TY - JOUR
T1 - Synergistic path planning for ship-deployed multiple UAVs to monitor vessel pollution in ports
AU - Shen, Lixin
AU - Hou, Yunxia
AU - Yang, Qin
AU - Lv, Meilin
AU - Dong, Jingxin
AU - Yang, Zaili
AU - Li, Dongjun
PY - 2022/9/1
Y1 - 2022/9/1
N2 - 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.
AB - 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.
KW - UAVs
KW - Vessel air pollution
KW - Bee colony algorithm
KW - Two-level path planning
KW - UAV
UR - https://www.scopus.com/pages/publications/85144305493
U2 - 10.1016/j.trd.2022.103415
DO - 10.1016/j.trd.2022.103415
M3 - Article
SN - 1361-9209
VL - 110
JO - Transportation Research Part D: Transport and Environment
JF - Transportation Research Part D: Transport and Environment
M1 - 103415
ER -