Identification and priorization techniques aplied to urban traffic crash locations: A scoping review

Fagner Sutel de Moura , Lucas França Garcia , Tânia Batistela Torres , Leonardo Pestillo Oliveira , Chritine Tessele Nodari
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Abstract

This paper presents a Scoping Review of methods used for the identification and prioritization of Traffic Crash Locations (TCL) in complex urban areas, considering different accident classes and outcomes with different degrees of severity. Were obtained relevant studies on identifying and prioritizing accident-prone locations from the consultation of two electronic databases (Scopus and Web of Science). The data obtained were evaluated by independent reviewers. Studies carried out in urban areas, which carry out the tasks of grouping accidents into units of analysis, identifying candidate areas, and prioritizing accident-prone locations, were selected. Forty-two studies were selected and evaluated. The applied units of analysis, identification methods, and criteria for prioritizing candidate areas for accident-prone locations were identified among the studies found. The mapping of the works that apply statistical significance criteria of the findings and longitudinal analyses of the candidate sites was carried out. Among the strategies used to identify TCL, the most frequently applied approach was Spatial Association (SA) (23.81%), followed by minimum threshold limit (MTL) (14.29%). Among the different ranking criteria identified, the upper control limit (UCL) criterion stood out, followed by the density and expected frequencies criteria. This work presents a narrative summary mapping the heterogeneity of applied approaches. The contribution of this study was the presentation of the roadmap for the different studies related to the analysis of TCL. Finally, this work points out the need to adopt longitudinal analyzes as a criterion for prioritizing TCL and the application of criteria of statistical significance during the prioritization stage of TCL.

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适用于城市交通事故地点的识别和优先排序技术:范围审查
本文对复杂城市地区交通事故易发地点(TCL)的识别和优先排序方法进行了范围审查,考虑了不同的事故类别和不同严重程度的事故结果。通过查阅两个电子数据库(Scopus 和 Web of Science),我们获得了关于事故易发地点的识别和优先排序的相关研究。获得的数据由独立审查员进行评估。选取了在城市地区开展的研究,这些研究的任务是将事故归类为分析单位、确定候选区域以及确定事故多发地点的优先次序。共选择并评估了 42 项研究。在这些研究中,确定了所应用的分析单位、识别方法和事故多发地点候选区域的优先排序标准。此外,还绘制了应用研究结果统计显著性标准和对候选地点进行纵向分析的作品图。在用于确定 TCL 的策略中,最常用的方法是空间关联法(SA)(23.81%),其次是最小阈值限值法(MTL)(14.29%)。在确定的不同排序标准中,控制上限 (UCL) 标准最为突出,其次是密度和预期频率标准。本研究对应用方法的多样性进行了叙述性总结。本研究的贡献在于为与 TCL 分析相关的不同研究提供了路线图。最后,本研究指出,有必要采用纵向分析作为确定 TCL 优先次序的标准,并在确定 TCL 优先次序的阶段采用统计意义标准。
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