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Innovative non-crash-based safety estimation: An extreme value theory approach.

机译：创新的基于非崩溃的安全性估算：一种极值理论方法。

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摘要

Crash-based safety analysis is hampered by several shortcomings, such as randomness and rarity of crash occurrences, lack of timeliness, and inconsistency in crash reporting. Safety analysis based on observable traffic characteristics more frequent than crashes is one promising alternative. A traditional approach to alternative safety analysis relies on the assumption of constant risk across locations. In addition, the current practice of collecting surrogate data often suffers from the inherent subjectivity of the humans involved in the task. In this research, we propose a novel application of the extreme value theory to a non-crash-based safety estimation that no longer relies on the assumption of constant risk. We evaluate the proposed method by applying it to right-angle collisions at signalized intersections. The feasibility of facilitating the measurement of traffic characteristics with digital video and image processing technology is also examined.; Eight-hour traffic movements at selected intersections were recorded using a mobile traffic laboratory. The risk of right-angle collisions was estimated using so-called post-encroachment times (PET). Evaluated video image processing techniques were not sufficiently accurate for the purpose of our research. Therefore, post-processing of digitized video clips using a manual method was selected. The Poisson and negative binomial regression analyses of short PETS and observed crash counts indicate a significant relationship between these two.; A series of negated PET observations was discretized into fixed time intervals and the maximum values in each interval were treated as extremes. This approach elegantly handles the dependence of extremes in comparison to an alternative approach that defines threshold excesses as extremes. A distribution of extreme values was modeled with a generalization of the generalized extreme value distribution as the non-stationary r largest order statistic model. Based on the premise that PETS being zero or less define a collision situation, safety levels were determined from the model in terms of crash frequency and return level estimates. Evaluation of the safety estimates against historical crash counts indicates a promising relationship between these two. However, the proposed method still yields large-variance estimates due to an insufficient observation period. A semi-empirical simulation experiment revealed that a few weeks of PET observation were needed to obtain crash frequency estimates with confidence intervals comparable to those being obtained from three-year observed crash counts. The proposed method can be applied to other types of locations and collisions as well.
机译：基于碰撞的安全性分析受到一些缺陷的阻碍，例如碰撞事件的随机性和稀有性，缺乏及时性以及碰撞报告的不一致。一种基于可观察到的交通特征（比事故多发生）的安全分析是一种有前途的选择。替代性安全性分析的传统方法依赖于跨地点恒定风险的假设。另外，当前收集替代数据的实践经常遭受参与该任务的人员的固有主观性的困扰。在这项研究中，我们提出了极值理论在基于非碰撞的安全估计中的新应用，该估计不再依赖于恒定风险的假设。我们通过将其应用于信号交叉口的直角碰撞来评估该方法。还研究了使用数字视频和图像处理技术促进交通特征测量的可行性。使用移动交通实验室记录了选定路口八小时的交通动向。直角碰撞的风险是使用所谓的侵占后时间（PET）估算的。对于我们的研究目的，评估后的视频图像处理技术不够准确。因此，选择了使用手动方法对数字化视频剪辑进行后处理。短PETS的Poisson和负二项式回归分析以及观察到的碰撞计数表明两者之间存在显着关系。将一系列否定的PET观测值离散化为固定的时间间隔，并将每个间隔中的最大值视为极端值。与将阈值超出量定义为极端的替代方法相比，此方法可以优雅地处理极端情况的依赖性。极值分布是通过将广义极值分布概括为非平稳r最大阶统计模型来建模的。基于PETS为零或更少定义碰撞情况的前提，根据碰撞频率和返回水平估计值从模型中确定安全级别。根据历史事故计数对安全估计值进行评估表明，这两者之间存在着有希望的关系。但是，由于观察期不足，所提出的方法仍会产生较大的估计差。一个半经验模拟实验表明，需要几周的PET观测才能获得碰撞频率估计值，其置信区间与从三年观察到的碰撞次数中获得的可信度相当。所提出的方法也可以应用于其他类型的位置和碰撞。

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  • 作者

    Songchitruksa, Praprut.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 343 p.
  • 总页数 343
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;
  • 关键词

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