Predicting workload by analyzing control task complexity.

Air traffic controller workload is considered to be a limiting factor in the growth of air traffic worldwide. What drives the workload of air traffic controllers? In an effort to understand and predict their workload, we analyze and model the complexity underlying the control problem. Our starting point is identifying the constraints contained in the ecology, which can be seen as the forcing function that shapes human behavior. Central in this approach is the “solution space”, where our hypothesis is that workload is inversely related to the available space of possibilities. That is, when the solution space is small, the more difficult it will be to solve a particular problem, and the more workload a human will experience. Besides the area of the available solution space, also dynamic properties such as the shrink rate of the solution space are considered.