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

Published online by Cambridge University Press:  14 September 2020

Xiaofeng Liu Open the ORCID record for Xiaofeng Liu [Opens in a new window] ,
Jian Ma ,
Dashan Chen  and
Li-Ye Zhang
Xiaofeng Liu*
Affiliation:
School of Automotive and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China
Jian Ma
Affiliation:
School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215011, Jiangsu, China E-mail: 9764634@qq.com
Dashan Chen
Affiliation:
School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China E-mail: logtop@126.com
Li-Ye Zhang
Affiliation:
Institute of High Performance Computing, A*STAR, Singapore 138632, Singapore E-mail: zhangly@ihpc.astar.edu.sg
*
*Corresponding author. E-mail: microbreeze@126.com
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Summary

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.

Keywords

Unmanned aerial vehicleTraffic monitoringRoute planningMulti-objective optimizationRoad segment
Type
Article
Information
Robotica , Volume 39 , Issue 6 , June 2021 , pp. 1007 - 1022
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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