An optimization model of UAV route planning for road segment surveillance
来源期刊：中南大学学报(英文版)2014年第6期
论文作者：LIU Xiao-feng(刘晓锋) GUAN Zhi-wei(关志伟) SONG Yu-qing(宋裕庆) CHEN Da-shan(陈大山)
文章页码：2501 - 2510
Key words：unmanned aerial vehicle; traffic surveillance; route planning; multi-objective optimization; evolutionary algorithm
Abstract: 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.
LIU Xiao-feng(刘晓锋)1, GUAN Zhi-wei(关志伟)1, SONG Yu-qing(宋裕庆)1, CHEN Da-shan(陈大山)2
(1. School of Automotive and Transportation, Tianjin University of Technology and Education,
Tianjin 300222, China;
2. Faculty of Transportation Engineering, Huaiyin Institute of Technology, Huai’an 223003, China)
Abstract: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.
Key words:unmanned aerial vehicle; traffic surveillance; route planning; multi-objective optimization; evolutionary algorithm
