Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ, USA.
Int J Inj Contr Saf Promot. 2020 Jun;27(2):243-252. doi: 10.1080/17457300.2020.1737139. Epub 2020 Mar 9.
This study explores the joint effect of visibility and warning devices on driver injury severity at the highway-rail grade crossings (HRGCs), while also considering other contributing factors. For this purpose, four mixed logit models are developed to estimate the determinants of driver injury severity considering the combinations of visibility conditions (daylight vs. no daylight) and type of warning devices (active vs. passive warning). The models were calibrated using the data obtained from the USDOT Federal Railroad Administration for HRGC crashes that occurred over a ten-year period 2008-2017 across the United States. A temporal transferability test was conducted and confirmed the stability of model specifications considering a ten-year span of collected data. The pseudo-elasticity analysis was conducted to ascertain marginal impact of the contributing factors on driver injury severity in each model. While the vehicle speed, train speed, time of day and driver age are found to be common significant factors among the four models, there are marked differences between parameters associated with various crash factors. The study provides new insight into the driver injury severity in train-vehicle collisions considering visibility and type of warning devices, which can help in setting up proper policies to improve safety at HRGCs.
本研究探讨了在公路铁路交叉口(HRGC)处,可视性和警告装置对驾驶员伤害严重程度的综合影响,同时还考虑了其他因素。为此,开发了四个混合逻辑回归模型,以估计在考虑可视条件(白天与非白天)和警告装置类型(主动与被动警告)组合的情况下,驾驶员伤害严重程度的决定因素。该模型使用美国交通部联邦铁路管理局在 2008 年至 2017 年期间在美国各地发生的 HRGC 碰撞事故数据进行了校准。进行了时间转移测试,并确认了考虑十年数据收集跨度的模型规范的稳定性。进行了拟弹性分析,以确定各模型中驾驶员伤害严重程度的影响因素的边际影响。虽然在四个模型中都发现车辆速度、列车速度、时间和驾驶员年龄是常见的重要因素,但与各种碰撞因素相关的参数之间存在显著差异。本研究深入探讨了考虑可视性和警告装置类型的情况下,火车与车辆碰撞导致的驾驶员伤害严重程度,这有助于制定适当的政策,以提高 HRGC 的安全性。