Predictive Mental Workload Modeling Methodology for Single-Pilot Operations System Design

Abstract

Predictive mental workload model is an important tool for evaluating early single-pilot operations (SPO) system design and can be used to explore the impact of different function allocation decisions before prototype or simulator implementation. To build this model, this paper proposes a methodology based on task analysis. Firstly, it selects the approach and landing scenario of the current two-pilot operations (TCO) and completes the task description of the TCO using the hierarchical task analysis. Secondly, it identifies the function allocation requirements for the transition from TCO to SPO using the work domain analysis and proposes the original function allocation decisions based on the SPO’s system framework. Finally, it creates the predictive mental workload model for evaluating different SPO system design options based on temporal network and multiple resource theory. The researchers use the created model to evaluate the original function allocation decisions and find that the designed SPO system has instantaneous workload values that exceed the upper limit at multiple time points. By analyzing the causes of these problems, the researchers introduce audible warnings and visual indicators to the SPO system to improve design decisions and evaluate these decisions. The results show that the continuous workload profile and overall average workload of the redesigned SPO system are better than the current TCO system, and also prove that the predictive mental workload model can be well applied to evaluate the system design of early SPO.