This study employs eye-tracking technology to systematically analyze cognitive load mechanisms in autonomous driving L4-level English interface design. Through a 3×3×3 experimental matrix, it reveals the impacts of three factors on cognitive efficiency: term density (increasing when>35%), menu hierarchy (optimal at four levels), and cross-cultural differences. The research proposes the "Clarity-Consistency-Cultural Sensitivity" (3C) design principles, providing scientific evidence for optimizing human-machine interaction in intelligent vehicles.

You Yuan. Cognitive Load Study on English Interface Design in Autonomous Driving System —— Experimental Analysis Based on Eye Tracking. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 8: 20-26. https://doi.org/10.25236/AJCIS.2025.080804.

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