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An optimization model of UAV route planning for road segment surveillance

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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.

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Authors and Affiliations

  1. School of Automotive and Transportation, Tianjin University of Technology and Education, Tianjin, 300222, China

    Xiao-feng Liu  (刘晓锋), Zhi-wei Guan  (关志伟) & Yu-qing Song  (宋裕庆)

  2. Faculty of Transportation Engineering, Huaiyin Institute of Technology, Huai’an, 223003, China

    Da-shan Chen  (陈大山)

Authors
  1. Xiao-feng Liu  (刘晓锋)
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  2. Zhi-wei Guan  (关志伟)
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  3. Yu-qing Song  (宋裕庆)
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  4. Da-shan Chen  (陈大山)
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Corresponding author

Correspondence to Xiao-feng Liu  (刘晓锋).

Additional information

Foundation item: Project(2009AA11Z220) supported by National High Technology Research and Development Program of China; Projects(61070112, 61070116) supported by the National Natural Science Foundation of China; Project(2012LLYJTJSJ077) supported by the Ministry of Public Security of China; Project(KYQD14003) supported by Tianjin University of Technology and Education, China

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Liu, Xf., Guan, Zw., Song, Yq. et al. An optimization model of UAV route planning for road segment surveillance. J. Cent. South Univ. 21, 2501–2510 (2014). https://doi.org/10.1007/s11771-014-2205-z

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  • DOI: https://doi.org/10.1007/s11771-014-2205-z

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