Uncorrelated Encounter Model of the National Airspace System, Version 1.0

Abstract

Airspace encounter models, covering close encounter situations that may occur after standard separation assurance has been lost, are a critical component in the safety assessment of aviation procedures and collision avoidance systems. Of particular relevance to unmanned aircraft systems (UAS) is the potential for encountering general aviation aircraft that are flying under visual flight rules (VFR) and which may not be in contact with air traffic control. In response to the need to develop a model of these types of encounters, Lincoln Laboratory undertook an extensive radar data collection and modeling effort involving more than 120 sensors across the U.S. This report describes the structure and content of that encounter model. The model is based on the use of Bayesian networks to represent relationships between dynamic variables and to construct random aircraft trajectories that are statistically similar to those observed in the radar data. The result is a framework from which representative intruder trajectories can be generated and used in fast-time Monte-Carlo simulations to provide accurate estimates of collision risk.

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Document Details

Document Type
Technical Report
Publication Date
Nov 14, 2008
Accession Number
ADA489955

Entities

People

  • J. D. Griffith
  • J. K. Kuchar
  • L. P. Espindle
  • M. J. Kochenderfer

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Traffic
  • Aircrafts
  • Bayesian Networks
  • Collision Avoidance
  • Collision Avoidance Systems
  • Computational Science
  • Feature Extraction
  • Information Science
  • Machine Learning
  • Monte Carlo Method
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Test And Evaluation
  • Unmanned Aerial Vehicles
  • Unmanned Systems

Fields of Study

  • Environmental science

Readers

  • Aviation Science / Aeronautics.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy
  • Space