Presentation
Human Performance Modeling of Carrier-Based Aircraft Landing Missions
SessionPoster Session 1
DescriptionThis study proposes a cognitive behavior model for carrier-based aircraft pilots during the critical "arresting or wave-off" phases, based on the Queuing Network-Model Human Processor (QN-MHP) framework, to address human-machine interface (HMI) design evaluation challenges in naval aviation. By simulating the "perception-cognition-motion" processing pathways under dynamic environments and integrating neuroscientific mechanisms with a production rule base, the model quantitatively analyzes operational error rates and reaction times across diverse interface designs, overcoming the limitations of traditional methods reliant on costly and time-consuming experimental data. Key contributions include: (1) establishing a cognitive behavior simulation model for carrier-based aircraft landing tasks, enabling performance quantification across mission phases; (2) elucidating the cognitive "black box" of pilot decision-making under high-pressure conditions; (3) proposing a simulation-driven HMI evaluation methodology for performance prediction in complex operational scenarios; and (4) validating the QN-MHP model’s applicability in optimizing HMIs for complex equipment. The framework provides an efficient tool for interface design optimization, with future research extending to full-process cockpit modeling to further advance human factors engineering and operational effectiveness in carrier-based aviation.
Event Type
Poster
TimeTuesday, October 14th5:30pm - 6:30pm CDT
LocationRiverside East
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