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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
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Synergistic Path Planning of Multi-UAVs for Air Pollution Detection of Ships in Ports1.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
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.
| Item Type: | Article |
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| Uncontrolled Keywords: | Social Sciences; Science & Technology; Technology; Economics; Engineering, Civil; Operations Research & Management Science; Transportation; Transportation Science & Technology; Business & Economics; Engineering; UAVs; Ship emissions; Air pollution; Path planning; Dynamic multiobjective; PSO; TRAVELING SALESMAN PROBLEM; EMISSION; OPTIMIZATION; VESSELS; 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; 1507 Transportation and Freight Services; Logistics & Transportation |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TD Environmental technology. Sanitary engineering V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering |
| Divisions: | Engineering |
| Publisher: | Elsevier |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 25 Jul 2022 08:55 |
| Last Modified: | 25 Jul 2022 09:00 |
| DOI or ID number: | 10.1016/j.tre.2020.102128 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/16964 |
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