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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

An expert system for air traffic control system

The objective was to design a control logic which automates all or part of the guidance function for air traffic control systems. Particular interest was focused on automation of the terminal area control system. A preliminary study was done on the development of an expert system. The system may be used to assist controllers by providing them with feasible options in guiding each aircraft in the control area to its desired destination.

Sensui, Takashi↗
NASA NTRS2001

Identification of Communication and Coordination Issues in the US Air Traffic Control System

Today's air traffic control system is approaching the point of saturation, as evidenced by increasing delays across the National Airspace System (NAS). There exists an opportunity to enhance NAS efficiency and reduce delays by improving strategic communication throughout the ATC system. Although several measures have been taken to improve communication (e.g., Collaborative Decision Making tools), communication issues between ATC facilities remain. It is hypothesized that by identifying the key issues plaguing inter-facility strategic communication, steps can be taken to enhance these communications, and therefore ATC system efficiency. In this report, a series of site visits were performed at Boston and New York ATC facilities as well as at the Air Traffic Control System Command Center. The results from these site visits were used to determine the current communication and coordination structure of Traffic Management Coordinators, who hold a pivotal role in inter-facility communications. Several themes emerged from the study, including: ambiguity of organizational structure in the current ATC system, awkward coordination between ATC facilities, information flow issues, organizational culture issues, and negotiation behaviors used to cope with organizational culture issues.

Davison, Hayley J.↗
NASA NTRS2004

Transforming the NAS: The Next Generation Air Traffic Control System

The next-generation air traffic control system must be designed to safely and efficiently accommodate the large growth of traffic expected in the near future. It should be sufficiently scalable to contend with the factor of 2 or more increase in demand expected by the year 2020. Analysis has shown that the current method of controlling air traffic cannot be scaled up to provide such levels of capacity. Therefore, to achieve a large increase in capacity while also giving pilots increased freedom to optimize their flight trajectories requires a fundamental change in the way air traffic is controlled. The key to achieving a factor of 2 or more increase in airspace capacity is to automate separation monitoring and control and to use an air-ground data link to send trajectories and clearances directly between ground-based and airborne systems. In addition to increasing capacity and offering greater flexibility in the selection of trajectories, this approach also has the potential to increase safety by reducing controller and pilot errors that occur in routine monitoring and voice communication tasks.

Erzberger, Heinz↗
NASA NTRSDate not supplied

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically ATCSCC planning telecon audio transcriptions. The Air Traffic Control System Command Center (ATCSCC) hosts bihourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. ITN is the process of converting un-formatted "raw'' speech-to-text transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With a preliminary overall Word Error Rate with Punctuation and Capitalization (WER PC) of 8.26, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

Air Traffic Management↗
NASA NTRS1965

Effects of the Air Traffic Control System on the Supersonic Transport

A study of the problems anticipated with the introduction of the supersonic transport into the air traffic control system indicated that supersonic transport design allowances for time and fuel for maneuvering during climbouts may not be sufficient, that there is a greater communications-navigation work- load for the supersonic transport than for the subsonic jet transport during descent, and that use of a flight director to command pitch control guidance for the pilot would be helpful.

Norman S. Silsby↗
NASA NTRSDate not supplied

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗
NASA NTRSDate not supplied

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗