Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports. (September 2022)
- Record Type:
- Journal Article
- Title:
- Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports. (September 2022)
- Main Title:
- Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports
- Authors:
- Shen, Lixin
Hou, Yunxia
Yang, Qin
Lv, Meilin
Dong, Jing-Xin
Yang, Zaili
Li, Dongjun - Abstract:
- Abstract: Traditionally, vessel air emissions are monitored onboard vessels or at fixed points at sea. These methods are not cost-effective for implementing emission control laws that address air pollution monitoring of vessels travelling over a large body of water. Unmanned aerial vehicles (UAVs) equipped with pollution monitoring sensors are becoming a research focus. However, due to battery capacity constraints, the monitoring scope of UAVs is still not optimal. Thus, using a ship (such as a patrol ship) as a UAV mobile supply base can overcome battery limitations and increase monitoring coverage. This paper investigates the joint routing and scheduling problem of ship-deployed multiple UAVs (SDMUs) for the monitoring of pollution from vessels. The artificial bee colony (ABC) algorithm based on simulated annealing is employed to minimize the total monitoring time. The model and solution algorithm are verified by real-time dynamic vessel data from Tianjin Port.
- Is Part Of:
- Transportation research. Volume 110(2022)
- Journal:
- Transportation research
- Issue:
- Volume 110(2022)
- Issue Display:
- Volume 110, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 110
- Issue:
- 2022
- Issue Sort Value:
- 2022-0110-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- UAV -- Vessel air pollution -- Two-level path planning -- Bee colony algorithm
Transportation -- Research -- Periodicals
Transportation -- Environmental aspects -- Periodicals
354.76 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13619209 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trd.2022.103415 ↗
- Languages:
- English
- ISSNs:
- 1361-9209
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274630
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