OPTIMIZATION THE ROUTE OF AN UNMANNED AERIAL VEHICLE DURING THE SEARCH FOR AN AIRCRAFT THAT HAS CRASHED USING AN UNIFORMLY OPTIMAL SEARCH STRATEGY

Abstract

Unmanned aerial vehicles (UAV) have been a significant advancement in SAR operations, ushering in an era of increased technological efficiency. The seamless integration of UAV into various tasks of the aviation search and rescue process highlights their high ability to perform tasks that were once burdensome or even impossible for traditional aircraft search methods, which human factors can negatively impact them. The primary objective of SAR operations remains the rapid and accurate location of a crashed aircraft. This is followed by such important actions as handover, information exchange, and timely delivery of various supplies to victims. All this is done within time constraints. The inclusion of UAV in SAR operations offers numerous notable advantages, including ease of deployment, cost-effective maintenance, exceptional mobility, and the ability to hover in areas where human intervention may be dangerous, limited, or require rapid decision making. Also, many UAV tasks can be performed automatically, such as image segmentation, which can help -locate victims in the surveyed area. The methodology for using UAV systems in SAR type search and rescue operations covers several key components, such as operation management, risk assessment, sensor technology, and UAV route selection. This article proposes a study to substantiate an optimization the route of a fixed-wing UAV during the search for an aircraft that has crashed, using uniformly optimal search strategies. The article analyzes existing search methods, highlighting their advantages and disadvantages. In the first stage of the study, the solution to the optimization problem for a uniformly optimal search strategy is presented. At the second stage, the authors developed a flowchart for a search and rescue operation algorithm utilizing the uniformly optimal search strategy. In the third stage, the results of applying the uniformly optimal search strategy to locate an aircraft in distress are illustrated, with implementation demonstrated using the Python programming language. The study discusses the potential application of the scientific findings. Additionally, possible directions for further research are suggested, focusing on modeling aviation accidents and calculating quantitative indicators for the search method examined in the scientific publication. These directions include employing fixedwing UAV simulator as a search tool for the given task.