基于知识图的道路运输车辆危险行为安全风险评估方法
1College of Automotive and Traffic Engineering, Nanjing Forestry University, Nanjing, China.
Traffic injury prevention
|August 20, 2025
概括
这项研究引入了一个知识图 (KG) 框架来分析危险的驾驶行为和道路安全. 危险驾驶和驾驶员能力是关键的风险因素,KG路径分析揭示了导致事故的机制.
科学领域:
- 道路安全研究
- 运输工程
- 数据科学
背景情况:
- 危险的驾驶行为对道路运输安全有重大影响.
- 量化驾驶员行为与事故之间的复杂关系对于预防至关重要.
研究的目的:
- 开发基于知识图 (KG) 的框架来分析危险驾驶行为对道路安全的影响.
- 量化和确定交通事故中的关键风险因素和因果链.
主要方法:
- 构建了一个多层的KG, 包含七类危险行为.
- 整合多个来源的事故数据来绘制关系.
- 应用了通过标准相关性 (CRITIC) 的标准重要性方法和同位素相似性分析.
- 使用基于KG的路径推理来追踪因果链.
主要成果:
- 危险的驾驶 (C5) 和驾驶员的技术能力 (C1) 被确定为最有影响力的风险因素.
- 最可能与危险驾驶相关的事故类型是后部碰撞.
- 疲劳和超速是常见的行为触发因素;KG分析有效地追踪了风险传播途径.
结论:
- 这项研究将KG分析与CRITIC方法整合在一起,以提供对交通事故行为机制的全面了解.
- 从危险行为到事故类型和原因的因果链明确可视化.
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