Using Knowledge Exploration Tools to Study Airspace Complexity in Air Traffic Control

Abstract

A study was conducted at the Federal Aviation Administration's Jacksonville en route air traffic control center to identify factors that contribute to airspace complexity. Direct (verbal reports) and indirect (multidimensional scaling) procedures were used to identify potential factors. A list of candidate factors was created by combining the data from the direct and indirect knowledge exploration methods. Important complexity factors were identified by determining their simple and multiple correlations with overall sector complexity as judged by a group of Traffic Management Unit personnel (flow controllers). A final list of 16 complexity factors was developed and is suggested as a reference for future research in the area. An evaluation of the knowledge extraction techniques indicated that, although little unique information was generated by the indirect procedure, it was useful for the identification of complexity factors when combined with data from direct sources. Further research to validate the identified sector complexity factors is recommended.