Low Complexity Algorithms for Mission Completion Time Minimization in UAV-Based Emergency Response

Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

2 Lataukset (Pure)

Abstrakti

The integration of unmanned aerial vehicles (UAVs) with wireless communication systems greatly enhances the application area of intelligent transportation systems (ITS). One of the mission-critical applications enabled by these systems is disaster management, where communication functionality can provide users with supplementary information such as escape routes, time to rescue, etc. In this paper, considering a large area with several locations of interest, we formulate and solve the optimization problem of delivering critical information by optimizing the UAV speed and the order of visits to the locations of interest so that the mission time is minimized. The formulated problem is a mixed integer nonlinear program, which is quite challenging to solve. To reduce the complexity of solution algorithms, we propose two circular trajectory designs. The first algorithm finds the optimal velocity and radius of the circular trajectories of the UAV. The second algorithm finds the optimal connections to join the individual circular trajectories. An important practical benefit of using circular trajectory design is that it can be implemented through either fixed-wing or rotary-wing UAVs. Our numerical results reveal that, with practical simulation parameters, the proposed single circular trajectory design provides a time saving of at least 30% as compared to existing zigzag trajectory design. Moreover, the proposed multiple circular trajectory design cuts the total mission completion time by at least 7 times as compared to proposed single circular trajectory design.

AlkuperäiskieliEnglanti
Sivumäärä16
JulkaisuIEEE Transactions on Intelligent Vehicles
DOI - pysyväislinkit
TilaE-pub ahead of print - 2024
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 2

!!ASJC Scopus subject areas

  • Automotive Engineering
  • Control and Optimization
  • Artificial Intelligence

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