The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.

安全绩效功能（SPF）的校准是《公路安全手册》（HSM）中包含的一种机制，用于调整HSM中的SPF，以用于预期的管辖范围。至关重要的是，在使用校准的SPF之前，必须评估校准程序的质量。HSM第一版发布后的几年中，已经开发了多种资源来帮助从业人员校准SPF。同样，文献提出了多种方法来评估经过校准的SPF与给定辖区的数据集的拟合优度（GOF）。本文将多个交叉SPF的校准结果用于大型密西西比州安全数据库，以检查多个GOF指标之间的关系。目标是开发一个合理的单一指标，该指标利用来自多个GOF指标的联合信息来评估整体校准质量。应用于校准结果的因素分析揭示了三个基本因素，这些因素解释了数据中76％的变异性。根据这些结果，作者开发了一个指标并进行了敏感性分析。发现关键指标按降序排列：累积残差（CURE）图与95％置信区的偏差，平均绝对偏差，修正的R平方和校准因子的值。本文还介绍了索引和替代评分策略之间的比较，以及使用综合数据验证结果的努力。