用于撞击频率建模的细分长度优化:在安全性能评估中评估功率光谱细分长度.
Parveen Kumar1, Geetam Tiwari1, Sourabh Bikas Paul2
1TRIP Centre, IIT Delhi, New Delhi 110016, India.
Accident; analysis and prevention
|May 28, 2025
概括
本研究介绍了一种基于数据的方法,用于选择使用功率光谱段长度 (PSSL) 分析的道路段长度. PSSL提高了碰撞预测的准确性,并确定了导致农村高速公路上致命碰撞的关键因素.
科学领域:
- 道路安全工程 道路安全工程
- 交通分析 交通分析
- 统计建模 统计建模
背景情况:
- 精确的道路段长度选择对于有效的道路安全分析和事故预测至关重要.
- 传统方法缺乏标准化指标,依赖于主观判断.
- 现有的方法在识别危险位置和评估安全性能方面难以准确.
研究的目的:
- 引入和评估功率光谱段长度 (PSSL) 方法,以优化道路段长度选择.
- 用数据驱动的方法提高致命事故预测模型的准确性.
- 为了比较基于PSSL的细分与道路安全分析中的传统方法的性能.
主要方法:
- 空间频域分析 (SFDA) 用于确定功率光谱段长度 (PSSL).
- 功率光谱百分比 (PSP) 被用作评估细分性能的一个关键指标.
- 随机参数负二项 (RPNB) 模型被开发用于分析农村双车道高速公路上的撞车数据.
主要成果:
- 与传统方法相比,基于PSSL的细分显示出更高的性能,由CURE图表和适合性统计数据证实.
- 路边服务区,人口密度,较小的接入点和交通异质性被确定为致命事故的重要预测因素.
- 该研究建立了一个优化的,数据驱动的框架,用于在碰撞建模中选择细分长度.
结论:
- PSSL方法为道路段长度选择提供了一个准确,可靠和可扩展的方法.
- 这一框架提高了碰撞模型和道路安全评估的精度.
- 了解关键的撞车预测因素可以提高农村高速公路上针对性的安全干预措施.
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