利用高速公路实时交通数据识别碰撞类型倾向。
Identifying crash type propensity using real-time traffic data on freeways.
机构信息
Université Paris-Est, Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), «Le Descartes 2», 2 Rue de la Butte Verte, 93166 Noisy-Le-Grand, France.
出版信息
J Safety Res. 2011 Feb;42(1):43-50. doi: 10.1016/j.jsr.2011.01.001. Epub 2011 Mar 2.
INTRODUCTION
We examine the effects of various traffic parameters on type of road crash.
METHOD
Multivariate probit models are specified on 4-years of data from the A4-A86 highway section in the Ile-de-France region, France.
RESULTS
Empirical findings indicate that crash type can almost exclusively be defined by the prevailing traffic conditions shortly before its occurrence. Rear-end crashes involving two vehicles were found to be more probable for relatively low values of both speed and density, rear-end crashes involving more than two vehicles appear to be more probable under congested conditions, while single-vehicle crashes appear to be largely geometry-dependent.
IMPACT ON INDUSTRY
Results could be integrated in a real-time traffic management application.
简介
我们研究了各种交通参数对道路碰撞类型的影响。
方法
在法国法兰西岛地区 A4-A86 高速公路路段的 4 年数据上，指定了多元概率比模型。
结果
实证结果表明，碰撞类型几乎可以完全根据其发生前的交通状况来定义。发现两车追尾碰撞在速度和密度都较低的情况下更有可能发生，多车追尾碰撞在拥挤的情况下更有可能发生，而单车碰撞则主要与几何形状有关。
对行业的影响
研究结果可集成到实时交通管理应用程序中。
Zotero 插件