• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Civil Engineering and Science >Comparing Full Bayes Likelihoods to Predict Road Accidents and Identify Potential Hazardous Sites
【24h】

Comparing Full Bayes Likelihoods to Predict Road Accidents and Identify Potential Hazardous Sites

机译：比较全贝叶斯可能性来预测道路事故并确定潜在的危险场所

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Developing reliable safety performance functions (SPFs) capable of estimating expected accident frequencies and identifying hazardous sites is a major concern of departments of transportation. In Bayesian accident data analysis, sites are commonly ranked based on their posterior expected accident frequency in order to be selected for safety countermeasures. The primary objective of this research was therefore to propose an alternative method to evaluate the level of accuracy of an SPF and identify potential hazardous sites, both directly through a single step or measurement. A case study of the Trans-Canada highway in New Brunswick was used applying Bayesian statistics with three different likelihoods: Poisson, hierarchical Poisson-gamma, and hierarchical Poisson-lognormal. As a secondary and validating objective, the above mentioned models were investigated and compared. At the same time, the effect of environmental exposure on the occurrence of accidents was studied. It was found that accident frequencies were slightly affected by environmental conditions. The posterior means of the model parameters indicated that, for the case study, various likelihoods provided roughly similar estimates. However, there were significant differences in the way in which these likelihoods captured the uncertainty around the posterior means through the standard deviation, 95% credible interval, and model-fitting. Moreover, a series of computational and graphical goodness-of-fit measures were examined. In particular, the hierarchical Poisson-gamma likelihood presented the best model-fitting. Furthermore, a measure of relative risk was computed for each site based on the error term presented in Poisson mixture models. The rankings of sites using this measure and the posterior expected accident frequency were generated and compared. A positive covariance between the adopted relative risk factor and the expected accident frequency per segment length was observed. The results and discussions suggested that such a factor can be employed (1) to verify the dependability of SPFs and (2) as an alternative to identify and prioritize potential hazardous sites.
机译：开发可靠的安全性能功能（SPF）以估计预期的事故发生频率并识别危险地点是交通部门的主要关注点。在贝叶斯事故数据分析中，通常会根据事后的预期事故发生频率对地点进行排名，以便选择安全对策。因此，这项研究的主要目的是提出一种替代方法，以评估SPF的准确性水平并直接通过单个步骤或测量来确定潜在的危险场所。使用新不伦瑞克省的横贯加拿大高速公路的案例研究，以三种不同的可能性应用贝叶斯统计数据：泊松，分层泊松-伽马和分层泊松对数正态。作为辅助和验证的目标，对上述模型进行了研究和比较。同时，研究了环境暴露对事故发生的影响。发现事故频率受环境条件的影响很小。模型参数的后均值表明，对于案例研究，各种可能性提供了大致相似的估计。但是，通过标准差，95％可信区间和模型拟合，这些可能性捕获了后均值周围不确定性的方式存在显着差异。此外，还检查了一系列计算和图形拟合优度度量。尤其是，分层的Poisson-gamma可能性提供了最佳的模型拟合。此外，根据泊松混合模型中显示的误差项，计算了每个站点的相对风险度。生成并比较了使用此度量的站点排名和后验预期事故发生频率。观察到采用的相对危险因素与每段长度的预期事故发生频率之间存在正协方差。结果和讨论表明，可以使用这样一个因素（1）验证SPF的可靠性，以及（2）作为识别和确定潜在危险场所优先级的替代方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号