Institute of Transport Studies, Department of Civil Engineering, Monash University, Melbourne, Australia; Directorate for Roads of Vietnam, Hanoi, Vietnam.
Smart Transport Research Centre, School of Civil Engineering and Build Environment, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia.
Accid Anal Prev. 2016 Sep;94:153-61. doi: 10.1016/j.aap.2016.05.028. Epub 2016 Jun 10.
This paper investigates factors associated with traffic crash fatalities in 63 provinces of Vietnam during the period from 2012 to 2014. Random effect negative binomial (RENB) and random parameter negative binomial (RPNB) panel data models are adopted to consider spatial heterogeneity across provinces. In addition, a spatiotemporal model with conditional autoregressive priors (ST-CAR) is utilised to account for spatiotemporal autocorrelation in the data. The statistical comparison indicates the ST-CAR model outperforms the RENB and RPNB models. Estimation results provide several significant findings. For example, traffic crash fatalities tend to be higher in provinces with greater numbers of level crossings. Passenger distance travelled and road lengths are also positively associated with fatalities. However, hospital densities are negatively associated with fatalities. The safety impact of the national highway 1A, the main transport corridor of the country, is also highlighted.
本文研究了 2012 年至 2014 年期间越南 63 个省份的交通事故死亡人数相关因素。采用随机效应负二项（RENB）和随机参数负二项（RPNB）面板数据模型来考虑省份之间的空间异质性。此外，利用具有条件自回归先验（ST-CAR）的时空模型来解释数据中的时空自相关。统计比较表明，ST-CAR 模型优于 RENB 和 RPNB 模型。估计结果提供了一些重要发现。例如，平交道口较多的省份交通事故死亡人数较高。乘客行驶距离和道路长度与死亡人数呈正相关。然而，医院密度与死亡人数呈负相关。还强调了国家 1A 号高速公路（该国的主要交通走廊）的安全影响。
