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At least 109 records · Page 6

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Peters, Mark↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Advanced Collision Avoidance System for UAS (ACAS Xu) Interoperability White Paper Presentation

The Phase 1 DAA Minimum Operational Performance Standards (MOPS) provided requirements for two classes of DAA equipment: equipment Class 1 contains the basic DAA equipment required to assist a pilot in remaining well clear, while equipment Class 2 integrates the Traffic Alert and Collision Avoidance (TCAS) II system. Thus, the Class 1 system provides RWC functionality only, while the Class 2 system is intended to provide both RWC and Collision Avoidance (CA) functionality, in compliance with the Minimum Aviation System Performance (MASPS) for the Interoperability of Airborne Collision Avoidance Systems. The FAAs TCAS Program Office is currently developing Airborne Collision Avoidance System X (ACAS X) to support the objectives of the Federal Aviation Administrations (FAA) Next Generation Air Transportation System Program (NextGen). ACAS X has a suite of variants with a common underlying design that are intended to be optimized for their intended airframes and operations. ACAS Xu being is designed for UAS and allows for new surveillance technologies and tailored logic for platforms with different performance characteristics. In addition to Collision Avoidance (CA) alerting and guidance, ACAS Xu is being tuned to provide RWC alerting and guidance in compliance with the SC 228 DAA MOPS. With a single logic performing both RWC and CA functions, ACAS Xu will provide industry with an integrated DAA solution that addresses many of the interoperability shortcomings of Phase I systems. While the MOPS for ACAS Xu will specify an integrated DAA system, it will need to show compliance with the RWC alerting thresholds and alerting requirements defined in the DAA Phase 2 MOPS. Further, some functional components of the ACAS Xu system such as the remote pilots displayed guidance might be mostly references to the corresponding requirements in the DAA MOPS. To provide a seamless, integrated, RWC-CA system to assist the pilot in remaining well clear and avoiding collisions, several issues need to be addressed within the Phase 2 SC-228 DAA efforts. Interoperability of the RWC and CA alerting and guidance, and ensuring pilot comprehension, compliance and performance, will be a primary research area.

detect and avoid↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project

Phase 1 of the UAS-NAS (Unmanned Aircraft Systems-National Airspace System) project focused on MOPS (Minimum Operational Performance Standards) development for large UAS transitioning through Class D, E, and G airspace. Phase 2 activities are currently focused on extended UAS operations in Class D, E, and G airspace, as well as sensors and architectures that will enable DAA (Detect and Avoid) equipment to be installed on a wider range of UAS. Encounters with non-cooperative intruders in low altitude airspace under 10,000 feet will be explored for UAS with a low Size, Weight, and Power (SWaP) radar. New sensors for detecting non-cooperative intruder aircraft will have a more limited detection range and field of regard; therefore, the analysis of non-cooperative encounter geometries may help in developing the requirements for an onboard low SWaP radar (and electro-optical sensor). The current simulation, led by HSI (Human Systems Integration Division at NASA Ames Research Center) as part of the DAA subproject, will support efforts toward developing a modified DAA Well Clear (DWC) definition that would be more appropriate for UAS equipped with limited surveillance and aircraft performance capabilities compared to the Phase 1 DAA system. The findings will inform Phase 2 display requirements for alternative surveillance use cases.

Collision Avoidance↗

Improving Human/Autonomous System Teaming Through Linguistic Analysis

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such integration requires humans to work closely with autonomous systems, forming human and autonomous agent teams. The intention behind such teaming is that a team composed of both humans and autonomous agents will operate better than homogenous teams. Procedures exist for licensing pilots to operate in the national airspace system and current work is being done to define methods for validating the function of autonomous systems, however there is no method in place for assessing the interaction of these two disparate systems. Moreover, currently these systems are operated primarily by subject matter experts, limiting their use and the benefits of such teams. Providing additional information about the ongoing mission to the operator can lead to increased usability and allow for operation by non-experts. Linguistic analysis of the context of verbal communication provides insight into the intended meaning of commonly heard phrases such as "What's it doing now?" Analyzing the semantic sphere surrounding these common phrases enables the prediction of the operator's intent and allows the interface to supply the operator's desired information.

Meszaros, Erica L.↗