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Modeling the impact of various variables on severity of crashes involving traffic barriers

机译:模拟各种变量对涉及交通障碍的崩溃严重性的影响

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摘要

Traffic barriers are in widespread use all around the world as measures for decreasing the severity of roadside crashes. Considering a comprehensive set of more than 160 variables, this article presents the investigation of the variables affecting the severity of crashes involving traffic barriers. An ordinal logistic regression approach was applied to 10-year crash data collected in Wyoming. The crash data included a wide range of various parameters related to traffic, drivers, and road geometry conditions. The results show that the type of vehicles and traffic barriers has the highest effect on the severity of crashes involved with traffic barriers. The rigid barrier might be the best barrier type for reducing trucks' crash severity, whereas guardrail barrier did not provide the same level of protection for trucks on high truck traffic-volume roads. The presented analytical model is more practical for rural states similar to the Rocky Mountains Region due to its similar conditions. The conclusions of the study will help transportation agencies by (1) guiding the designers when selecting the proper type of traffic barriers based on different road conditions and (2) ranking the risk of various traffic barrier segments for prioritizing the most hazardous ones for future improvements.
机译:交通障碍在世界各地广泛使用,作为降低路边崩溃严重程度的措施。本文考虑了一套超过160个变量,提出了影响涉及交通障碍的崩溃严重程度的变量的调查。序数逻辑回归方法应用于在怀俄明中收集的10年崩溃数据。崩溃数据包括与流量,驱动程序和道路几何条件相关的各种参数。结果表明,车辆和交通障碍的类型对涉及交通障碍的崩溃严重程度最高。刚性屏障可能是减少卡车碰撞严重程度的最佳屏障类型,而护卫舰屏障在高卡车交通群体道路上没有提供相同的卡车保护水平。由于其类似条件,所呈现的分析模型对于与岩石山脉类似的农村国家更加实用。该研究的结论将通过(1)在选择基于不同的道路状况的适当类型的交通障碍和(2)排名各种交通障碍段的风险以优先考虑未来改进的各种交通障碍段的风险,帮助运输代理人。

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