Simulation-Based Tool for Traffic Management Training

Both the current NAS, as well as NextGen, need successful use of advanced tools. Successful training is required today because more information gathering and decision making must be done manually, which requires training in the fundamental principles and objectives of traffic management. Successful training is required in NextGen due to the increased reliance on automation. Given the multitude of input channels and actors that must be included in an environment for comprehensive training of Traffic Management Coordinators (TMCs), it would be too costly and too complex to attempt a full-scale human-in-the-loop simulation or table-top exercise that includes the direct participation of all of these entities. In Phase I of this research, we studied and prototyped effective techniques and technologies to allow virtual and/or constructive simulation of key components of the TMC's environment to achieve a significant step forward in the state of the art of TMC training. In Phase II, we will conduct further research on Traffic Management (TM) training techniques and create a more comprehensive prototype system for evaluation. The proposed innovation and focus on this research is called the COMprehensive Environment for TM Training by Simulation (COMETTS). NASA's recent research thrust in the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART NAS) Test Bed provides an important step toward, and platform for, research in simulation-based training for the controller and TMC workforce. Such research holds the potential to significantly improve the transition of technologies from NASA to the FAA and onward to fully successful implementation and acceptance by the end users. This proposed effort will leverage SMART NAS to conduct research, development, prototyping and evaluation of advanced simulation-based TMC training.

As this innovative concept is directly related to the air transportation system, the most appropriate application of the concept and prototype will be further research on operational improvements in the US ATM system. This concept for simulation-based TM training can be applied by NASA across many concepts and technologies to enhance the technology transfer process and end-user acceptance of NASA-developed capabilities. By considering the training process as a core part of the research on advanced ATM decision support tools and procedures, NASA can optimize concepts and capabilities to facilitate training in the operational environment. NASA can use the COMETTS environment to perform research specifically on ATM training associated with new tools, to further improve the FAA's deployment process of new capabilities.

The simulation-based training concept described in this proposal can also be used by airlines and other Flight Operators for training of their dispatchers and ATC coordinators. Collaborative Decision Making in ATM requires a detailed understanding of terminology, operations, tools and constraints amongst all participants. Through a broad use of the COMETTS concept across both FAA and Flight Operator participants, CDM can be enhanced. The simulation-based training concept has extensive applicability across numerous other fields including military, emergency response, security, power plant operations, process control, and many other areas. The ability to simulate unstructured interaction with virtual/constructive participants is at the cutting edge of current market needs in many of these fields. Through the combination of Artificial Intelligence, Natural Language Processing, Machine Learning and Speech Recognition, Mosaic will leverage this work to significant commercial opportunities.

This is early/mid-stage (TRL 6) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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