Analysis of Aircraft Ground Trajectories: Map-Matching with Open Source Data for Modeling Safety-Driven Applications

Publikation: Beitrag zu KonferenzenPaperBeigetragenBegutachtung


Increasing flight volumes and complex airport operations may affect taxi routing and pose challenges for safe and efficient aircraft ground traffic on movement areas. This can lead to extended taxiing distances affecting the aircraft motion behavior on ground, resulting in altered load dynamics on aircraft structures, notably impacting landing gear components.
Digital twin technology plays a crucial role in monitoring aircraft components, such as stress and fatigue spectra during operations, and predicting future component conditions. For monitoring and predicting loads during ground operations within a digital twin framework, the actual aircraft maneuvering trajectories have to be considered and can be modeled by utilizing different data sources containing information on the aircraft's position. However, these data are often sparse, noisy, or misaligned. Therefore, our methodology demonstrates processing and analyzing of aircraft ground maneuvering trajectories using sparse ADS-B data and geospatial airport data, achieving more realistic trajectories compared to raw ADS-B data through consistent map-matching and filtering methods. These trajectories can enhance motion representation accuracy of modeling approaches for load monitoring within safety-driven digital twin applications.
Titel in Übersetzung
Analyse von Luftfahrzeug-Bodentrajektorien: Map-Matching mit Open-Source-Daten zur Modellierung sicherheitsrelevanter Anwendungen


PublikationsstatusAngenommen/Im Druck - 8 Apr. 2024


Titel11th International Conference on Research in Air Transportation
KurztitelICRAT 2024
Dauer1 - 4 Juli 2024
BekanntheitsgradInternationale Veranstaltung
OrtNanyang Technological University



  • trajectory modeling, map-matching, aircraft ground maneuvers, data analytics, aircraft component safety