a Department of Civil and Environmental Engineering , The University of North Carolina at Charlotte , Charlotte , North Carolina.
Traffic Inj Prev. 2018 Jan 2;19(1):102-109. doi: 10.1080/15389588.2017.1335396. Epub 2017 May 26.
The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature.
Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity.
Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway.
The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.
本研究有两个目的：(a) 基于事故伤害严重程度建立并识别关键道路特征（或位置），并将其与事故频率进行比较；(b) 建立并识别导致事故的驾驶员更有可能通过道路特征导致事故的模型。
从北卡罗来纳州的公路安全信息系统（HSIS）获取 2011 年至 2013 年的事故数据。考虑、分析并比较了 23 种不同的道路特征，以及没有道路特征的情况。开发了多项逻辑回归（MNL）模型，并估计了优势比，以调查道路特征对事故伤害严重程度的影响。
在众多道路特征中，地下通道、高速公路终点或起点以及交叉路口的入口终端是前 3 个关键道路特征。交叉口事故频繁发生，但与关键道路特征相比，不太可能导致严重伤害。环岛不太可能导致严重和中度伤害。与男性驾驶员相比，女性驾驶员更有可能在交叉口（四路和 T 型）发生事故。成年驾驶员更有可能在地下通道发生事故。老年驾驶员在高速公路终点或起点发生事故的可能性是其他驾驶员的 1.6 倍。
本研究的结果有助于确定需要优先考虑的关键道路特征。例如，在高速公路终点或起点等位置增加额外的高级警告标志，并提供放大或高度反光的标志，以吸引老年驾驶员的注意力，可能有助于使这些位置更加安全。除了工程解决方案外，还可以教育驾驶员在关键道路特征处所需的必要技能，以帮助他们在道路上采取更安全的驾驶行为。
