Knowledge-based scheduling of arrival aircraft in the terminal area

Krzeczowski, K.; Davis, Thomas J.; Erzberger, Heinz; Lev-Ram, Israel; Bergh, C.

doi:10.2514/6.1995-3366

Cited by 6 publications

(1 citation statement)

References 4 publications

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“…Extensive simulation and operational assessment of pFAST has shown a high level of schedule acceptance can be achieved by considering all merge locations in the TRACON; an acceptable result was never achieved by only considering the threshold scheduling constraint. 9 While pFAST demonstrated the importance of considering all TRACON merge locations in producing an acceptable schedule, the fidelity to which it modeled American Institute of Aeronautics and Astronautics these merge locations does not fully support active advisories. Passive FAST modeled the arrival merge locations as static merge points, while they in fact can move within the defined airspace.…”

Section: Previous Studiesmentioning

confidence: 99%

A knowledge-based conflict resolution algorithm for terminal area air traffic control advisory generation

Isaacson

Robinson

2001

AIAA Guidance, Navigation, and Control Conference and Exhibit

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NASA researchers, working under the Aviation System Capacity Program and in conjunction with the FAA Free Flight Program Office, have developed a set of decision support tools to assist terminal area air traffic controllers with control of arrival and departure traffic. Two of these tools, the Final Approach Spacing Tool (FAST) and the Expedite Departure Path (EDP) tool, provide air traffic controllers with heading, speed and altitude advisories to assist in spacing aircraft. This paper describes the conflict prediction and resolution algorithm shared by aFAST and EDP to produce conflict-free aircraft trajectories with realistic conflict resolution maneuvers. The process is accomplished in three stages: prediction, classification and resolution. A conflict prediction scheme is documented which incorporates all applicable FAA separation requirements, including automatic detection of separation during transition from staggered to simultaneous parallel approach operations. A method of classifying predicted conflicts with a limited set of criteria is detailed. Finally, a knowledge-based conflict resolution process is presented which allows for resolution of predicted conflicts in a manner consistent with controller practice: including prioritization of resolution tactics and mixture of multiple degrees of freedom to achieve separation. The scheme has been employed in both closed-loop simulations to determine solution stability and controller-in-the-loop simulations to begin development of the resolution tactics knowledge base.

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Section: Previous Studiesmentioning

confidence: 99%

A knowledge-based conflict resolution algorithm for terminal area air traffic control advisory generation

Isaacson

Robinson

2001

AIAA Guidance, Navigation, and Control Conference and Exhibit

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The Center-Tracon Automation System: Simulation and Field Testing

Denery

Erzberger

1997

Modelling and Simulation in Air Traffic Management

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SummaryA new concept for air traffic management in the terminal area, implemented as the Center-TRACON Automation System, has been under development at NASA Ames in a cooperative program with the FAA since 1991. The development has been strongly influenced by concurrent simulation and field site evaluations. The role of simulation and field activities in the development process will be discussed. Results of recent simulation and field tests will be presented.

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An Aircraft Sequencing Approach Based on Fuzzy Petri-net

Sun

Ke-qiang

2009

2009 International Joint Conference on Computational Sciences and Optimization

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Knowledge-based scheduling of arrival aircraft in the terminal area

Cited by 6 publications

References 4 publications

A knowledge-based conflict resolution algorithm for terminal area air traffic control advisory generation

A knowledge-based conflict resolution algorithm for terminal area air traffic control advisory generation

The Center-Tracon Automation System: Simulation and Field Testing

An Aircraft Sequencing Approach Based on Fuzzy Petri-net

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