A human-in-the-loop investigation of sector complexity using ground-based automation

Abstract

Dynamic density (DD) is a quantifiable air traffic complexity metric(s) designed to provide information more intricate than aircraft count, the basis of the current system. Prior validation studies of the DD metric have found that the model consistently performs better than aircraft count; however, complexity changes due to increased levels of automation have not yet been explored. Significant increases in air traffic levels have lead to the development of the Next Generation Air Transportation System (NextGen) which includes improved automation and tools to ease the workload of air traffic controllers. Several ground-based automation tools, such as the Traffic Management Advisor (TMA) and Data Communication (DataComm), are planned for wide implementation for the NextGen mid-term timeframe. In an effort to explore possible complexity changes in the DD model that may result from automation and traffic increases a real-time, human-in-the-loop (HITL) simulation was conducted at the Federal Aviation Administration (FAA) William J. Hughes Technical Center (WJHTC) in New Jersey. Complexity ratings were collected during the simulation and regression analysis was conducted to evaluate the DD metric. Residual data was also analyzed to investigate perceived complexity differences in different traffic and DataComm conditions. The findings of the exercise are discussed.