The present study is part of an ongoing effort to identify objective predictors of subjective air traffic controller (ATC) workload. The study begins with a comparison of the salient variables governing en route controllers' perceptions of the performance capabilities of a sample of aircraft and the actual performance of the aircraft in the en route environment. A group of 24 Certified Professional Controllers (CPCs) from Kansas City (N=17) and Boston (N=7) en route centers provided estimates of cruising speed, climb, and descent rates for a sample of 24 aircraft types. A matrix of squared Euclidean distances derived from summary measures (i.e., means of estimated speed, climb, and descent rates) was used to construct a classical multidimensional scaling (CMDS) model representing controllers' perceptions of the performance capabilities of each aircraft type. A second matrix was derived from means of speed, climb, and descent rates for the same 24 aircraft types computed from a sample of live air traffic data collected from the Kansas City and Boston en route centers. This matrix was used to construct a second CMDS model representing actual aircraft performance. Interpretation of the dimensions of the CMDS model of ATC estimates suggested that Dimension 1 was related to engine type, whereas Dimension 2 was primarily associated with aircraft weight class. In the model of System Analysis Recording (SAR) data, both engine type and weight class were predominantly associated with Dimension 1. Results are used to develop a measure of aircraft mix (i.e., the mix of aircraft with different performance characteristics) to be added to a suite of controller activity and taskload measures.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; References; Tables;
  • Pagination: 14 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00960031
  • Record Type: Publication
  • Report/Paper Numbers: DOT/FAA/AM-03/8,, Final Report
  • Files: NTL, TRIS, USDOT
  • Created Date: Jul 7 2003 12:00AM