Synergistic path planning of multi-UAVs for air pollution detection of ships in ports
The phenomena of the COVID-19 outbreak and the Arctic Iceberg melting over the past two years make us reconsider the impact our way of life has on the environment and the responsibility of business toward minimizing and potentially eliminating emissions. Increasing ship traffic in ports leads to the...
Published in: | Transportation Research Part E: Logistics and Transportation Review |
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2020
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Online Access: | http://researchonline.ljmu.ac.uk/id/eprint/16964/ https://researchonline.ljmu.ac.uk/id/eprint/16964/8/Synergistic%20Path%20Planning%20of%20Multi-UAVs%20for%20Air%20Pollution%20Detection%20of%20Ships%20in%20Ports1.pdf https://doi.org/10.1016/j.tre.2020.102128 |
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ftliverpooljmu:oai:researchonline.ljmu.ac.uk:16964 2023-05-15T15:12:43+02:00 Synergistic path planning of multi-UAVs for air pollution detection of ships in ports Shen, L Wang, Y Liu, K Yang, Z Shi, X Yang, X Jing, K 2020-11-01 text http://researchonline.ljmu.ac.uk/id/eprint/16964/ https://researchonline.ljmu.ac.uk/id/eprint/16964/8/Synergistic%20Path%20Planning%20of%20Multi-UAVs%20for%20Air%20Pollution%20Detection%20of%20Ships%20in%20Ports1.pdf https://doi.org/10.1016/j.tre.2020.102128 en eng Elsevier https://researchonline.ljmu.ac.uk/id/eprint/16964/8/Synergistic%20Path%20Planning%20of%20Multi-UAVs%20for%20Air%20Pollution%20Detection%20of%20Ships%20in%20Ports1.pdf Shen, L, Wang, Y, Liu, K, Yang, Z, Shi, X, Yang, X and Jing, K (2020) Synergistic path planning of multi-UAVs for air pollution detection of ships in ports. Transportation Research Part E: Logistics and Transportation Review, 144. ISSN 1366-5545 doi:10.1016/j.tre.2020.102128 cc_by_nc_nd CC-BY-NC-ND TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering VM Naval architecture. Shipbuilding. Marine engineering Article PeerReviewed 2020 ftliverpooljmu https://doi.org/10.1016/j.tre.2020.102128 2022-07-28T22:26:07Z The phenomena of the COVID-19 outbreak and the Arctic Iceberg melting over the past two years make us reconsider the impact our way of life has on the environment and the responsibility of business toward minimizing and potentially eliminating emissions. Increasing ship traffic in ports leads to the growing emission of air pollutants, which influences the air quality and public health in the surrounding areas. The International Maritime Organization (IMO) has adopted relevant regulations (e.g., Annex VI of IMO's pollution prevention treaty (MARPOL) and mandatory energy-efficiency measures) to address ship emissions. To ensure the effective implementation of such regulations and measures, air emission detection and monitoring has become crucial. In this paper, a dynamic multitarget path planning model is developed to realize multi-UAVs (Unmanned Aerial Vehicles) performing synergistic detection of ship emissions in ports. A path planning algorithm under a dynamic environment is developed to establish the model. This algorithm incorporates a Tabu table into particle swarm optimization (PSO) to improve its optimization ability, and it obtains the initial detection route of each UAV based on a “minimum ring” method. This paper describes a multi-UAVs synergistic algorithm to formulate the path reprogramming time in a dynamic environment by judging and cutting the “minimum ring”. This finding proves the improved efficiency of air pollution detection by UAVs. It provides useful insights for maritime and port authorities to detect ship emissions in practice and to ensure ship emission reduction for better air quality in the postpandemic era. Article in Journal/Newspaper Arctic Iceberg* Liverpool John Moores University: LJMU Research Online Arctic Transportation Research Part E: Logistics and Transportation Review 144 102128 |
institution |
Open Polar |
collection |
Liverpool John Moores University: LJMU Research Online |
op_collection_id |
ftliverpooljmu |
language |
English |
topic |
TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering VM Naval architecture. Shipbuilding. Marine engineering |
spellingShingle |
TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering VM Naval architecture. Shipbuilding. Marine engineering Shen, L Wang, Y Liu, K Yang, Z Shi, X Yang, X Jing, K Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
topic_facet |
TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering VM Naval architecture. Shipbuilding. Marine engineering |
description |
The phenomena of the COVID-19 outbreak and the Arctic Iceberg melting over the past two years make us reconsider the impact our way of life has on the environment and the responsibility of business toward minimizing and potentially eliminating emissions. Increasing ship traffic in ports leads to the growing emission of air pollutants, which influences the air quality and public health in the surrounding areas. The International Maritime Organization (IMO) has adopted relevant regulations (e.g., Annex VI of IMO's pollution prevention treaty (MARPOL) and mandatory energy-efficiency measures) to address ship emissions. To ensure the effective implementation of such regulations and measures, air emission detection and monitoring has become crucial. In this paper, a dynamic multitarget path planning model is developed to realize multi-UAVs (Unmanned Aerial Vehicles) performing synergistic detection of ship emissions in ports. A path planning algorithm under a dynamic environment is developed to establish the model. This algorithm incorporates a Tabu table into particle swarm optimization (PSO) to improve its optimization ability, and it obtains the initial detection route of each UAV based on a “minimum ring” method. This paper describes a multi-UAVs synergistic algorithm to formulate the path reprogramming time in a dynamic environment by judging and cutting the “minimum ring”. This finding proves the improved efficiency of air pollution detection by UAVs. It provides useful insights for maritime and port authorities to detect ship emissions in practice and to ensure ship emission reduction for better air quality in the postpandemic era. |
format |
Article in Journal/Newspaper |
author |
Shen, L Wang, Y Liu, K Yang, Z Shi, X Yang, X Jing, K |
author_facet |
Shen, L Wang, Y Liu, K Yang, Z Shi, X Yang, X Jing, K |
author_sort |
Shen, L |
title |
Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
title_short |
Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
title_full |
Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
title_fullStr |
Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
title_full_unstemmed |
Synergistic path planning of multi-UAVs for air pollution detection of ships in ports |
title_sort |
synergistic path planning of multi-uavs for air pollution detection of ships in ports |
publisher |
Elsevier |
publishDate |
2020 |
url |
http://researchonline.ljmu.ac.uk/id/eprint/16964/ https://researchonline.ljmu.ac.uk/id/eprint/16964/8/Synergistic%20Path%20Planning%20of%20Multi-UAVs%20for%20Air%20Pollution%20Detection%20of%20Ships%20in%20Ports1.pdf https://doi.org/10.1016/j.tre.2020.102128 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Iceberg* |
genre_facet |
Arctic Iceberg* |
op_relation |
https://researchonline.ljmu.ac.uk/id/eprint/16964/8/Synergistic%20Path%20Planning%20of%20Multi-UAVs%20for%20Air%20Pollution%20Detection%20of%20Ships%20in%20Ports1.pdf Shen, L, Wang, Y, Liu, K, Yang, Z, Shi, X, Yang, X and Jing, K (2020) Synergistic path planning of multi-UAVs for air pollution detection of ships in ports. Transportation Research Part E: Logistics and Transportation Review, 144. ISSN 1366-5545 doi:10.1016/j.tre.2020.102128 |
op_rights |
cc_by_nc_nd |
op_rightsnorm |
CC-BY-NC-ND |
op_doi |
https://doi.org/10.1016/j.tre.2020.102128 |
container_title |
Transportation Research Part E: Logistics and Transportation Review |
container_volume |
144 |
container_start_page |
102128 |
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1766343361229225984 |