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Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile

机译:智利公路车祸中货运卡车的空间自相关分析

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The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (Le., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.
机译:近年来,由于智利货运量的增加,公路碰撞中的货运卡车数量不断增加,促使本研究确定了Ruta 5(R5)公路上持久性碰撞簇的形成。使用两种空间统计方法(Moran's I和Getis-Ord Gi *)来确定这条高速公路上的撞车事故是否从全局和局部角度显示了时间上的空间聚类。在全球范围内,R5北部的垂直弯道和高速公路直段上的反复碰撞事故群在空间上具有相关性,其中卡车类型不同,R5南部在雨天与牵引车-拖车单元也是如此。局部空间自相关结果表明,与车辆失去控制,驾驶员的疲劳和轻率有关的促成原因以及涉及带牵引车的拖车的撞车事故往往会导致整个R5持续翻车撞车事故。总体而言,在具有垂直曲线的高速公路位置和在R5北部占主导地位的阴天,发生了具有较高值(Le,热点)的碰撞属性的聚类,而在R5南部的晴天,最多的经常性热点发生在晴天。进一步进行了热点空间共现分析,以识别研究的碰撞属性与碰撞和伤害类型作为结果之间的牢固关系。公路事故中的货运卡车聚集的高风险迹象为提高公路安全性并降低相关的社会和经济成本提供了基础。

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