使用先进的混合决策模型,可靠地测量道路安全
Jiaxu Jin1, Hanrui Feng2, Haojing Gao3
1Financial Market Department, Zhongyuan Bank Co., Ltd, Zhengzhou, 450000, Henan, China.
Scientific reports
|October 8, 2025
概括
本研究介绍了HDPV-BeVarMax模型,用于强大的道路安全分析. 它有效地衡量了国家绩效,并指导了改善道路安全结果的政策.
科学领域:
- 决策科学 决策科学
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 有效的道路安全分析需要强大的决策框架.
- 现有的方法在识别性能模式时可能缺乏稳定性和整体最佳性.
- 道路安全方面的高维数据给传统分析带来了挑战.
研究的目的:
- 引入和验证一种新的混合多标准决策 (MCDM) 框架,即HDVP-BeVarMax模型.
- 将该模型应用于使用综合指标测量国家道路安全绩效.
- 为道路安全提供可靠的决策支持工具,用于政策制定和资源分配.
主要方法:
- 开发了一个混合MCDM框架,结合了高维向量投影 (HDVP) 和类间变量最大化 (BeVarMax).
- 将HDVP-BeVarMax模型应用于13个东亚峰会 (EAS) 国家 (2012-2023) 的纵向道路安全数据,使用15个安全绩效指标 (SPI).
- 进行敏感性,基准和验证分析,以评估模型的可靠性和稳定性.
主要成果:
- 与传统方法相比,HDVP-BeVarMax模型表现出优越的可靠性,稳定性和区分能力.
- 该模型成功量化了国家道路安全绩效,并确定了各国之间的潜在结构.
- 分析证实了该模型在各种规范化和权衡方案中的有效性.
结论:
- HDVP-BeVarMax模型为道路安全决策提供了一种可靠的方法.
- 它可以有效地对国家绩效进行比较,并为目标干预和资源分配提供信息.
- 该模型支持区域合作,并推动实现全球道路安全目标的进展.
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