Automating Simulation-Based Air Traffic Control
Abstract
Air Traffic Control (ATC) receives little attention in simulation-based training and experimentation, in part because of the cost of including human operators to play ATC roles. Where ATC is used, it is typically very limited, reducing the realism of the experiment or training experience. This problem has become more apparent as UAVs and as joint battles are more often fought in simulation, requiring closer human management of the simulated airspace to coordinate air corridors, restricted airspaces, joint fire support, and the like. Furthermore, UAVs have become more prevalent in real battlefields, and the services are struggling with how to employ them safely and effectively within a broader air operations picture. Fighting ATC realistically in a simulated battlespace can help develop more realistic and appropriate employment tactics in the real battlespace. This paper describes the results of a Phase I SBIR investigating the feasibility of automating air traffic control (ATC) within simulation environments, for both experimentation and training. We leverage prior research analyzing human ATC tasks and situational awareness requirements in Tower, TRACON, and En Route operations, and describe how simulation environments can place different constraints and requirements on an ATC capability. We describe the use of human-driven ATC in recent joint experiments as a way to define some operational requirements of automated ATC. Key requirements include the ability to interact with both human pilots in virtual cockpits (using voice interaction), and with synthetic pilots and existing airspace management tools (using digital data links). We identify existing tools and technologies that can be used to fill these requirements, and where technology gaps still exist. Finally, we describe a cognitive systems approach to automating simulation-based ATC, and the development of a limited prototype that illustrates some of the key components of the architecture.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2005
- Accession Number
- ADA635024
Entities
People
- Glenn Taylor
- J. Miller
- Jeff Maddox