125 citations · 179 across the 16 of their papers we have counts for
16 papers
Graph-based Complexity Forecasts in UK En Route Airspace Using Relevant Aircraft Interactions
Edward Henderson, George De Ath, Nick Pepper
Effectively managing Air Traffic Control Officer (ATCO) workload is crucial in maintaining operational safety. Group supervisors use tools that estimate upcoming traffic load to ai…
Human-in-the-Loop Testing of AI Agents for Air Traffic Control with a Regulated Assessment Framework
Ben Carvell, Marc Thomas, Andrew Pace +7
We present a rigorous, human-in-the-loop evaluation framework for assessing the performance of AI agents on the task of Air Traffic Control, grounded in a regulator-certified simul…
Online Action-Stacking Improves Reinforcement Learning Performance for Air Traffic Control
Ben Carvell, George De Ath, Eseoghene Benjamin +1
We introduce online action-stacking, an inference-time wrapper for reinforcement learning policies that produces realistic air traffic control commands while allowing training on a…
A Future Capabilities Agent for Tactical Air Traffic Control
Paul Kent, George De Ath, Martin Layton +3
Escalating air traffic demand is driving the adoption of automation to support air traffic controllers, but existing approaches face a trade-off between safety assurance and interp…
A Probabilistic Digital Twin of UK En Route Airspace for Training and Evaluating AI Agents for Air Traffic Control
Nick Pepper, Adam Keane, Amy Hodgkin +11
This paper presents the first probabilistic Digital Twin of operational en route airspace, developed for the London Area Control Centre. The Digital Twin is intended to support the…
AirTrafficGen: Configurable Air Traffic Scenario Generation with Large Language Models
Dewi Sid William Gould, George De Ath, Ben Carvell +1
The manual design of scenarios for Air Traffic Control (ATC) training is a demanding and time-consuming bottleneck that limits the diversity of simulations available to controllers…
Air Traffic Controller Task Demand via Graph Neural Networks: An Interpretable Approach to Airspace Complexity
Edward Henderson, Dewi Gould, Richard Everson +2
Real-time assessment of near-term Air Traffic Controller (ATCO) task demand is a critical challenge in an increasingly crowded airspace, as existing complexity metrics often fail t…
Context-Aware Generative Models for Prediction of Aircraft Ground Tracks
Nick Pepper, George De Ath, Marc Thomas +2
Trajectory prediction (TP) plays an important role in supporting the decision-making of Air Traffic Controllers (ATCOs). Traditional TP methods are deterministic and physics-based,…
MBORE: Multi-objective Bayesian Optimisation by Density-Ratio Estimation
George De Ath, Tinkle Chugh, Alma A. M. Rahat
Optimisation problems often have multiple conflicting objectives that can be computationally and/or financially expensive. Mono-surrogate Bayesian optimisation (BO) is a popular mo…
How Bayesian Should Bayesian Optimisation Be?
George De Ath, Richard Everson, Jonathan Fieldsend
Bayesian optimisation (BO) uses probabilistic surrogate models - usually Gaussian processes (GPs) - for the optimisation of expensive black-box functions. At each BO iteration, the…
Asynchronous ε-Greedy Bayesian Optimisation
George De Ath, Richard M. Everson, Jonathan E. Fieldsend
Batch Bayesian optimisation (BO) is a successful technique for the optimisation of expensive black-box functions. Asynchronous BO can reduce wallclock time by starting a new evalua…
What do you Mean? The Role of the Mean Function in Bayesian Optimisation
George De Ath, Jonathan E. Fieldsend, Richard M. Everson
Bayesian optimisation is a popular approach for optimising expensive black-box functions. The next location to be evaluated is selected via maximising an acquisition function that…
-shotgun: -greedy Batch Bayesian Optimisation
George De Ath, Richard M. Everson, Jonathan E. Fieldsend +1
Bayesian optimisation is a popular, surrogate model-based approach for optimising expensive black-box functions. Given a surrogate model, the next location to expensively evaluate…
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
George De Ath, Richard M. Everson, Alma A. M. Rahat +1
The performance of acquisition functions for Bayesian optimisation to locate the global optimum of continuous functions is investigated in terms of the Pareto front between explora…
Visual Object Tracking: The Initialisation Problem
George De Ath, Richard Everson
Model initialisation is an important component of object tracking. Tracking algorithms are generally provided with the first frame of a sequence and a bounding box (BB) indicating…
Part-based Tracking by Sampling
George De Ath, Richard M. Everson
We propose a novel part-based method for tracking an arbitrary object in challenging video sequences. The colour distribution of tracked image patches on the target object are repr…