Machine learning-based cognitive load prediction model for AR-HUD to improve OSH of professional drivers.

Motivation: Augmented reality head-up display (AR-HUD) interface design takes on critical significance in enhancing driving safety and user experience among professional drivers. However, optimizing the above-mentioned interfaces poses challenges, innovative methods are urgently required to enhance performance and reduce cognitive load.

Description: A novel method was proposed, combining the IVPM method with a GA to optimize AR-HUD interfaces.