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A STUDY OF TRAFFIC ACCIDENTS IN SPANISH INTERCITY ROADS BY MEANS OF FEATURE VECTORS

机译:功能向量对西班牙互通道路交通事故的研究。

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Frequently, road traffic accidents are modelled as discrete and independent random and rare events, which possess a low probability of occurrence through time. Nevertheless, in order to study each accident individually it is necessary to obtain details of a number of characteristics that surround it, which may be correlated with each other. In this article, we propose to associate the probability of occurrence of an accident with a large number of features such as weather conditions, incidents caused by the start and end of a roadwork, geographical location of speed control radars, roadway infrastructure, etc. The influence of these features is significant and should be taken into account when proposing measures to help alleviate these undesirable events. The big data methods employed to extract the variables or features allow us to compose a series of vectors that will serve as a basis to study road accident distributions.
机译:通常,道路交通事故被建模为离散的,独立的随机事件和稀有事件,其随时间发生的可能性很小。但是,为了单独研究每个事故,有必要获得围绕它的许多特征的详细信息,这些特征可能相互关联。在本文中,我们建议将事故发生的可能性与多种特征相关联,例如天气情况,道路工程的起止点,速度控制雷达的地理位置,道路基础设施等。这些功能的影响是很大的,在提出缓解这些不良事件的措施时应予以考虑。用于提取变量或特征的大数据方法使我们能够组合一系列向量,这些向量将成为研究道路事故分布的基础。

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