通过考虑过量零和异质性的碰撞频率模型调查影响因素:对山地高速公路安全性的新见解
Liang Zhang1, Zhongxiang Huang1, Lei Zhu1
1School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China.
PloS one
|April 9, 2025
概括
新的统计模型改善了对山地高速公路撞车事故的理解. 分析显示,道,交叉路口,路面状况和暴雨对撞车频率产生重大影响,有助于采取积极的安全措施.
科学领域:
- 交通安全工程 交通安全工程
- 统计建模 统计建模
- 交通运输规划 交通运输规划
背景情况:
- 对于山地高速公路撞车原因的统计建模因数据可用性和过多的零和异质性而面临限制和挑战.
- 这阻碍了在这些特定的道路类型上有效地针对主动事故预防策略.
研究的目的:
- 开发创新的统计模型,准确量化山地高速公路上的撞车原因.
- 为了应对过多的零值和事故数据异质性的技术挑战.
- 确定影响碰撞频率的关键因素,以改善安全措施.
主要方法:
- 收集了来自中国山区高速公路的多维撞车数据,包括道路设计,交通,路面和天气条件.
- 开发了两个新型模型:随机参数负二项林德利 (RPNB-L) 和随机参数负二项通用指数 (RPNB-GE).
- 使用适合度指标,与六个竞争模型进行模型性能比较.
主要成果:
- RPNB-L和RPNB-GE模型显示出优异的适应性,表明林德利和GE分布有效处理多零数据,随机参数处理异质性.
- 确定了包括道,交叉路口,路面损坏状况指数 (PCI) 和暴雨 (TR) 在内的重大撞车致死因素.
- 这些因素,特别是道,交叉路口,PCI和TR,在以前的研究中被强调是研究不足的.
结论:
- 开发的RPNB-L和RPNB-GE模型为分析山地高速公路撞车事故提供了改进的统计方法.
- 这些发现提供了对道路几何形状和天气等特定贡献因素的关键见解,使得有针对性的安全干预措施成为可能.
- 结果为为山地高速公路选择有效的积极安全对策提供了有价值的参考资料.
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