当安全感变得危险时:VR-EEG-计算机视觉框架用于分析在动态交通环境中的骑自行车安全
Lurong Xu1, Tengfeng Lin2, Steve O'Hern3
1Department of Civil and Environmental Engineering, Monash University, Clayton, VIC 3800, Australia.
Accident; analysis and prevention
|February 1, 2026
概括
骑自行车的人经过后感觉更安全,即使风险仍然存在,创造了一个危险的盲点. 环境设计可以加剧这种风险感知不匹配,影响道路安全.
科学领域:
- 道路安全研究 道路安全研究
- 交通运输中的人类因素
- 感知神经科学的感知神经科学
背景情况:
- 在混合交通中,骑自行车者的安全感和实际撞车风险之间的差异是不太了解的.
- 现有的研究往往忽视了动态视觉元素对风险感知的影响.
研究的目的:
- 调查骑自行车者的安全感和碰撞风险之间的不匹配.
- 探索建筑环境 (BE) 特征对这种感知不匹配的影响.
主要方法:
- 开发了一个虚拟现实 (VR) 平台,集成了VISSIM的脑电图 (EEG),BE数据和碰撞时间 (TTC).
- 利用长期短期记忆 (LSTM) 模型分析了72名参与者的EEG和环境数据.
主要成果:
- 确定了一个"感知缓解期",其中骑自行车的人低估了超越后的风险.
- 发现高空间封闭,复杂的纹理,密集的植被和低可见的车辆密度放大了风险感知不匹配.
- 证明以美学为重点的BE特征可能无意中增加高冲突地区的风险.
结论:
- 该研究提供了综合人车环境安全框架的经验证据.
- 强调需要神经科学和交通工程之间的跨学科合作,以实现更安全的自行车基础设施.
- 表明当前的道路设计可能会通过影响风险感知而无意中损害骑自行车者的安全.
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