Corpus ID: 109873069

Modeling Air Traffic Management Technologies With a Queuing Network Model of the National Airspace System

  title={Modeling Air Traffic Management Technologies With a Queuing Network Model of the National Airspace System},
  author={Long Dou and A Lee David and Johnson Jesse and M Gaier Eric and F Kostiuk Peter},
This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -- Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and… Expand
Air-Traffic Uncertainty Models for Queuing Analysis
*† ‡ The national airspace system (NAS) is a highly complex and intricate dynamical network of airports, airways, navigation systems and other air traffic components. Numerous factors influence theExpand
Queuing Network Models of the National Airspace System
Understanding the relationships between trajectory uncertainties due to aviation operations, precision of navigation and control, and the traffic flow efficiency are central to the design of nextExpand
Formulation of a Method to Assess Technologies for the Improvement of Airport Capacity
Commercial air transportation growth and airline deregulation in recent years have resulted in traffic volume beyond the capacity of existing airports and air traffic control. This excess trafficExpand
Queueing Network Models of the National Airspace System
A methodology for incorporating the trajectory uncertainty models into queuing network models of the air traffic at national, regional and local scales is discussed and usefulness of these models in assessing the impact of uncertainties on traffic flow efficiency is illustrated. Expand
Modeling Air-Traffic Service Time Uncertainties for Queuing Network Analysis
This study focuses on identifying various air traffic uncertainty sources and deriving the associated mathematical models of service time distributions that provide the distributions given air traffic uncertainties through analytical expressions without resorting to computationally expensive Monte-Carlo simulations. Expand
Trajectory Uncertainty Modeling for Queuing Analysis of the National Airspace System
An important step in the design of next-generation air-traffic system is that of assessing the impact of uncertainty and precision on traffic flow efficiency. Queuing models provide an efficientExpand
Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty
A critical review of recent developments in the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion is provided. Expand
Applications of Operations Research in the Air Transport Industry
An overview of several important areas of operations research applications in the air transport industry, including the various stages of aircraft and crew schedule planning; revenue management; and the planning and operations of aviation infrastructure (airports and air traffic management). Expand
A Framework for Stochastic Air Traffic Flow Modeling and Analysis
A framework for stochastic traffic flow modeling over the U. S. National airspace based on queuing network models is advanced. The proposed framework allows the inclusion of a wide variety ofExpand
A Method for Forecasting the Commercial Air Traffic Schedule in the Future
This report presents an integrated set of models that forecasts air carriers'' future operations when delays due to limited terminal-area capacity are considered. This report models the industry as aExpand


Estimating the Effects of the Terminal Area Productivity Program
The report describes methods and results of an analysis of the technical and economic benefits of the systems to be developed in the NASA terminal Area Productivity (TAP) program. A runway capacityExpand
An analysis of landing rates and separations at the Dallas/Fort Worth International Airport
Advanced air traffic management systems such as the Center/TRACON Automation System (CTAS) should yield a wide range of benefits, including reduced aircraft delays and controller workload. ToExpand
A Method for Making Cross-Comparable Estimates of the Benefits of Decision Support Technologies for Air Traffic Management
We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management and we apply a specific implementation, orExpand
Abstract A prototype decision support tool for terminal area air traffic controllers, referred to as the Final Approach Spacing Tool (FAST), was recently evaluated in operation with live air trafficExpand
Validation of Air Traffic Controller Workload Models
Abstract : During the past several years, computer models have been developed for off-site estimation of controller's workload. The inputs to these models are audio and digital data normally recordedExpand
A Closure Approximation for the Nonstationary M/M/s Queue
A computationally undemanding approximate method for finding the time dependent mean and standard deviation of the number of customers in an server queueing system with time-varying arrival and service rates is presented. Expand
Coverage of Future National Airspace System Operational Requirements
  • NASA Ames Research Center, AATT Program Office, October 21, 1997.
  • 1997
Air Carrier Investment Model (Third Generation), NASA Contractor Report
  • Air Carrier Investment Model (Third Generation), NASA Contractor Report
  • 1998
Current Market Outlook
  • Boeing Commercial Airplane Group Marketing, P.O. Box 3707,
  • 1998
Current Market Outlook, Boeing Commercial Airplane Group Marketing
  • Current Market Outlook, Boeing Commercial Airplane Group Marketing
  • 1998