A Framework for Unlocking Hidden Air Traffic Management Data Sources Through Advanced Technologies

Our proposed innovation, Air Traffic Language Analysis System for Coordination, Operational Prediction, and Enhancement (ATLASCOPE), is an Artificial Intelligence-based airspace service that improves the efficiency of traditional civil aviation missions in the near-term NAS, thus directly addressing Subtopic A3.01. ATLASCOPE does this by unlocking crucial ATM information hidden in unstructured, non-traditional data sources. A key example is unpublished traffic management initiatives (TMIs) that are negotiated between FAA facilities via phone conversations and implemented without being published via SWIM or other sources. Lack of information on these TMIs prevents airlines from making preemptive adjustments to minimize impact to their networks, leading to significant, avoidable operating costs. Information on unpublished TMIs can be inferred indirectly from controller-pilot conversations. ATLASCOPE Monitors these voice comm data feeds, Converts the audio to text, Extracts crucial information from the text via AI-based NLP, and Provides insights and predictions based on this information to airlines and other NASA Digital Information Platform (DIP) users. ATLASCOPE supports NASA ATM-X’s DIP sub-project’s plans for demonstrating the pre-departure rerouting digital service (called CDDR) in the SNFP-Ops demos, by providing a hitherto unavailable source of information on the impact of unpublished TMIs on departure route capacities and departure delays. This increases the effectiveness of CDDR. The SBIR brings together an innovative approach for creating training datasets for fine-tuning audio-to-text conversion Large Language Models, cutting-edge AI model training techniques that avoid pitfalls of over- and under-fitting, and an innovative flight track processing-based approach for creating unpublished TMI activity truth dataset. The anticipated Phase I result is demonstration of the ATLASCOPE prototype on one or more historical unpublished TMIs scenarios.
Benefits: The proposed innovation is applicable to a wide array of NASA projects because ATLASCOPE can be leveraged to unlock hidden information in numerous unstructured aviation data sources relevant to several NASA project needs. These include the following NASA applications: (1) A Traffic Management Initiative (TMI) Detection Service for supporting NASA Digital Information Platform’s (DIP’s) CDDR service: ATLASCOPE can help DIP’s pre-/post-departure rerouting service (CDDR) and airline fleet-wide IROPS management capabilities by detecting unpublished TMIs and predicting their impact on airspace capacity and delays. Thus, ATLASCOPE improves the effectiveness and benefits of DIP capabilities to the airspace users, and supports the successful accomplishment of the planned Sustainable Flight National Partnership – Operations (SNFP-Ops) demonstration objectives. (2) TMI impact predictor service for supporting NASA NAS Digital Twin simulations: ATLASCOPE can enhance air traffic simulations for evaluating decision support tools that require ATC voice comms-derived information such as unpublished TMI impacts, airport/airspace safety events detection, and TFM coordination activity tracking. (3) NAS voice communications transcription and analytics methods to support NASA System-Wide Safety project’s In-Time Aviation Safety Management System research: ATLASCOPE can provide fused voice plus track data to detect precursors of safety incidents or instances of beneficial interventions from controllers or pilots. (4) TFM strategic telecons transcription and text mining service to support NASA NARI’s work with the FAA: ATLASCOPE’s ASR and NLP methods can improve information extraction from TFM meeting recordings. (5) NLP-based service to support NExCT project’s digital common operational picture for diverse and increasingly autonomous operations: ATLASCOPE can provide fusion of ATC voice comms-derived information with flight track information to build a complete operational picture. The proposed SBIR research has broad commercial application in multiple aviation and non-aviation areas. The direct application of Phase I technology, which addresses unpublished TMIs, is as a decision support aid for Airline ATC Coordinators, who will use ATLASCOPE to detect unpublished TMIs and predict airline network-wide TMI impacts. Our airline partner estimates that ATLASCOPE could save 2% gate returns and tarmac delays for just their New York area operations, with additional knock-on effects on reducing NAS-wide ripple delay effects. Going beyond the unpublished-TMIs application, ATLASCOPE technology can be applied to unlock hidden information buried in a large variety of unstructured data sources with applications to the following significant, pressing ATM and non-ATM problems and commercialization opportunities: - FAA System Command Center can use ATLASCOPE to create planning meeting conversation transcription-based TFM coordination tools. - FAA airport control towers, TRACONs, and ARTCCs can use ATLASCOPE to detect precursors of safety events by analyzing real-time fused ATC voice comms and flight track datasets. - ATLASCOPE can be used in workplace applications, to automate text understanding and text generation tasks. - It can be used in customer support applications, to analyze customer support calls, extracting valuable insights to improve service quality, identify emerging issues. - It can be used in market research, to analyze audio recordings or transcripts of market research interviews or focus group discussions for revealing consumer preferences, trends, and sentiments. - It can be used in healthcare, for transcribing and analyzing medical consultations, patient records, and clinical notes to aid in identifying patterns, trends, and insights for medical research, disease diagnosis, and patient care management.