2023
DOI: 10.4018/ijitsa.326558
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Exploring Enhancement of AR-HUD Visual Interaction Design Through Application of Intelligent Algorithms

Abstract: This study aims to optimize the visual interaction design of AR-HUD and reduce cognitive load in complex driving situations. An immersive driving simulation incorporating eye-tracking technology was utilized to analyze objective physiological indices and measure subjective cognitive load using the NASA-TLX. Additionally, a visual cognitive load index was integrated into a BP-GA neural network model for load prediction, enabling the derivation of an optimal solution for AR-HUD design. The optimized AR-HUD inter… Show more

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