Identification of Robust Routes using Convective Weather Forcasts
Name
Balakrishnan_IdentificationOf.pdf
Size
564.98 KB
Format
Adobe PDF
Checksum (MD5)
5afb2a9c3871f2deda57f79db5aa2f36
Author(s)
Michalek, Diana
Balakrishnan, Hamsa
Date Issued
June 2009
Journal
USA/Europe Air Traffic Management Research and Development Seminar, 8th (ATM2009)
Publisher
Eurocontrol
Citation
Michalek, Diana and Hamsa Balakrishnan. "Identification of Robust Routes using Convective Weather Forcasts." Eighth USA/Europe Air Traffic Management Research and Development Seminar (ATM2009), Napa, California, June 29-July 2 2009. Paper 124.
Version
Author's final manuscript
Abstract
Convective weather is responsible for large delays and widespread disruptions in the U.S. National Airspace System (NAS), especially during summer months when travel demand is high. This has been the motivation for Air Traffic Flow Management (ATFM) algorithms that optimize flight routes in the presence of reduced airspace and airport capacities. These models assume either the availability of reliable probabilistic weather forecasts or accurate predictions of robust routes; unfortunately, such forecasts do not currently exist. This paper adopts a data-driven approach that identifies robust routes and derives stochastic capacity forecasts from deterministic convective weather forecasts. Using techniques from machine learning and extensive data sets of forecast and observed convective weather, the proposed approach classifies routes that are likely to be viable in reality. The resultant model for route robustness can also be mapped into probabilistic airspace capacity forecasts.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Sloan School of Management
Terms of Use
Attribution-Noncommercial-Share Alike 3.0 Unported
Persistent DSpace Link
DOI of Published Version
http://www.atmseminar.org/8th-seminar-united-states-june-2009/papers/paper_124/view
