Wang Jie, Li Jiangtong
School of Mechanical Engineering, Tianjin University, Tianjin, China.
School of New Media and Communication, Tianjin University, Tianjin, China.
Traffic Inj Prev. 2025;26(6):671-678. doi: 10.1080/15389588.2024.2444471. Epub 2025 Feb 18.
This study investigates the interaction between human perception and driver behavior on horizontal curves, focusing on how road geometry and visibility affect driving performance.
A driving simulator replicated 3 curve types by radius-200 m (sharp), 400 m (moderate), and 600 m (loose)-under day and night conditions. The focus of expansion (FOE) is the source point of optical flow, and an FOE model was established to linked the driver's visual perception with vehicle dynamics. Data on eye movement and vehicle dynamics were collected from 24 drivers (mean age: 27 years, mean driving experience: 3.8 years).
The results indicate that driving at night on sharp curves significantly impairs the ability of drivers to align their perception with vehicle motion, leading to delayed steering adjustments and increased lateral errors. The most dangerous areas, identified as the back half of the test curves and corresponding to the minimum FOE radius, were where the misalignment between perception and motion was most significant. On loose curves, decreased driver vigilance was observed, potentially due to a perceived reduction in steering demands, underscoring the role of psychological and contextual factors during curve negotiation.
This study underscores the importance of optimizing curve radii and enhancing the alignment between drivers' visual perceptions and vehicle dynamics to reduce accident risks. In real traffic, placing traffic guidance mid-curve may better prompt drivers to slow down, particularly at night. Integrating FOE-based feedback into advanced driver assistance systems (ADAS) could further enhance performance by offering real-time cues tailored to curve geometry in low visibility.
本研究调查人类感知与驾驶员在水平弯道上行为之间的相互作用,重点关注道路几何形状和能见度如何影响驾驶性能。
驾驶模拟器在白天和夜间条件下复制了3种半径类型的弯道——200米(急弯)、400米(适中弯)和600米(缓弯)。扩展焦点(FOE)是光流的源点,建立了一个FOE模型以将驾驶员的视觉感知与车辆动力学联系起来。从24名驾驶员(平均年龄:27岁,平均驾驶经验:3.8年)收集了眼动和车辆动力学数据。
结果表明,夜间在急弯上驾驶会显著削弱驾驶员使感知与车辆运动对齐的能力,导致转向调整延迟和横向误差增加。最危险的区域被确定为测试弯道的后半部分,对应于最小FOE半径,是感知与运动之间错位最显著的地方。在缓弯上,观察到驾驶员警惕性下降,这可能是由于感觉到转向需求减少,强调了在弯道行驶过程中心理和情境因素的作用。
本研究强调了优化弯道半径以及增强驾驶员视觉感知与车辆动力学之间对齐以降低事故风险的重要性。在实际交通中,在弯道中间设置交通引导可能会更好地促使驾驶员减速,尤其是在夜间。将基于FOE的反馈集成到先进驾驶辅助系统(ADAS)中,可以通过在低能见度情况下提供针对弯道几何形状的实时提示来进一步提高性能。