Automated flight planning method to facilitate the route planning process in predicted conditions

The primary purpose of this study was to elaborate a method that facilitates aircraft operation at the flight planning stage by automating the flight planning process. This paper describes the impact that external factors, such as airspace structure or weather conditions, have on flight efficiency. The proposed method was based on the discrete airspace model and a specifically designed manner of data processing in respect to the conditions data set in this model. The entire process makes it possible to interpret store data to seek and suggest the path according to user preferences. By specifying the departure and arrival aerodromes, the user obtains data about distance, flight duration, fuel consumption, route charges, overall cost of the enroute phase, and the impact of turbulences. The solution was developed using the C++ programming language. The Floyd-Warshall algorithm was applied to find the shortest (“lowest cost”) path. However, before the path seeking algorithm was employed, several methods had been used to evaluate the data inserted into the model with regard to aircraft performance and the predicted position. The predicted position within the location on the model was established using graph theory and applying a Voronoi diagram. The obtained result demonstrated that the elaborated method can be used to obtain information about benefits from individual path variants. After entering the aerodrome of departure and aerodrome of arrival requests, the user obtains a flight path according to the criteria provided in the request. As proven in the discrete airspace model, even more advantageous paths can be found than the one based on the shortest route. The elaborated method can bring benefits in a variety of transportation problems. It involves a useful solution that allows the application of the Floyd-Warshall algorithm in seeking a “low-costs” route based on more than one criterion. It may be useful in planning autonomous missions for remotely piloted aircraft systems. In aviation, the adoption of this method could even contribute to reducing the discrepancy between the planned flights submitted to the processing system and the actual network situation. That, as a result may decrease time-related deviations, and reduce the workload of Air Traffic Control Officers.