考虑空间溢出效应的高速公路交通事故随机参数频次模型

A Random Parameters Frequency Model for Highway Crash Analysis Considering Spatial Spillover Effects

为提高高速公路事故频次模型参数估计的准确性,本文以精细的事故记录、道路属性、交通流状态和天气条件数据为样本,首先,构建传统的事故频次模型并对比拟合效果,选择效果最佳的泊松-对数正态分布模型作为优化的基础模型;之后,为挖掘更多的影响高速公路事故频次的空间效应,在加入条件自回归先验的基础上,本文考虑相邻路段的空间溢出效应,建立一个带有空间溢出协变量的模型分析空间溢出效应对路段事故频次的影响。同时,为描绘数据的异质性对路段事故频次的影响,进一步构建一个随机参数模型。结果表明,空间溢出效应显著有效,考虑空间自相关和空间溢出效应的随机参数模型的拟合优度相较于对照模型明显提升。根据最优模型的参数估计结果进行风险因素甄别,其中,“ln(MADT)”“ln(路段长度)”“1类车”“4类车”“降水”等普通变量以及“1类车S“”圆曲线长S”等空间溢出协变量与事故频次显著相关。

To enhance the accuracy of parameter estimation for highway crash frequency models,this paper utilizes crash records,road attributes,traffic flow conditions,and weather condition data as samples to compares the fitting performances of several conventional crash frequency models.The Poisson-lognormal distribution model,which exhibits the best performance,is chosen as the foundational model for optimization.Then,the paper considers the spatial spillover effects of adjacent road segments and investigates additional spatial effects influencing crash frequency on highways.A model with spatial spillover covariates is developed to analyze the impact of spatial spillover effects on crash frequency of road segments in consideration of conditional autoregressive priors.Additionally,a random parameter model is developed to capture the influence of data heterogeneity on crash frequency of road segments.The results demonstrate the effectiveness of spatial spillover effects,and the goodness-of-fit of the proposed models have been improved compared to the control model.Based on the parameter estimation results of the optimal model,risk factors are identified,including"ln(MADT)","ln(road length)","category 1 vehicles","category 4 vehicles",and"precipitation"as ordinary variables,as well as spatial spillover covariates such as"category 1 vehiclesS"and"curvature lengthS",which exhibit significant correlations with crash frequency.