期刊论文

Wu, Ling-tao

英文

中南大学学报(英文版)

2095-2899

2020

27

8

2259-2268

10.1007/s11771-020-4447-2

Foundation item: Project(51978082) supported by the National Natural Science Foundation of China; Project(19B022) supported by the Outstanding Youth Foundation of Hunan Education Department, China; Project(2019QJCZ056) supported by the Young Teacher Development Foundation of Changsha University of Science & Technology, China

本校为第一机构

Before-after study with the empirical Bayes (EB) method is the state-of-the-art approach for estimating crash modification factors (CMFs). The EB method not only addresses the regression-to-the-mean bias, but also improves accuracy. However, the performance of the CMFs derived from the EB method has never been fully investigated. This study aims to examine the accuracy of CMFs estimated with the EB method. Artificial realistic data (ARD) and real crash data are used to evaluate the CMFs. The results indicate that: 1) The CMFs derived from the E...

事故修正系数（措施安全效果）的评估是交通安全管理的重要环节,经验贝叶斯（EB）方法是目前最先进、首选的方法。该方法能够解决回归到均值的问题并提高评估精度,然而,尚未有学者对EB方法所得到事故修正系数的精确度进行细致的分析,本论文旨在填补该项空白,并重点针对事故修正系数的标准差进行分析。论文采用了模拟与实际观测两项数据对EB方法进行了分析,结果表明:1) EB方法得到的事故修正系数与理论值比较接近;2)EB方法所得到事故修正系数的标准差并不能反映真实值,估计值不随真实值的变化而变化;3)基于实际数据的分析表明EB方法往往低估事故修正系数的标准差。交通安全研究人员应当注意在使用...