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Investigating exposure measures and functional forms in urban and suburban intersection safety performance functions using generalized negative binomial - P model

机译:使用广义负二型 - P模型调查城市和郊区交叉路口安全性能函数的曝光措施和功能形式

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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 SingleVehicle 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.
机译:选择适当的曝光测量和用于安全性能函数的功能形式(SPFS)对于通过不同的崩溃类型进行准确地预测交叉类型的不同崩溃类型至关重要。本研究提出了一种新的方法,即广义负二进制-P(GNB-P)模型,通过碰撞类型来模拟崩溃和不同曝光措施之间的复杂关系,这有助于不仅识别最可靠的交叉口SPF的曝光度量,还探索了最适合NB模型的功能形式。为此,三种类型的SPF功能形式,即具有不同曝光措施的电源功能,HOERL函数1和HOERL功能2,包括MACED RODE AADT,小路AADT和总AADT,用于停止控制和两种类型的崩溃类型信号交叉口。使用曝光措施来估计SPF模型的过度分散估计,以解释不同交叉路口的崩溃数据变化。SPF估计结果突出显示NB模型的平均方差结构不一致并通过崩溃数据变化。通过碰撞类型的SPF的过度分散不是恒定的并且在不同的交叉点上变化。在估计同一方向碰撞(SDC),交叉方向崩溃(IDC)和单级碰撞(SVC)的崩溃计数中,小路AADT被认为与SPF的过度分散呈正相关。使用曝光措施估算过度分散导致更可靠的SPF结果。此外,发现具有主要道路和小路Aadt作为曝光测量的功率功能在估计与相反方向崩溃(ODC)的SPF中表现最佳。随着曝光量度曝光量度的总Aadt的Hoerl函数2和小路AADT的比例在估计SVC SPF的交叉口时表现最佳。 HOERL功能1具有主要道路和小路AADT作为曝光措施在估算SDC和IDC的SPF方面更准确。

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