Workload and complexity measures are, as of today, often imprecise and subjective. Currently, two commonly used workload and complexity measuring formulas are Monitor Alert Parameter and the “Bars”, both using the same measurement variables; amount of aircraft and time. This study creates formulas for quantifying ATC complexity. The study is done in an approach environment and is developed and tested on Stockholm TMA by the creation of 20 traffic scenarios. Ten air traffic controllers working in Stockholm TMA studied the complexity of the scenarios individually and ranked the scenarios in reference to each other. Five controllers evaluated scenario A1-A10. These scenarios were used as references when creating the formulas. The other half of the scenarios, B1-B10, ranked by another five controllers, was used as validation scenarios. Factors relevant to an approach environment were identified, and the data from the scenarios were extracted according to the identified factors. Moreover, a regression analysis was made with the ambition to reveal appropriate weights for each variable. At the first regression, called formula #1, some parameter values were identical. Also, some parameter weights became negative in the regression analysis. The basic requirements were not met and consequently, additional regressions were done; eventually forming formula #2. Formula #2 showed stable values and plausible parameter weights. When compared to a workload measuring model of today, formula #2 showed better performance. Despite the small amount of data samples, we were able to prove a genuine relation between three, of each other independent, variables and the traffic complexity.

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Published on 01/01/2015

Volume 2015, 2015

Licence: CC BY-NC-SA license

ATC • Air traffic control • DD • Dynamic Density • LFV • Luftfartsverket • MAP • Complexity • Flygledare • Flygledning • Regression • Workload

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