School of Transportation, Southeast University, Nanjing 211189, China.
Department of Civil Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Accid Anal Prev. 2024 Oct;206:107717. doi: 10.1016/j.aap.2024.107717. Epub 2024 Jul 15.
Extreme value theory (EVT) models have been frequently utilized to estimate crash risk from traffic conflicts with the peak over threshold commonly used to identify conflict extremes. However, a common problem for the peak over threshold method is the selection of a suitable threshold to distinguish general and extreme conflicts. Subjective and arbitrary selection of the threshold in peak over threshold method can result in bias and unstable estimation results. The primary objective of the study is to propose a hybrid modelling approach for the threshold determination in peak over threshold method. The hybrid model consists of a joint gamma distribution and generalized Pareto distribution (GPD). The gamma distribution is used to fit general conflicts while the GPD is used to fit extreme conflicts. Specially, discontinued, continued and differentiable gamma-GPD models are developed with the threshold being treated as a model parameter. Traffic conflict data collected from three signalized intersections in the city of Surrey, British Columbia were used for the study. The modified time to collision (MTTC) was employed as conflict indicator. The Bayesian approach was employed to estimate the threshold as well as other hybrid gamma-GPD model parameters. The results show that the discontinued gamma-GPD model is superior to the continued and differentiable gamma-GPD models for determining the threshold in terms of crash estimation accuracy and model fit. The crash estimates using the threshold determined by the hybrid gamma-GPD model outperform those estimated based on the traditional quantile plots method, indicating that the superiority of the proposed threshold determination approach based on gamma-GPD hybrid model. The proposed hybrid gamma-GPD model could determine the threshold parameter in peak over threshold method for traffic conflicts extremes automatically in an objective and quantitative way. It contributes to existing peak over threshold method for producing reliable crash estimation.
极值理论 (EVT) 模型常用于通过阈值以上极值法来估计来自交通冲突的碰撞风险。然而,阈值以上极值法的一个常见问题是选择合适的阈值来区分一般冲突和极端冲突。在阈值以上极值法中,阈值的主观和任意选择可能导致偏差和不稳定的估计结果。本研究的主要目的是提出一种混合建模方法来确定阈值以上极值法中的阈值。混合模型由联合伽马分布和广义帕累托分布 (GPD) 组成。伽马分布用于拟合一般冲突,而 GPD 用于拟合极端冲突。特别是,开发了带有阈值作为模型参数的间断、连续和可微伽马-GPD 模型。研究使用了不列颠哥伦比亚省萨里市三个信号交叉口收集的交通冲突数据。修改后的碰撞时间 (MTTC) 用作冲突指标。采用贝叶斯方法来估计阈值以及其他混合伽马-GPD 模型参数。结果表明,在碰撞估计准确性和模型拟合方面,间断伽马-GPD 模型优于连续和可微伽马-GPD 模型,用于确定阈值。使用混合伽马-GPD 模型确定的阈值进行碰撞估计优于基于传统分位数图方法的估计,表明基于伽马-GPD 混合模型的阈值确定方法具有优越性。所提出的混合伽马-GPD 模型可以以客观和定量的方式自动确定交通冲突极值中的阈值参数,为现有阈值以上极值法提供了可靠的碰撞估计。