Department of Engineering Sciences, Universidad Andres Bello, Quillota 980, Viña del Mar, 2531015, Chile.
Faculty of Engineering, Universidad Andres Bello, Quillota 980, Viña del Mar, 2531015, Chile.
Accid Anal Prev. 2018 Nov;120:195-210. doi: 10.1016/j.aap.2018.08.022. Epub 2018 Aug 28.
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 (i.e., 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.
近年来，由于智利货运量的增加，高速公路上的货车事故数量不断增加，这促使本研究旨在确定公路 Ruta 5（R5）上持续碰撞集群的形成。使用了两种空间统计方法（Moran's I 和 Getis-Ord Gi*），从全球和局部角度确定了这段公路上的事故是否随着时间的推移表现出空间聚类。从全局来看，在 R5 的北部，与不同类型的卡车以及在 R5 的南部雨天的拖拉机拖车单元相关的反复发生的碰撞集群在垂直曲线和直线路段上具有空间相关性。局部空间自相关结果表明，与车辆失去控制、驾驶员疲劳和轻率以及涉及带拖车的拖拉机单元的碰撞有关的原因可能导致整个 R5 持续发生翻车碰撞集群。总体而言，在具有垂直曲线和多云天气的公路位置上，具有高值（即热点）的碰撞属性聚类占主导地位，在 R5 的北部，反复出现的热点数量最多，而在 R5 的南部，晴天出现的热点数量最多。进一步进行了热点空间共现分析，以确定所研究的碰撞属性与作为结果的碰撞和伤害类型之间的强关系。表明高速公路上货车碰撞集群存在高风险，为改善公路安全和降低相关社会经济成本提供了依据。
