Comparison of Required Task Load in Simulated Autonomous and Controlled Airspace

Abstract

This paper presents a first-order analysis of the control cost associated with a novel concept of operation for future air traffic. The concept of operation divides the airspace into autonomous flows and actively controlled flows. The paper models the effects of autonomy ratio and traffic volume on controller task load. A Monte Carlo simulator framework is used that allocates directly controlled routes and autonomous self-deconflicting four-dimensional trajectory flows in the airspace. Several stochastic models of aircraft scheduling, navigation precision, and conflict detection and resolution are interconnected in the simulation. Results show that autonomy can provide a buffer, preventing rapidly increasing task load with high traffic volumes. The projected increase in traffic volume still maintains feasible averages, but it poses a risk due to the rapidly growing variance that signals unpredictability. A Poisson process model is proposed for task load.