Improved F-RRT ∗ Algorithm for Flight-Path Optimization in Hazardous Weather

Abstract

Hazardous weather has become a major cause of flight delays in recent years. With the development of satellite navigation systems, the study of flight-path optimization under hazardous weather conditions has become especially important. In this study, radar data were used as the basis for the initial flight-restricted area under hazardous weather conditions, and the Graham algorithm was used to delineate the dynamic flight-restricted area by comprehensively considering the hazardous weather boundary changes along with the speed and direction. Then, under the grid environment model, the range of influence, size, and distribution characteristics of the flight-restricted area was examined, and the path optimization model was created according to constraints related to the path distance, corner size, and number of turning points. An improved F-RRT ${}^{\ast }$ algorithm was developed to solve the model. The algorithm can overcome the problems of traditional path planning algorithms, such as strong randomness, poor guidance, slow convergence speed, unsmooth paths, and poor tracing smoothness. Finally, a simulation analysis was conducted on the Guiyang–Guangzhou route in China as an example. This study can address the drawbacks of existing research on route change and provide sufficient theoretical support and reference for the implementation of specific route change plans in the future.