncertainty, finding a coordinating agent, holding an auction, applying allocation strategies (four strategies), and implementing and observing the real environment. Applying allocation strategies is the main innovation of the method. The methodology was evaluated in Tehran's District 1 for 6.6, 6.9, and 7.2 magnitude earthquakes. The simulation began by calculating the numbers of injured individuals, which were 28 856, 73 195, and 111 463 people for each earthquake, respectively. Simulations were performed for each scenario for a variety of rescuers (1000, 1500, and 2000 rescuers). In comparison with the CNP, the standard duration of rescue operations with the proposed approach exhibited at least 13 % improvement, with a maximal improvement of 21 %. Interval uncertainty analysis and comparison of the proposed strategies showed that increased uncertainty led to increased rescue time for the CNP and strategies 1 to 4. The time increase was less with the uniform distribution strategy (strategy 4) than with the other strategies. The consideration of strategies in the task allocation process, especially spatial strategies, facilitated both optimization and increased flexibility of the allocation. It also improved conditions for fault tolerance and agent-based cooperation stability in the USAR simulation system.</p>
format	article
author	N. Hooshangi A. A. Alesheikh M. Panahi M. Panahi S. Lee S. Lee
author_facet	N. Hooshangi A. A. Alesheikh M. Panahi M. Panahi S. Lee S. Lee
author_sort	N. Hooshangi
title	Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
title_short	Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
title_full	Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
title_fullStr	Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
title_full_unstemmed	Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions
title_sort	urban search and rescue (usar) simulation system: spatial strategies for agent task allocation under uncertain conditions
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/682f5ad398084015b9ed71279db88059
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Urban search and rescue (USAR) simulation system: spatial strategies for agent task allocation under uncertain conditions

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