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Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones

Unmanned Aerial Vehicles, commonly known as drones, have been widely used in transmission line inspection and traffic patrolling due to their flexibility and environmental adaptability. To take advantage of drones and overcome their limited endurance, the patrolling tasks are parallelized by concurr...

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Autores principales: Tian, Shuangxi, Chen, Honghui, Wu, Guohua, Cheng, Jiaqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415381/
https://www.ncbi.nlm.nih.gov/pubmed/36015838
http://dx.doi.org/10.3390/s22166077
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author Tian, Shuangxi
Chen, Honghui
Wu, Guohua
Cheng, Jiaqi
author_facet Tian, Shuangxi
Chen, Honghui
Wu, Guohua
Cheng, Jiaqi
author_sort Tian, Shuangxi
collection PubMed
description Unmanned Aerial Vehicles, commonly known as drones, have been widely used in transmission line inspection and traffic patrolling due to their flexibility and environmental adaptability. To take advantage of drones and overcome their limited endurance, the patrolling tasks are parallelized by concurrently dispatching the drones from a truck which travels on the road network to the nearby task arc. The road network considered in previous research is undirected; however, in reality, the road network usually contains unidirectional arcs, i.e., the road network is asymmetric. Hence, we propose an asymmetric coordinated vehicle-drones arc routing mode for traffic patrolling. In this mode, a truck travelling on an asymmetric road network with multiple drones needs to patrol multiple task arcs, and the drones can be launched and recovered at certain nodes on the truck route, making it possible for drones and the truck to patrol the task in parallel. The total patrol time is the objective function that needs to be minimized given the time limit constraints of drones. The whole problem can be considered as an asymmetric arc routing problem of coordinating a truck and multiple drones. To solve this problem, a large-scale neighborhood search with simulated annealing algorithm (LNS-SA) is proposed. Finally, extensive computation experiments and a real case are carried out. The experimental results show the efficiency of the proposed algorithm. Moreover, a detailed sensitivity analysis is performed on several drone-parameters of interest.
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spelling pubmed-94153812022-08-27 Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones Tian, Shuangxi Chen, Honghui Wu, Guohua Cheng, Jiaqi Sensors (Basel) Article Unmanned Aerial Vehicles, commonly known as drones, have been widely used in transmission line inspection and traffic patrolling due to their flexibility and environmental adaptability. To take advantage of drones and overcome their limited endurance, the patrolling tasks are parallelized by concurrently dispatching the drones from a truck which travels on the road network to the nearby task arc. The road network considered in previous research is undirected; however, in reality, the road network usually contains unidirectional arcs, i.e., the road network is asymmetric. Hence, we propose an asymmetric coordinated vehicle-drones arc routing mode for traffic patrolling. In this mode, a truck travelling on an asymmetric road network with multiple drones needs to patrol multiple task arcs, and the drones can be launched and recovered at certain nodes on the truck route, making it possible for drones and the truck to patrol the task in parallel. The total patrol time is the objective function that needs to be minimized given the time limit constraints of drones. The whole problem can be considered as an asymmetric arc routing problem of coordinating a truck and multiple drones. To solve this problem, a large-scale neighborhood search with simulated annealing algorithm (LNS-SA) is proposed. Finally, extensive computation experiments and a real case are carried out. The experimental results show the efficiency of the proposed algorithm. Moreover, a detailed sensitivity analysis is performed on several drone-parameters of interest. MDPI 2022-08-14 /pmc/articles/PMC9415381/ /pubmed/36015838 http://dx.doi.org/10.3390/s22166077 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tian, Shuangxi
Chen, Honghui
Wu, Guohua
Cheng, Jiaqi
Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title_full Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title_fullStr Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title_full_unstemmed Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title_short Asymmetric Arc Routing by Coordinating a Truck and Multiple Drones
title_sort asymmetric arc routing by coordinating a truck and multiple drones
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415381/
https://www.ncbi.nlm.nih.gov/pubmed/36015838
http://dx.doi.org/10.3390/s22166077
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