回归分析
旅行时间
线性回归
运输工程
计算机科学
变量(数学)
差异(会计)
模拟
度量(数据仓库)
统计
工程类
数学
数据挖掘
会计
数学分析
业务
作者
Ibukun Titiloye,Oluwanifemi Adegbulugbe,Olumide F. Abioye,Doreen Kobelo,Maxim A. Dulebenets,Thobias Sando
标识
DOI:10.1061/jtepbs.0000555
摘要
Inadequate understanding of driver heterogeneity and characteristics creates challenges building models in microscopic traffic simulation tools that accurately represent merging behavior in real traffic. To further understand merging behavior, this study, unlike previous studies, considers age group and other driver characteristics under varying weather, traffic, and geometric conditions. A pilot study was conducted using a driving simulator to simulate merging scenarios on four-lane and six-lane freeway segments for Level of Service (LOS) A and B under clear and foggy weather conditions. A total of 100 individuals voluntarily participated in the study and their time taken to complete merging maneuvers (or merging time) was used as the performance measure. The collected data were analyzed using ANOVA and log-linear regression models, and results show that although there were statistically significant differences among age groups, “number of lanes” was the most significant predictor variable in the model because drivers required longer time merging to the four-lane freeway segment than to the six-lane freeway segment. Also, some driver characteristics and self-reported driving abilities were found to influence the merging time of drivers.
科研通智能强力驱动
Strongly Powered by AbleSci AI