Lagrangian Delay Predictive Model for Sector-Based Air Traffic Flow

Abstract

We derive a control theoretic model of sector-based air traffic flow using hybrid automata theory. This model is Lagrangian, meaning that it models the properties of the system along its trajectories. A subset of this model is used to generate analytic predictions of air traffic congestion: we define and derive a dynamic sector capacity which we use to predict the time it takes to overload a given portion of airspace. This result links our approach with Eulerian models, which account for temporal variations of parameters in a fixed volume. We design and validate an air traffic flow simulator, to assess the accuracy of our predictions. The simulator is then used to show that flow scheduling and conflict resolution may be decorrelated under assumptions on aircraft density.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA525512

Entities

People

  • Alexandre M. Bayen
  • Claire J. Tomlin
  • George Meyer
  • Pascal Grieder

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Air Traffic
  • Air Traffic Control Systems
  • Air Traffic Controllers
  • Aircrafts
  • Automata
  • Automata Theory
  • Computational Complexity
  • Control Systems
  • Cross Flow
  • Lists (Data Structures)
  • Mathematical Analysis
  • Mathematical Models
  • Predictive Modeling
  • Simulations
  • Simulators
  • Traffic
  • Travel Time

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aviation Safety and Air Traffic Management
  • Computational Modeling and Simulation

Technology Areas

  • Space