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Big Data Analytics and Visualization with Spatio-Temporal Correlations for Traffic Accidents

机译:交通事故的时空相关性大数据分析与可视化

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Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize accident occurrences in both temporal and spatial view. Second, we illustrate spatio-temporal visualization results through two case studies in multiple road segments, and the impact of weather on crash types. These findings of accident occurrences analysis and visualization would not only help traffic police department implement instant personnel assignments among simultaneous accidents, but also inform individual drivers about accident-prone sections and the time span which requires their most attention.
机译:交通事故的大数据分析是一个热门话题,在城市中有一个智能和安全的交通具有重要价值。根据2014年10月至2015年3月在中国厦门的大规模交通事故数据,我们提出了一种新的事故发生在空间和时间尺寸中的分析方法,以预测具有特定碰撞类型的事故的何时,其余的是由谁发生。首先,我们在时间和空间视图中分析和可视化事故发生。其次,我们通过多个道路段的两个案例研究以及天气对碰撞类型的影响来说明时空可视化结果。这些事故发生分析和可视化的调查结果不仅可以帮助交警部门在同时事故中实施即时人员作业,而且还会向个人司机提供信息,易于易于的司机以及需要他们最关注的时间跨度。

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