Multidimensional Scaling Analysis of Controllers' Perceptions of Aircraft Performance Characteristics

Details

• Creators:
  Pfleiderer, Elaine M.
• Corporate Creators:
  United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Civil Aerospace Medical Institute
• Corporate Contributors:
  United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Office of Aerospace Medicine
• Subject/TRT Terms:
  • Air traffic controllers
  • Aircraft
  • Decision making
  • Engines
  • Enroute traffic control
  • Multiple regression analysis
  • Perception
  • Performance
  • Weight
  • Workload
  More +
• Publication/ Report Number:
  DOT/FAA/AM-00/24
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  United States. Department of Transportation. Federal Aviation Administration. Office of Aviation. Civil Aerospace Medical Institute
• Abstract:
  Thirty full performance level (FPL) en route air traffic control specialists participated in an investigation of the salient features of aircraft mix, a proposed sector complexity factor. Controllers rated the ""familiarity"" (i.e., frequency of encounter) of 30 selected aircraft. They also provided weight class, engine number, engine type, cruising speed, climb, and descent rate estimates for each aircraft. A matrix of squared Euclidean distances derived from summary estimates (i.e., means of speed, climb, and descent) was used to construct a multidimensional scaling model of the aircraft. Multiple regression interpretation revealed that Dimension 1 was related to engine type, whereas Dimension 2 was associated with weight class. The position of elements in the derived stimulus space indicated that controllers may develop performance-related prototypes through the use of multiple cues derived from a number of sources. Results are presented as justification for further investigation into potential advantages of providing enhanced prediction cues (e.g., engine type and weight class) from a single source, which may increase the efficiency of controller decision making and decrease perceived workload.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/57923/dot_57923_DS1.pdf
• File Type:
  [PDF - 347.13 KB]
• Collection(s):
  FAA Civil Aerospace Medical Institute
• Main Document Checksum:
  urn:sha256:635cd469cb88605fd2aff723d5aae1bb214b5a20f5f49cefe3cc6a621ada9cf8