@article{Xu2026, 
author = {Xun Xu and Jing Yang and Sixing Zhao and Yajun Li and Linyan Ren and Mengniu Li and Biao Yan},
title = {Enhancing spatial learning during driving: the role of 3D navigation interface visualization in AR-HUD},
year = {2026},
journal = {Geo-Spatial Information Science},
volume = {29},
number = {4},
pages = {2570-2586},
keywords = {Geovisualization style, Augmented Reality Head-Up Display (AR-HUD), spatial learning, human-machine interface, physiological signals},
url = {https://www.sciopen.com/article/10.1080/10095020.2025.2558822},
doi = {10.1080/10095020.2025.2558822},
abstract = {The style of geovisualization influences drivers’ cognition, decision-making, and spatial learning abilities. With the advancement of in-vehicle navigation technologies, Augmented Reality Head-Up Displays (AR-HUDs) have been widely applied in driving contexts. However, whether AR-HUDs impair drivers’ spatial learning and lead to over-reliance on navigation tools remains unclear. This study evaluates the impact of 2D and 3D Arrow Navigation Interfaces (ANIs) within AR-HUD systems on drivers’ spatial learning, using continuous and objective physiological measures, including Electroencephalography (EEG), Electrodermal Activity (EDA), Heart Rate (HR), and Heart Rate Variability (HRV). A pilot experiment conducted under real-road conditions indicates that the 3D-ANI enhances drivers’ spatial memory and reduces cognitive load. Notably, the depth perception and landmark cues provided by the 3D-ANI facilitate spatial memory encoding under turn-by-turn navigation, mitigating the typical limitations of such systems in supporting spatial knowledge acquisition. These findings offer critical insights into spatial cognitive mechanisms and provide valuable guidance for optimizing navigation interface design.}
}