Delft University of Technology, Faculty of Technology, Policy & Management, Safety & Security Science Section, Jaffalaan 5, 2628 BX Delft, The Netherlands.
Design School, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK.
Accid Anal Prev. 2019 Apr;125:85-97. doi: 10.1016/j.aap.2019.01.002. Epub 2019 Feb 5.
The objective of this paper is the review and comparative assessment of infrastructure related crash risk factors, with the explicit purpose of ranking them based on how detrimental they are towards road safety (i.e. crash risk, frequency and severity). This analysis was carried out within the SafetyCube project, which aimed to identify and quantify the effects of risk factors and measures related to behaviour, infrastructure or vehicles, and integrate the results in an innovative road safety Decision Support System (DSS). The evaluation was conducted by examining studies from the existing literature. These were selected and analysed using a specifically designed common methodology. Infrastructure risk factors were structured in a hierarchical taxonomy of 10 areas with several risk factors in each area (59 specific risk factors in total), examples include: alignment features (e.g. horizontal-vertical alignment deficiencies), cross-section characteristics (e.g. superelevation, lanes, median and shoulder deficiencies), road surface deficiencies, workzones, junction deficiencies (interchange and at-grade) etc. Consultation with infrastructure stakeholders (international organisations, road authorities, etc.) took place in dedicated workshops to identify user needs for the DSS, as well as "hot topics" of particular importance. The following analysis methodology was applied to each infrastructure risk factor: (i) A search for relevant international literature, (ii) Selection of studies on the basis of rigorous criteria, (iii) Analysis of studies in terms of design, methods and limitations, (iv) Synthesis of findings - and meta-analysis, when feasible. In total 243 recent and high quality studies were selected and analysed. Synthesis of results was made through 39 'Synopses' (including 4 original meta-analyses) on individual risk factors or groups of risk factors. This allowed the ranking of infrastructure risk factors into three groups: risky (11 risk factors), probably risky (18 risk factors), and unclear (7 risk factors).
本文的目的是回顾和比较与基础设施相关的碰撞风险因素，并根据它们对道路安全的危害性（即碰撞风险、频率和严重程度）对其进行排名。这项分析是在 SafetyCube 项目中进行的，该项目旨在识别和量化与行为、基础设施或车辆相关的风险因素和措施的影响，并将结果整合到一个创新的道路安全决策支持系统 (DSS) 中。评估是通过检查现有文献中的研究来进行的。这些研究是使用专门设计的通用方法选择和分析的。基础设施风险因素被构建在一个 10 个领域的层次分类法中，每个领域都有几个风险因素（总共 59 个具体风险因素），例如：线路特征（例如，水平-垂直对准缺陷）、横断面特征（例如，超高、车道、中央分隔带和路肩缺陷）、路面缺陷、施工区域、交叉口缺陷（互通式立交和平面交叉口）等。与基础设施利益相关者（国际组织、道路管理部门等）举行了专门的研讨会，以确定 DSS 的用户需求以及特别重要的“热点话题”。对每个基础设施风险因素应用了以下分析方法：（i）搜索相关的国际文献，（ii）根据严格的标准选择研究，（iii）根据设计、方法和局限性分析研究，（iv）综合发现——并在可行时进行荟萃分析。总共选择和分析了 243 项最近和高质量的研究。通过 39 项关于个别风险因素或风险因素组的“概要”（包括 4 项原始荟萃分析）综合结果，将基础设施风险因素分为三组：风险较大（11 个风险因素）、可能风险较大（18 个风险因素）和不明确（7 个风险因素）。
