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An evaluation of performance measures for hotspot identification

机译：评估热点识别的性能指标

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摘要

An important step in highway safety analysis is the identification of high-crash locations or "hotspots." Various performance measures are currently used for hotspot identification (HSID). Current measures are mostly based on crash frequency. This article proposes a performance measure based on crash severity, namely, the crash factor measure (CFM). In this article, the performance measures are classified broadly by crash frequency and crash severity. The crash severity measures, the CFM, the equivalent property damage only (EPOO), and the Empirical Bayes supplemented with crash severity (EBCS), and the crash frequency measures, the crash rate (CR) and the Empirical Bayes (EB) are evaluated using eight tests based on empirical and simulated data. To ensure detailed assessment, the evaluation was carried out for three entire highway routes (an Interstate, a US, and a State highway), that is, beyond the top 1% to 10% of hotspots commonly examined. The results from the evaluation demonstrate that the EB and CFM measures performed consistently and are recommended for use. Based on inconsistent results, the CR measure is not recommended for HSID. Based on the overall results, it is also recommended that, for any proposed performance measure, the evaluation should be carried beyond 1% to 10% of the hotspots.
机译：公路安全分析中的重要一步是识别高车祸位置或“热点”。当前，各种性能度量用于热点识别（HSID）。当前的措施主要基于碰撞频率。本文提出了一种基于崩溃严重性的性能度量，即崩溃因子度量（CFM）。在本文中，性能指标大致按崩溃频率和崩溃严重性进行分类。碰撞严重性度量，CFM，仅等效财产损失（EPOO）和补充了碰撞严重性（EBCS）的经验贝叶斯，以及碰撞频率度量，碰撞率（CR）和经验贝叶斯（EB）被评估使用基于经验和模拟数据的八项测试。为确保进行详细评估，对三条完整的高速公路路线（州际公路，美国公路和州际公路）进行了评估，即超出了通常检查的热点的前1％至10％。评估结果表明，EB和CFM措施执行一致，建议使用。基于不一致的结果，不建议将HS度量用于HSID。根据总体结果，还建议，对于任何拟议的绩效指标，评估应超出热点的1％至10％。

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