Future ATC automation aids based upon AI technology

The authors discuss two knowledge-based systems that are currently under development by the US Federal Aviation Administration, namely a simulation system for air traffic controller training and an automated problem resolution capability that is the central feature of the Automated En Route Air Traffic Control System (AERA 2). For each of these systems, the manner in which knowledge-based system technology is applied is discussed, along with the knowledge bases. The process for building, refining, and evaluating the knowledge bases is also presented. In the air traffic controller training system, ATCoach, the representation of ATC knowledge has been shown to be highly beneficial for both ATC training and airspace modeling. In AERA 2 automated problem resolution (APR) evaluations, the AI/knowledge-based system technology has proven to be indispensable in the representation of the experts´ knowledge and the effective factoring of the knowledge into APR. It is concluded that these applications offer great potential for success and, consequently, represent only the first step in applying AI principles to ATC