交互模式探索和风险评估在车道变化中的初始场景和演变过程
Junhua Wang1, Bo Yao2, Qiangqiang Shangguan1
1The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China; College of Transportation, Tongji University, 4800 Cao'an Highway, Shanghai 201804, China.
Accident; analysis and prevention
|December 18, 2025
概括
本研究确定了9个车道交换 (LC) 场景和20个交互模式,并根据风险分类它们. 这些发现增强了对自动驾驶和交通安全系统的驾驶员行为的理解.
科学领域:
- 交通安全 交通安全
- 人与计算机的交互
- 自主驾驶系统 自主驾驶系统
背景情况:
- 换车道 (LC) 是一个复杂的过程,受驾驶员的决定,交通和道路状况的影响.
- 了解特定的LC场景和驾驶员互动至关重要,但仍然不清楚.
- 现有的研究缺乏一个框架来分析车道更改期间车辆的联合行为.
研究的目的:
- 建立一个分析变车道 (LC) 场景和交互模式的框架.
- 识别和分类不同的LC初始场景和驾驶员交互模式.
- 评估与不同LC场景和模式相关的驾驶风险.
主要方法:
- 开发了一个双层集成集群框架,用于LC交互.
- 使用规范化k-means和对对聚合SSE进行高维数据分析.
- 在高清轨迹数据上提取员工交互特征.
主要成果:
- 确定了9个主要的LC初始场景和20个主要的LC相互作用模式.
- 在LC场景和交互模式之间建立了关系.
- 将模式分为全球一般,地方一般和特殊类型;确定了风险和安全的场景/模式.
结论:
- 提供了对车道更换过程的全面了解.
- 提供了自动驾驶开发和测试的理论基础.
- 支持协作变车道系统和交通警报技术的设计.
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