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Spatio-temporal hotspots analysis of pedestrian-vehicle collisions in tunisian coastal regions

机译:突尼斯沿海地区行人车辆碰撞的时空热点分析

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Like many countries, the extent of road safety in Tunisia is considerable. In addition, road accidents cause extensive economic losses. It is in this perspective that the requirement of safety has become a priority value, a goal that applies to everyone, especially in the field of transport. The objective of this research is to examine pedestrian-vehicle collisions (PVC) in coastal regions in Tunisia in term of area of occurrence under peak time periods. To do so, an innovative and integrated two-step approach was applied. Firstly, Ripley's K-function was used to detect the highway segments, where PVC were significantly clustered, dispersed or random. Secondly, Since PVC are distributed over a Network Kernel Density Estimation approach will be used to detect where exactly road accidents aggregates across the study area under peak time periods in order to predict some hourly trend to the PVC distribution and to find whether the detected high-risk locations are subject to temporal fluctuation. To the best of the authors' knowledge, this research is the first to examine road accidents in term of hotspot analysis under peak time periods. The findings of this has significant implications for public decision-maker to enhance road safety situation, especially with the considerable surge in the vehicle fleet in Tunisia.
机译:像许多国家一样,突尼斯的道路安全程度相当可观。此外,道路事故导致广泛的经济损失。正是在这种观点中,安全的要求已成为优先价值,这是适用于每个人的目标,特别是在运输领域。该研究的目的是在峰值时间段的发生面积中审查突尼斯沿海地区的行人车祸(PVC)。为此,应用了创新和集成的两步方法。首先,Ripley的K函数用于检测高速公路段,其中PVC显着聚集,分散或随机。其次,由于PVC分布在网络内核密度估计方法上,因此将用于检测在峰值时间段内跨越研究区域的总结道路意外聚集在哪里,以便预测到PVC分布的一些小时趋势,并找到检测到的高度风险位置受时间波动的影响。据作者所知,这项研究是第一个在高峰期间检查热点分析的道路事故。这一调查结果对公共决策者提高道路安全情况具有重大影响,特别是突尼斯的车队中的相当大的浪涌。

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