Impacts of Green Landscapes of Urban Freeway on Driver's Visual Perception: An Equilibrium Effect of Greenness and Complexity

Abstract

While green landscapes are known to influence drivers' visual attention, the optimal configurations for enhancing driving safety and performance remain unclear. This study employed eyetracking technology to investigate eye fixation and gaze behaviors of 24 drivers during a 90-minute simulated urban highway driving task across six distinct landscape conditions across three primary Areas of Interest (AOIs). Within-subject analysis of variance (ANOVA) comparing barren, turf, and woody landscapes revealed that increased greenness significantly directs drivers' eye movements towards greenery. Comparative analysis of the six landscape conditions suggested that shrub landscape settings achieved the most balanced distribution of visual attention across AOIs, preventing drivers from excessively focusing on either natural or artificial features. Moreover, the ANOVA examining two shrub settings and two tree settings revealed a trade-off effect between landscape greenness and complexity. This study provides crucial empirical evidence for a balanced configuration of greenness and complexity in landscape design, confirming its critical role in achieving optimal visual perception outcomes. Finally, it proposes a triangular theoretical framework linking visual perception, mental states, and driving performance, offering theoretical support and practical reference for future research and design of healthy and safe driving environments.

绿色景观对驾驶员视觉注意力具有重要影响，但仍需进一步探索最 优的景观构成方案。本研究采用眼动追踪技术开展城市高速公路模拟驾 驶实验，记录24名驾驶员在6种不同景观环境下完成90分钟驾驶任务 时，在3个主要关注区域（AOIs）的眼部注视和凝视行为。通过对无植 物景观、草坪景观和木本植物景观的被试内方差分析发现，绿化度的增 加可显著引导驾驶员的眼部运动转向绿色区域。针对6种景观条件的对比 分析表明，灌木景观环境能够提供最为平衡的AOI分布，使驾驶员既不 过度关注绿色特征，也不过度关注人工特征，实现了视觉注意力的最优 分配。此外，通过对2种灌木景观环境和2种乔木景观环境的重复测量双 因子方差分析，发现高速公路景观绿化度与复杂性之间存在权衡效应。 本研究为景观设计中绿化度与复杂性的平衡配置提供了重要的科学依 据，证实了这种平衡对实现最佳视觉感知效果的关键作用。最后，本文 提出了“视觉感知－心理状态－驾驶表现”三角理论框架，为未来健康 安全驾驶环境的研究和设计提供了理论支持和实践参考。