Agent-based modeling to support collaborative decision making in predictable airport ground operations

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Inside the complex air traffic network, delay occurring at the aircraft stand and related ground processes has the potential to propagate and so increase. This “butterfly effect” typically has a significant negative impact on the downstream
flights and airports. Efficient aircraft ground operations can help stabilize the in- and outbound aircraft operations and, in some cases, reduce knock-on effects. Reliably forecasting possible bottlenecks at a dedicated airport and its management is key to optimally using resources and applying appropriate strategies. In this research, we implement the digital twin of a selected airport
section, Pier H of Amsterdam Schiphol airport, to simulate the aircraft ground operations throughout the course of a single day using an agent-based model. The agents’ behavior representing various ground handling operators is considered for an optimized collaborative decision making process. The consequences derived from operational needs will be demonstrated, and the remedies to reduce operational stress will be put to the test. The findings
and lessons offer the possibilities for predictable airport ground operations, both in terms of strategic and tactical planning as well as operations.

Details

OriginalspracheEnglisch
TitelSESAR Innovation Days 2022
Seiten1-8
Seitenumfang8
PublikationsstatusVeröffentlicht - Dez. 2022
Peer-Review-StatusJa

Externe IDs

ORCID /0009-0005-7833-7169/work/184005036

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

  • aircraft ground operations, airport collaborative decision making, agent-based model and simulation, digital twin