Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, South Korea.
Accid Anal Prev. 2013 Mar;51:141-9. doi: 10.1016/j.aap.2012.10.019. Epub 2012 Dec 12.
This paper documents findings from evaluating performances of three different methods for segmenting freeway sites for the purpose of identifying high collision concentration locations: Sliding Moving Window (SMW), Peak Searching (PS) and Continuous Risk Profile (CRP). The traffic collision data from sites segmented in each method under two different roadway definitions were used to estimate excess expected average crash frequency with Empirical Bayes adjustment with respect to two different sets of Safety Performance Functions (SPFs). The estimates from each of the methods were then used to prioritize the detected sites for safety investigation and these lists were compared with previously confirmed high collision concentration locations (or hot spots). The input requirements for each of three methods were identical, yet their performance markedly varied. The findings revealed that CRP method has the lowest false positive (i.e., requiring a site for safety investigation while it is not needed) rate. The performances of SMW and PS significantly varied when different sets of SPFs were used while that of CRP was less affected.
本文记录了评估三种不同方法在高速公路路段划分中的性能的结果,目的是确定高碰撞集中的位置:滑动移动窗口(SMW)、峰值搜索(PS)和连续风险剖面(CRP)。在两种不同的道路定义下,每种方法划分的路段的交通碰撞数据用于估计在两个不同的安全性能函数(SPF)下,经经验贝叶斯调整后的超额预期平均碰撞频率。然后,使用每种方法的估计值对检测到的路段进行安全调查优先级排序,并将这些列表与之前确认的高碰撞集中的位置(或热点)进行比较。三种方法的输入要求相同,但性能差异明显。研究结果表明,CRP 方法的假阳性率(即需要对一个路段进行安全调查,但实际上并不需要)最低。当使用不同的 SPF 集时,SMW 和 PS 的性能差异显著,而 CRP 的性能受影响较小。