Advancing knowledge of the safety implications of transportation engineering decisions with surrogate safety data and innovative statistical techniques

利用替代安全数据和创新统计技术增进对交通工程决策的安全影响的了解

• 批准号: RGPIN-2017-05288
• 负责人: Sacchi, Emanuele
• 金额: $ 1.89万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=664009
• 关键词: Advancing; knowledge; safety; implications; transportation

The way transportation engineers study and evaluate road and traffic safety has remarkably advanced in recent years. Engineers can now employ a systematic and rigorous process to analyze safety at road sites that identifies opportunities to reduce crashes and implement potential safety countermeasures. This process mainly relies on a set of statistical techniques and models developed over several years of research. In turn, these models rely on crash observations as the main data source to quantify safety levels. However, the use of crash data in safety models has several limitations, mainly related to quality and availability issues. Moreover, the use of crash observations is reactive: a substantial number of crashes must occur before any action is taken. These limitations also inhibit application of new opportunities offered by methodological advancements in the field.***Surrogate safety data represents a promising alternative to the exclusive use of crashes in road safety analysis. So far, limited research has been carried out to estimate and validate coefficients converting surrogate measures to crash frequency. Nevertheless, the continual advance in statistical methodologies has enabled researchers to extract more and more information from existing data sources. For this reason, the proposed research program is aimed at implementing advanced methodologies in road safety using non-crash-based safety measures and establishing a functional relationship between crashes and crash surrogates.***The short-term objectives of the proposed research program are to: (1) collect and measure emerging surrogate safety data and indicators to overcome the limitations related to crash data; (2) validate the use of surrogate safety data obtained from traffic microsimulation models by establishing a relationship with field-measured surrogates; and (3) establish a functional relationship between crashes and crash surrogates by taking advantage of the new methodological frontier in road safety statistics. The results of this research are expected to enhance safety performance of highways by increasing the level of knowledge associated with the safety implications of traffic operations and road design choices. This will have direct impact on the sustainability of our society due to the enormous economic and human costs related to road casualties.

近年来，交通工程师研究和评估道路和交通安全的方法有了显著的进步。工程师现在可以采用系统和严格的流程来分析道路现场的安全性，以确定减少碰撞的机会，并实施潜在的安全对策。这一过程主要依赖于一套经过多年研究开发的统计技术和模型。反过来，这些模型依赖于碰撞观察作为量化安全水平的主要数据源。然而，在安全模型中使用碰撞数据有一些局限性，主要与质量和可用性问题有关。此外，使用崩溃观察是被动的：在采取任何行动之前，必须发生大量的崩溃。这些限制也阻碍了该领域方法论进步所提供的新机会的应用。***替代安全数据代表了在道路安全分析中只使用碰撞数据的一种有希望的替代方法。到目前为止，已经进行了有限的研究来估计和验证将替代措施转换为碰撞频率的系数。然而，统计方法的不断进步使研究人员能够从现有的数据来源中提取越来越多的信息。出于这个原因，拟议的研究计划旨在采用基于非碰撞的安全措施实施先进的道路安全方法，并在碰撞和碰撞替代品之间建立函数关系。***拟议研究计划的短期目标是：(1)收集和测量新出现的替代安全数据和指标，以克服与碰撞数据相关的局限性；(2)通过与现场测量的替代数据建立关系，验证从交通微观模拟模型中获得的替代安全数据的使用；(3)利用道路安全统计的新方法前沿，建立碰撞与碰撞代理之间的函数关系。这项研究的结果有望通过提高与交通运营和道路设计选择的安全影响相关的知识水平来提高公路的安全性能。这将直接影响到我们社会的可持续发展，因为道路伤亡会带来巨大的经济和人力成本。