Connecticut Transportation Safety Research Center, Connecticut Transportation Institute, University of Connecticut, 270 Middle Turnpike, Unit 5202, Storrs, CT 06269-5202, USA.
Accid Anal Prev. 2020 Dec;148:105838. doi: 10.1016/j.aap.2020.105838. Epub 2020 Oct 27.
Selecting an appropriate exposure measure and functional form for Safety Performance Functions (SPFs) is critical in precisely predicting crash counts by different crash types for intersections. This study proposes a new approach, namely Generalized Negative Binomial-P (GNB-P) model, to model the complex relationship between crashes and different exposure measures by crash type for intersections, which helps not only identify the most reliable exposure measure for intersection SPFs, but also explore the most appropriate functional form of the NB models. To this end, three types of SPF functional forms, namely Power function, Hoerl function 1 and Hoerl function 2 with different exposure measures including major road AADT, minor road AADT and total AADT were estimated by crash type for stop-controlled and two types of signalized intersections. The over-dispersion of the SPF models was estimated using the exposure measures to account for crash data variation across different intersections. The SPF estimation results highlighted that the mean-variance structure of NB models is not consistent and varies by crash data. The over-dispersion of SPFs by crash type is not constant and varies across different intersections. The minor road AADT is shown to be positively correlated with the over-dispersion of SPFs in estimating crash counts for Same-Direction Crashes (SDC), Intersecting-Direction Crashes (IDC) and Single-Vehicle Crashes (SVC). Estimating the over-dispersion using exposure measures results in more reliable SPF results. Furthermore, it is found that the Power function with major road and minor road AADT as the exposure measure performs the best in estimating SPFs for Opposite-Direction Crashes (ODC). The Hoerl function 2 with total AADT and the proportion of minor road AADT over the total as the exposure measure performs the best in estimating SVC SPFs for intersections. The Hoerl function 1 with major road and minor road AADT as the exposure measure is more accurate in estimating SPFs for both SDC and IDC.
选择适当的暴露度量和功能形式对于准确预测交叉口不同碰撞类型的碰撞次数至关重要。本研究提出了一种新方法，即广义负二项式- P（GNB-P）模型，用于通过碰撞类型来模拟交叉口碰撞与不同暴露度量之间的复杂关系，这不仅有助于确定交叉口 SPF 最可靠的暴露度量，还可以探索 NB 模型的最合适功能形式。为此，根据碰撞类型，针对停车控制交叉口和两种信号交叉口，使用包括主要道路 AADT、次要道路 AADT 和总 AADT 在内的三种 SPF 功能形式（幂函数、Hoerl 函数 1 和 Hoerl 函数 2）来估计 SPF。使用暴露度量来估计 SPF 模型的过离散度，以说明不同交叉口之间的碰撞数据变化。SPF 估计结果突出表明，NB 模型的均值-方差结构不一致，并且因碰撞数据而异。SPF 按碰撞类型的过离散度不是常数，并且在不同的交叉口之间变化。次要道路 AADT 与 SPF 过离散度呈正相关，这在估计同方向碰撞（SDC）、相交方向碰撞（IDC）和单车碰撞（SVC）的碰撞次数时得到了证实。使用暴露度量来估计过离散度可以产生更可靠的 SPF 结果。此外，发现使用主要道路和次要道路 AADT 作为暴露度量的幂函数在估计相反方向碰撞（ODC）的 SPF 方面表现最佳。使用总 AADT 和次要道路 AADT 占总 AADT 的比例作为暴露度量的 Hoerl 函数 2 在估计交叉口 SVC SPF 方面表现最佳。使用主要道路和次要道路 AADT 作为暴露度量的 Hoerl 函数 1 更准确地估计了 SDC 和 IDC 的 SPF。
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