2 research outputs found
Informed scenario-based RRT* for aircraft trajectory planning under ensemble forecasting of thunderstorms
Thunderstorms represent a major hazard for flights, as they compromise the safety of both the
airframe and the passengers. To address trajectory planning under thunderstorms, three variants
of the scenario-based rapidly exploring random trees (SB-RRTs) are proposed. During an iterative
process, the so-called SB-RRT, the SB-RRT* and the Informed SB-RRT* find safe trajectories by
meeting a user-defined safety threshold. Additionally, the last two techniques converge to solutions
of minimum flight length. Through parallelization on graphical processing units the
required computational times are reduced substantially to become compatible with near real-time
operation. The proposed methods are tested considering a kinematic model of an aircraft flying
between two waypoints at constant flight level and airspeed; the test scenario is based on a
realistic weather forecast and assumed to be described by an ensemble of equally likely members.
Lastly, the influence of the number of scenarios, safety margin and iterations on the results is
analyzed. Results show that the SB-RRTs are able to find safe and, in two of the algorithms, closeto-
optimum solutions.This work has received funding from (1) the Spanish Government (Project RTI2018-098471-B-C32) and (2) the SESAR Joint
Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 783287