在共享空间中解读行人与自动化车辆交互的影响因素:多层次路径分析方法
Liu Yang1, Gamze Dane1, Tao Feng2
1Department of the Built Environment, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, Netherlands (the).
Accident; analysis and prevention
|March 5, 2026
概括
在自动驾驶汽车 (AV) 周围的行人行为受到交通标志和条件的影响. 了解这些因素和个体特征是改善城市共享空间行人安全的关键.
科学领域:
- 城市规划和交通安全.
- 人与计算机在自主系统中的互动.
- 行为科学和交通心理学.
背景情况:
- 步行者将越来越多地在城市共享空间中遇到自动驾驶汽车 (AV).
- 安全的行人-自动驾驶互动需要了解影响行人行为因素.
- 目前的研究缺乏对行人对自动驾驶汽车反应的环境和个人影响的全面分析.
研究的目的:
- 调查环境和个人因素如何影响行人感知和穿越行为在AVS前.
- 模拟各种因素对感知安全,舒适,可读性和信任的直接和间接影响.
- 为设计更安全的AV系统和共享的城市环境提供见解.
主要方法:
- 一个虚拟现实 (VR) 实验,涉及60名参与者模拟各种交通场景.
- 收集关于行人感知和交叉行动的主观和行为数据.
- 多层次路径分析以建模环境和个人因素的影响.
主要成果:
- 交通标志 (例如斑马交叉口) 和交通状况显著影响行人的感知和行为.
- 个人因素,如教育水平和个性特征 (例如,开放性) 也起着显著的作用.
- 感知作为环境/个人因素和行人行为之间的调解者,影响安全和信任.
结论:
- 交通基础设施的设计和自动驾驶汽车的行为 (例如,屈服) 对安全的行人互动至关重要.
- 根据个人差异量身定制AV系统和城市空间,可以提高行人接受度和安全性.
- 该研究为改善自动驾驶汽车时代的行人安全和信任提供了可操作的见解.
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