UPE IFSTTAR GRETTIA, French Institute of Science and Technology for Transport, Development and Networks, France.
Accid Anal Prev. 2013 Nov;60:456-65. doi: 10.1016/j.aap.2013.03.006. Epub 2013 Apr 1.
This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion.
本研究旨在突出天气条件与道路事故风险之间的联系,包括在总体水平和按月基础上的联系,以便改善国家层面的道路安全监测。它基于欧盟 FP6 项目“SafetyNet-建立欧洲道路安全观测站”中“数据分析和综合”工作包 7 中进行的一些案例研究,这些研究说明了如何使用天气变量来分析道路伤害事故数量的变化。使用了具有解释变量的时间序列分析模型,这些变量定量测量天气,并将其应用于法国、荷兰和雅典地区超过 20 年的伤害事故综合数据集。主要结果按月显示天气变量与伤害事故总数之间存在显著相关性,但这些相关性的大小甚至符号因道路类型(高速公路、农村道路或城市道路)而异。此外,在法国的城市间网络的情况下,似乎降雨的影响主要是高速公路上的直接影响——暴露不变,而主要道路上的部分间接影响——由于暴露的变化。针对雅典地区的每日基础上获得的其他结果表明,捕捉天气变量的月内可变性并将其包含在月度模型中,可以突出极端天气的影响。这些发现与使用类似方法在法国获得的先前结果一致,但雅典地区发现降水与伤害事故数量之间存在负相关,对此进行了进一步调查。在结论中讨论了该方法及其附加值的前景。