'library2.bib'
- 'Evolution.bib'
title: Online Learning for Ground Trajectory Prediction
---

Air Traffic Control, Trajectory Prediction, Hybrid System, Total-Energy Model, Black-Box Optimization, Machine Learning

Introduction {#sec:intro}
============

Trajectory Prediction (TP) is the core component of automated systems in Air Traffic Control (ATC). Many functionalities of the Decision Support Tool directly rely on an accurate TP: controller posting, workload estimation, arrival sequencing, loss of separation detection, and conflict resolution, to name the most prominent ones. As a consequence, TP is the weakness of the current automation ATC systems and a major issue in the ATC research community, even more with the new paradigmatic shift toward 4D trajectories in both the SESAR Joint Undertaking and the NextGen project. The challenge is to reduce the uncertainty of the prediction of the aircraft states on a temporal horizon of at least 20 minutes. To achieve this, the information of the current state of the aircraft and its environment shall be reliable. As a matter of fact, the Flight Management System (FMS) has access to the measurements from the sensors of the aircraft and creates its own TP, which is updated frequently. Therefore, we should expect that this TP is the most accurate one. Thanks 