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应用一种新的混合多组统计方法来研究影响碰撞严重性的因素
Mahsa Jafari1, Bhagwant Persaud1
1Department of Civil Engineering, Toronto Metropolitan University, 350 Victoria St, Toronto, ON M5B 2K3, Canada.
Accident; analysis and prevention
|March 4, 2025
概括
本研究介绍了一种混合结构方程建模/模糊集定性比较分析 (SEM-FsQCA) 方法,用于分析道路事故严重性因素. 调查结果显示,邻里收入影响了事故严重程度,使得有针对性的安全策略成为可能.
科学领域:
- 道路安全工程工程 道路安全工程
- 运输科学 运输科学
- 社会经济影响分析.
背景情况:
- 了解碰撞严重性的决定因素对于有效的道路安全策略至关重要.
- 传统方法难以同时分析复杂的因果关系和相互作用效应.
- 事故严重程度研究中的数据不平衡构成了重大分析挑战.
研究的目的:
- 探索混合结构方程建模/模糊集定性比较分析 (SEM-FsQCA) 技术来分析撞击严重程度.
- 为了研究邻里收入对撞车严重性的缓解影响.
- 评估合成少数超标采样技术 (SMOTE) 对不平衡的碰撞数据的有用性.
主要方法:
- 应用混合SEM-FsQCA方法来分析复杂的因果关系和相互作用效应.
- 使用合成少数人过量采样技术 (SMOTE) 来解决数据不平衡.
- 在俄俄州收集公路数据上进行了多组分析,比较了低收入和高收入社区.
主要成果:
- 在SEM分析中,年龄,成绩百分比,教育水平,水平曲线和速度限制被确定为影响碰撞严重性的重要因素.
- 在收入较低和收入较高的社区之间观察到独立和调节变量的影响有显著差异.
- FsQCA确定了导致事故严重程度更高的特定因果配置,根据社区收入水平而异.
结论:
- 混合SEM-FsQCA方法有效地分析了复杂的碰撞严重性关系和缓解效应.
- 事故预防策略可以通过根据相邻社区的社会经济特征定制措施来加强.
- 社区收入水平是影响事故严重程度和道路安全干预措施有效性的关键因素.
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