An efficient algorithm for smoothing airspace congestion by fine-tuning take-off times

Current technological advances in communications and navigation have improved air traffic management (ATM) with new decision support tools to balance airspace capacity with user demands. Despite agreements achieved in flying reference business trajectories (RBTs) among different stakeholders, tight spatio-temporal connectivity between trajectories in dense sectors can cause perturbations that might introduce time or space deviations into the original RBTs, thus potentially affecting other 4D trajectories. In this paper, several challenging results are presented by properly tuning the Calculated Take-Off Times (CTOTs) as a tool for mitigating the propagation of perturbations between trajectories that can readily appear in dense sectors. Based on the identification of “collective microregions”, a tool for predicting potential spatio-temporal concurrence events between trajectories over the European airspace was developed, together with a CTOT algorithm to sequence the departures that preserve the scheduled slots while relaxing tight trajectory interactions. The algorithm was tested by considering a realistic scenario (designed and analyzed in the STREAM project (Stream, 2013)) to evaluate relevant ATM KPIs that provide aggregated information about the sensitivity of the system to trajectory interactions, taking into account the system dynamics at a network level. The proposed approach contributes to enhancing the ATM capacity of airports to mitigate network perturbations.

• Record URL:
  https://doi.org/10.1016/j.trc.2014.03.017
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X14000904
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Nosedal, Jenaro
  • Piera, Miquel A
  • Ruiz, Sergio
  • Nosedal, Alvaro
• Publication Date: 2014-7

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: pp 171-184
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 44
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Air traffic control; Airspace (Aeronautics); Algorithms; Decision support systems; Departure time; Perturbations; Takeoff
• Geographic Terms: Europe
• Subject Areas: Aviation; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01535042
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 25 2014 7:43AM