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Development of a methodology for identifying effective countermeasures in regional safety management programs using a Bayesian safety assessment framework (B-SAF).

机译:使用贝叶斯安全评估框架(B-SAF),开发一种在区域安全管理计划中识别有效对策的方法。

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摘要

Rural highways represent the largest single class of highways in the United States, and they account for approximately 80 percent of all paved highways. Two-lane highways account for more than 85% of all rural highways, and fatal crashes nationwide on these roadways totaled 19,055 in 2000. Transportation safety managers are increasingly responsible for identifying and investing public monies in highway projects that result in the greatest reduction of fatalities, injuries and property damage resulting from motor vehicle crashes.; Prior to the implementation of any given highway safety countermeasure, safety managers need a repeatable and objective process that evaluates the expected effect on highway safety from these highway projects. Objective methods for countermeasure selection are limited. Safety managers could use the results from literature reviews or locally funded research in selecting projects, but these approaches face technical deficiencies such as constraints due to right-of-way or environment features, are costly, and do not account for local or regional influences. In addition, many studies only provide insight of the implementation and effects of a single safety countermeasure at a time, whereas in reality multiple countermeasures could be applied.; The approach presented in this thesis proposes an analytical framework to assist highway safety managers in selecting highway safety countermeasures with the greatest safety benefit. This methodology, which relies on Bayesian statistical methods, meta-analytical methods, and subjective engineering evaluations, is termed the Bayesian Safety Assessment Framework (B-SAF) and is used to identify, assess, and rank safety countermeasure effectiveness in regional highway safety programs. The B-SAF methodology is sufficiently general in that it can be applied for managing safety in local, regional, or state jurisdictions. Additionally, this B-SAF process is beneficial, as safety countermeasures that have yet to be applied in their region of interest can be evaluated without being physically implemented beforehand.
机译:农村公路代表了美国最大的高速公路类别,大约占所有已铺设公路的80%。两车道高速公路占所有农村公路的85%以上,2000年全国这些高速公路上的致命交通事故总数为19,055。交通安全管理人员越来越多地负责在公路项目中识别和投资公共资金,从而最大程度地减少了死亡人数,因汽车碰撞而造成的伤害和财产损失;在实施任何给定的公路安全对策之前,安全管理人员需要一个可重复且客观的过程,以评估这些公路项目对公路安全的预期影响。对策选择的客观方法是有限的。安全经理可以使用文献综述或当地资助的研究结果来选择项目,但是这些方法面临技术缺陷,例如由于通行权或环境特征而产生的限制,成本高昂,并且无法考虑当地或区域的影响。另外,许多研究一次只能提供一个安全对策的实施和效果的见识,而实际上可以应用多个对策。本文提出的方法提出了一个分析框架,以协助公路安全管理者选择具有最大安全效益的公路安全对策。这种方法基于贝叶斯统计方法,荟萃分析方法和主观工程评估,被称为贝叶斯安全评估框架(B-SAF),用于在区域公路安全计划中识别,评估和排名安全对策的有效性。 B-SAF方法具有足够的通用性,可以应用于地方,区域或州管辖范围内的安全管理。另外,此B-SAF过程是有益的,因为尚未预先在其物理上实施的情况下,可以评估尚未应用到其感兴趣区域中的安全对策。

著录项

  • 作者

    White, David James.;

  • 作者单位

    Georgia Institute of Technology.;

  • 授予单位 Georgia Institute of Technology.;
  • 学科 Engineering Civil.; Transportation.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 307 p.
  • 总页数 307
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;综合运输;
  • 关键词

  • 入库时间 2022-08-17 11:46:11

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