Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors
Analyzing freeway crash severity using a Bayesian spatial generalized ordered logit model with conditional autoregressive priors
复制标题
使用具有条件自回归先验的贝叶斯空间广义有序 Logit 模型分析高速公路碰撞严重程度
DOI：
10.1016/j.aap.2019.02.029
复制
发表时间：
2019-06-01
影响因子：
5.9
通讯作者：
Hao, Wei
中科院分区：
文献类型：
--
作者：
Zeng, Qiang;Gu, Weihua;Hao, Wei
本研究开发了一种具有条件自回归先验的贝叶斯空间广义有序逻辑模型，以检验高速公路事故的严重程度。我们的模型能够同时考虑离散事故严重程度等级的有序性以及相邻事故之间的空间相关性，而无需固定事故严重程度等级之间的阈值。收集了2014年中国开阳高速公路的事故数据进行分析，其中事故严重程度等级是综合考虑伤害严重程度、经济损失以及伤亡人数来定义的。我们对所提出的空间模型进行了校准，并通过贝叶斯推理将其与传统的广义有序逻辑模型进行了比较。空间模型的优越性体现在其更好的模型拟合度以及空间项的统计显著性上。估计结果表明，驾驶员类型、季节、交通流量和构成、紧急医疗服务的响应时间以及事故类型对事故严重程度倾向有显著影响。此外，车辆类型、季节、一天中的时间、天气状况、纵坡、桥梁、交通流量和构成以及事故类型对中度和重度事故等级之间的阈值有显著影响。还计算了各影响因素对每个事故严重程度等级的平均边际效应。基于估计结果，提出了一些关于驾驶员教育、交通规则执行、车辆和道路工程以及应急服务的对策，以减轻高速公路事故的严重程度。
This study develops a Bayesian spatial generalized ordered logit model with conditional autoregressive priors to examine severity of freeway crashes. Our model can simultaneously account for the ordered nature in discrete crash severity levels and the spatial correlation among adjacent crashes without fixing the thresholds between crash severity levels. The crash data from Kaiyang Freeway, China in 2014 are collected for the analysis, where crash severity levels are defined considering the combination of injury severity, financial loss, and numbers of injuries and deaths. We calibrate the proposed spatial model and compare it with a traditional generalized ordered logit model via Bayesian inference. The superiority of the spatial model is indicated by its better model fit and the statistical significance of the spatial term. Estimation results show that driver type, season, traffic volume and composition, response time for emergency medical services, and crash type have significant effects on crash severity propensity. In addition, vehicle type, season, time of day, weather condition, vertical grade, bridge, traffic volume and composition, and crash type have significant impacts on the threshold between median and severe crash levels. The average marginal effects of the contributing factors on each crash severity level are also calculated. Based on the estimation results, several countermeasures regarding driver education, traffic rule enforcement, vehicle and roadway engineering, and emergency services are proposed to mitigate freeway crash severity.