Propagation of trained flight performance and observed anomalies to air traffic models

Hyunseong Lee, Guoyi Li, Ashwin Rai, Aditi Chattopadhyay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An integrated monitoring framework is developed in this work to detect in-flight performance anomalies in aircraft and investigate the propagation of observed anomalies. A robust detection algorithm is developed and trained using a historical flight dataset recorded from commercial aircrafts to detect flight performance anomalies in real-time, which significantly deviates from normal behavior. Additionally, an air traffic simulator is utilized to integrate aircraft level flight information to airspace. The detected performance anomalies are then introduced in air traffic interface and the impact of aircraft level anomalies on large-scale air traffic system is investigated.

Original languageEnglish (US)
Title of host publicationAIAA Aviation 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105890
DOIs
StatePublished - 2019
EventAIAA Aviation 2019 Forum - Dallas, United States
Duration: Jun 17 2019Jun 21 2019

Publication series

NameAIAA Aviation 2019 Forum

Conference

ConferenceAIAA Aviation 2019 Forum
Country/TerritoryUnited States
CityDallas
Period6/17/196/21/19

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Aerospace Engineering

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