Journal
JOURNAL OF CENTRAL SOUTH UNIVERSITY
Volume 21, Issue 6, Pages 2501-2510Publisher
JOURNAL OF CENTRAL SOUTH UNIV
DOI: 10.1007/s11771-014-2205-z
Keywords
unmanned aerial vehicle; traffic surveillance; route planning; multi-objective optimization; evolutionary algorithm
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Funding
- National High Technology Research and Development Program of China [2009AA11Z220]
- National Natural Science Foundation of China [61070112, 61070116]
- Ministry of Public Security of China [2012LLYJTJSJ077]
- Tianjin University of Technology and Education, China [KYQD14003]
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Unmanned aerial vehicle (UAV) was introduced to take road segment traffic surveillance. Considering the limited UAV maximum flight distance, UAV route planning problem was studied. First, a multi-objective optimization model of planning UAV route for road segment surveillance was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem. At last, a UAV flight experiment was conducted to test UAV route planning effect, and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning. The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%, respectively. Additionally, shortening or extending the length of road segments has different impacts on UAV route planning.
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