针对印度北方邦两轮车道路事故的天气驱动风险评估模型
Tripti Garg1, Durga Toshniwal2, Manoranjan Parida3
1Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India. tgarg@cs.iitr.ac.in.
Scientific reports
|February 26, 2025
概括
天气对北方邦的两轮车交通事故有很大影响. 一个新的天气影响的集群和随机采样 (WICRS) 模型通过评估各种天气条件下的撞车风险来增强道路安全分析.
科学领域:
- 道路交通安全 道路交通安全
- 环境科学 环境科学
- 运输工程 运输工程
背景情况:
- 两轮车道路交通事故对公众健康和安全构成重大挑战,特别是在具有不同天气模式的地区,如印度的北方邦.
- 了解天气条件对事故发生的影响对于有效的道路安全干预至关重要.
- 分析与天气有关的撞车风险的现有方法,例如匹配对分析,在捕捉复杂的环境相互作用方面可能存在局限性.
研究的目的:
- 为了调查不同天气条件和北方邦两轮车道路事故之间的关系.
- 引入和评估一种新的天气影响的集群和随机采样 (WICRS) 模型,用于相对事故 (崩) 风险 (RAR) 分析.
- 为了比较WICRS模型的有效性与传统方法,如匹配对分析 (MPA).
主要方法:
- 一项对954,000多起两轮车事故的初步分析,考虑了位置,人类和环境因素.
- 开发和应用WICRS模型,利用基于随机抽样的聚类来分类天气模式.
- 分层RAR分析包括性别,道路类型和一天的时间等变量,特别关注潮湿和非潮湿的日子.
主要成果:
- 该研究证实了天气条件对两轮车道路交通事故发生频率和风险的重大影响.
- WICRS模型在分析天气影响的撞车风险方面表现出有效性,与MPA相比,它提供了一个细微的方法.
- 风险分析显示了潮湿和非潮湿天气条件的不同模式,突出了特定的安全问题.
结论:
- 天气条件是导致北方邦两轮车道路事故的关键因素.
- WICRS模型为详细的相对事故 (崩) 风险分析提供了一个强大的框架,改进了传统方法.
- 这些发现支持实施WICRS模型,用于基于证据的道路安全政策制定和减缓策略.
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