Regression analysis of top of descent location for idle-thrust descents

Stell, Laurel and Bronsvoort, Jesper and McDonald, Greg (2013). Regression analysis of top of descent location for idle-thrust descents. In: "Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013)", 10/06/2013 - 13/06/2013, Chicago, IL, USA. pp..

Description

Title: Regression analysis of top of descent location for idle-thrust descents
Author/s:
  • Stell, Laurel
  • Bronsvoort, Jesper
  • McDonald, Greg
Item Type: Presentation at Congress or Conference (Article)
Event Title: Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013)
Event Dates: 10/06/2013 - 13/06/2013
Event Location: Chicago, IL, USA
Title of Book: Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013)
Date: 2013
Subjects:
Freetext Keywords: Idle-thrust descents; trajectory prediction; top of de- scent; flight management system
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (290kB) | Preview

Abstract

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. In addition to recording TOD, the cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also identified for use as the independent variables in the regression analysis. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajectory parame- ters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowledge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace.

More information

Item ID: 29791
DC Identifier: http://oa.upm.es/29791/
OAI Identifier: oai:oa.upm.es:29791
Deposited by: Memoria Investigacion
Deposited on: 20 Jul 2014 07:36
Last Modified: 22 Apr 2016 00:10
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM