Individual Prediction Modelling for Air Traffic Control using Supervised Learning

In the future, Air Traffic Controllers are expected to work together with more advanced computer-based automation that can automatically take action. The main challenge is then how to design computer-based tools such that they foster acceptance among air traffic controllers. One possible approach to foster acceptance is by matching the automated...

Towards Explainable Automation for Air Traffic Control Using Deep Q-learning from Demonstrations and Reward Decomposition

The current ATC system is seen as the most significant limitation to coping with an increased air traffic density. Transitioning towards an ATC system with a high degree of automation is essential to cope with future traffic demand of the airspace. In recent studies, reinforcement learning has shown promising results automating Conflict...

Implicit Coordinated Tactical Avoidance for UAVs within a Geofenced Airspace

This research presents the derivation, implementation and safety assessment of a velocity obstacle- based conflict resolution method to be used by UAVs flying within a horizontally restricted airspace by a geofence under the presence of wind. Two parameters indicating the safety of the applied conflict resolution method have been measured, i.e.,...

A Decentralized Recovery Method for Air Traffic Conflicts

In an effort to increase airspace capacity, new methods for the decentralization of air traffic control have been a topic for research since the early nineties. The Modified Voltage Potential is a method to provide decentralized conflict detection and resolution. Through this method, aircraft can fly direct routes while resolving conflicts in a...

Supporting Discovery Learning in Air Traffic Control through Ecological Interfaces

In an effort to further evaluate the effects of Ecological Interface Design on acquiring expertise, this paper presents the results of an investigation into how Ecological Interface Design could possibly promote discovery learning processes in the Air Traffic Control domain through the application of an instructional design model, and how it...

Personalized Automation for Air Traffic Control using Convolutional Neural Networks

In the upcoming years, en route airspace capacity will be limited by air traffic controller workload, requiring the introduction of automation to assist controllers with conflict detection and resolution. However, acceptance is considered to be one of the main obstacles in the introduction of novel automation. Individual-sensitive automation has...

Coordination in Multi-Actor Self-Separation in Complex Airspace Environments: A human-in-the-loop experiment using the Solution Space Diagram

The Air Traffic Management research community expects that the responsibility of maintaining a minimum safe separation distance between aircraft will move from the groundbased Air Traffic Control, a centralized system, towards the flight deck, a decentralized system. Previous research on the decentralized, also known as distributed Air Traffic...

Multi-aircraft Conflict Resolution using Velocity Obstacles

Currently, Air Traffic Control is responsible for the separation of air traffic in our limited airspace. To facilitate the continuing growth of air traffic, an ambitious plan is to give the responsibility of the separation task to the pilots of the aircraft. The behavior of existing conflict resolution methods within this decentralized approach...