Single Pilot Operations Model: Dynamic Cognitive Load Assessment Via Integrated Cognitive Architecture

ABSTRACT The transition toward the Single Pilot Operations (SPO) in civil aviation necessitates advanced tools to manage pilot cognitive overload during task‐intensive flight phases. This study proposes a novel dynamic cognitive workload assessment framework to address multitasking demands during the approach phase. Grounded in Time‐stochastic Petri nets (TSPN) and Multiple Resource Theory (MRT), the research innovatively integrates a weighted VACP quantification method with the QN‐ACTR cognitive architecture, establishing a “Temporal‐Resource‐Cognitive” triple‐coupled model. Specifically, the framework utilizes TSPN with inhibitor arcs and stochastic time delays to formally characterize task concurrency and priority scheduling. By incorporating the decay factor from QN‐ACTR, the model captures the “reactivation costs” associated with postponed tasks resulting from working memory degradation during cognitive queuing. To validate the model, a flight simulation experiment was conducted with 29 participants across four workload intensity levels. Experimental results demonstrate that the model‐predicted values are highly correlated with NASA‐TLX scores and sensitive eye‐tracking parameters, significantly outperforming traditional static assessment methods. This dynamic framework provides a reliable quantitative tool for HMI optimization and intelligent flight system development, offering substantial practical value for enhancing aviation safety in future SPO model cockpits.