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The purpose of this study is to provide an alternative graph-based airspace model for more effective free-route flight planning.

Based on graph theory and available data sets describing airspace, as well as weather phenomena, a new FRA model is proposed. The model is applied for near to optimal flight route finding. The software tool developed during the study and complexity analysis proved the applicability and timed effectivity of the flight planning approach.

The sparse bidirectional graph with edges connecting only (geographically) closest neighbours can naturally model local airspace and weather phenomena. It can be naturally applied to effective near to optimal flight route planning.

Practical results were acquired for one country airspace model.

More efficient and applicable flight planning methodology was introduced.

Aircraft following the new routes will fly shorter trajectories, which positively influence on the natural environment, flight time and fuel consumption.

The airspace model proposed is based on standard mathematical backgrounds. However, it includes the original airspace and weather mapping idea, as well as it enables to shorten flight planning computations.

This study presents an image processing algorithm capable of calculating selected flight parameters requested by flight control systems to guide aircraft along the horizontal projection of the landing trajectory. The parameters identified based on the basics of the image of the Calvert light system appearing in the on-board video system are used by flight control algorithms that imitate the pilot’s schematics of control. Controls were generated using a fuzzy logic expert system. This study aims to analyse an alternative to classical solutions that can be applied to some specific cases.

The paper uses theoretical discussions and breakdowns to create the basics for the development of structures for both image processing algorithms and control algorithms. An analytical discussion on the first stage was transformed into laboratory rig tests using a real autopilot unit. The results of this research were verified in a series of software-in-the-loop computer simulations.

The image processing method extracts the most crucial parameters defining the relative position of the aircraft to the runway, as well as the control algorithm that uses it.

In flight control systems that do not use any dedicated ground or satellite infrastructure to land the aircraft.

This paper presents the original approach of the author to aircraft control in cases where visual signals are used to determine the flight trajectory of the aircraft.