Real-time Unmanned Aerial Vehicle Cruise Route Optimization for Road Segment Surveillance using Decomposition Algorithm

被引:14
|
作者
Liu, Xiaofeng [1 ]
Ma, Jian [2 ]
Chen, Dashan [3 ]
Zhang, Li-Ye [4 ]
机构
[1] Tianjin Univ Technol & Educ, Sch Automot & Transportat, Tianjin 300222, Peoples R China
[2] Suzhou Univ Sci & Technol, Sch Civil Engn, Suzhou 215011, Jiangsu, Peoples R China
[3] Shanghai Inst Technol, Sch Railway Transportat, Shanghai 201418, Peoples R China
[4] ASTAR, Inst High Performance Comp, Singapore 138632, Singapore
关键词
Unmanned aerial vehicle; Traffic monitoring; Route planning; Multi-objective optimization; Road segment; GENETIC ALGORITHM; MOEA/D; MODEL;
D O I
10.1017/S0263574720000867
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Unmanned aerial vehicle (UAV) was introduced for nondeterministic traffic monitoring, and a real-time UAV cruise route planning approach was proposed for road segment surveillance. First, critical road segments are defined so as to identify the visiting and unvisited road segments. Then, a UAV cruise route optimization model is established. Next, a decomposition-based multi-objective evolutionary algorithm (DMEA) is proposed. Furthermore, a case study with two scenarios and algorithm sensitivity analysis are conducted. The analysis result shows that DMEA outperforms other two commonly used algorithms in terms of calculation time and solution quality. Finally, conclusions and recommendations on UAV-based traffic monitoring are presented.
引用
收藏
页码:1007 / 1022
页数:16
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