Texas A&M Transportation Institute, 1111 RELLIS Parkway, Bryan, TX 77807, United States.
Texas A&M Transportation Institute, 3135 TAMU, College Station, TX 77843, United States.
J Safety Res. 2020 Dec;75:14-23. doi: 10.1016/j.jsr.2020.07.001. Epub 2020 Jul 30.
Alcohol-related impairment is a key contributing factor in traffic crashes. However, only a few studies have focused on pedestrian impairment as a crash characteristic. In Louisiana, pedestrian fatalities have been increasing. From 2010 to 2016, the number of pedestrian fatalities increased by 62%. A total of 128 pedestrians were killed in traffic crashes in 2016, and 34.4% of those fatalities involved pedestrians under the influence (PUI) of drugs or alcohol. Furthermore, alcohol-PUI fatalities have increased by 120% from 2010 to 2016. There is a vital need to examine the key contributing attributes that are associated with a high number of PUI crashes.
In this study, the research team analyzed Louisiana's traffic crash data from 2010 to 2016 by applying correspondence regression analysis to identify the key contributing attributes and association patterns based on PUI involved injury levels.
The findings identified five risk clusters: intersection crashes at business/industrial locations, mid-block crashes on undivided roadways at residential and business/residential locations, segment related crashes associated with a pedestrian standing in the road, open country crashes with no lighting at night, and pedestrian violation related crashes on divided roadways. The association maps identified several critical attributes that are more associated with fatal and severe PUI crashes. These attributes are dark to no lighting, open country roadways, and non-intersection locations. Practical Applications: The findings of this study may be used to help design effective mitigation strategies to reduce PUI crashes.
酒精相关损伤是交通事故的一个主要促成因素。然而，只有少数研究关注行人损伤作为碰撞特征。在路易斯安那州，行人死亡人数一直在增加。从 2010 年到 2016 年，行人死亡人数增加了 62%。2016 年共有 128 名行人在交通事故中丧生，其中 34.4%的死亡事故涉及受药物或酒精影响的行人（PUI）。此外，2010 年至 2016 年期间，酒精-PUI 死亡人数增加了 120%。迫切需要检查与大量 PUI 碰撞相关的关键促成属性。
在这项研究中，研究团队通过应用对应回归分析，分析了路易斯安那州 2010 年至 2016 年的交通事故数据，以确定与 PUI 相关的伤害水平相关的关键促成属性和关联模式。
研究结果确定了五个风险集群：位于商业区/工业区的交叉口碰撞、位于住宅区和商业区/住宅区的未分隔道路的中间街区碰撞、与行人站在道路上相关的路段相关碰撞、夜间无照明的开阔乡村碰撞，以及在分隔道路上与行人违规相关的碰撞。关联图确定了与致命和严重 PUI 碰撞更相关的几个关键属性。这些属性是黑暗或无照明、开阔的乡村道路和非交叉口位置。实际应用：本研究的结果可用于帮助设计有效的缓解策略，以减少 PUI 碰撞。
