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Distributed Air Ground Traffic Management (DAG-TM):

The Distributed Air/Ground Traffic Management (DAG-TM) concept is a coherent set of conceptual elements that describe possible modes of operation within the outlines of the Free Flight concept defined by the RTCA Task Force. It may be viewed as one possible approach to the potential implementation of Free Flight, progressing along the path started by the Free Flight Phase 1 activities. This DAG-TM concept was developed by the Advanced Air Transportation Technologies (AATT) Project.

Distributed Air/Ground Traffic Management is a National Airspace System concept in which flight deck (FD) crews, air traffic service providers (ATSP) and aeronautical operational control (AOC) facilities use distributed decision-making to enable user preferences and increase system capacity, while meeting air traffic management requirements. DAG-TM will be accomplished with a human-centered operational paradigm enabled by procedural and technological innovations. These innovations include automation aids, information sharing and Communication, Navigation, and Surveillance (CNS) / Air Traffic Management (ATM) technologies.

DAG-TM is a proposed concept for gate-to-gate NAS operations beyond the year 2015. It will address dynamic NAS constraints such as bad weather, Special Use Airspace (SUA) and arrival metering/spacing. The goal of DAG-TM is to enhance user flexibility/efficiency and increase system capacity, without adversely affecting system safety or restricting user accessibility to the NAS. The DAG-TM concept is intended to address all user classes (commercial carriers, general aviation, etc.) with an emphasis towards ensuring access to airspace resources for the entire user community. It covers all flight phases (Pre-Flight Planning, Departure, Cruise and Arrival) and operational domains in the NAS (Surface, Terminal Airspace and En route Airspace). Although other operational domains (e.g., European, oceanic, and under-developed airspace) are outside the scope of the current DAG-TM concept, research activities will give due consideration to global interoperability issues.

For more information, see the DAG-TM website here.



CTAS-FMS Integration, 2002 (CFI'02):

CFI'02 compares a sector-oriented approach to arrival flow management to a candidate trajectory-oriented approach. The sector-oriented approach is bases on current day operations for handling arrival traffic in a time-based metering situation. The trajectory-oriented approach provides advanced tools for the controller and introduces a more active interaction with the traffic management coordinator (TMC). These additions may help manage an arrival flow from a broader perspective, helping controllers, especially controllers in upstream sectors, to use strategic clearances to improve the downstream flow at the meter fix merge.

CFI'02 seeks to validate the assumed benefits associated with a trajectory-oriented approach. This research will be conducted in two operational modes. The first is a baseline condition resembling current day operations for time-based metering. The trajectory-oriented approach is the other condition, adding such tools as CTAS/FMS descent procedures, conflict prediction, trial planning, speed advisories, automation to support controller-controller clearance coordination, and TMA-derived meter fix RTA advisory updates to en route aircraft.

The CFI'02 experiment gives us an opportunity to determine what benefits can be gained by introducing ground-based procedures for trajectory-oriented traffic management, and to develop scenarios and metrics to support other DAG-TM concepts.



Crew Activity Tracking System (CATS):

The Crew Activity Tracking System (CATS) tracks human operator activities to detect deviations from correct operations that may impact the safety of complex systems. It supports visualization and analysis of operator-caused deviations and the context surrounding them. CATS has a computational hierarchical model of the preferred way to control the system. With data about the current state of the system and constraints on its behavior, CATS generates a representation of the current operational context and predicts operator activities according to its model. CATS compares each actual operator action it detects to its predictions to determine if the action is: (1) preferable according to the model, (2) part of a valid alternative method for performing a required function, or (3) an error of commission. CATS also ensures that human operators perform activities to meet high-level control requirements; if not, CATS signals errors of omission. In addition to tracking operator activities, CATS also provides a framework for intelligent agents that can control simulated complex systems in predictable ways to support design.
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Curator: Phil So
NASA Official: Everett Palmer
Last Updated: June 22, 2012