Predicting Average Vehicle Speed in Two Lane Highways Considering Weather Condition and Traffic Characteristics

World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium - WMCAUS

土木建筑工程

Mirbaha, Babak^1 ; Saffarzadeh, Mahmoud^2 ; Amirhossein Beheshty, Seyed^3 ; Aniran, Mirmoosa^3 ; Yazdani, Mirbahador^1 ; Shirini, Bahram^1

Engineering Faculty, Imam Khomeini International University, Qazvin, Iran^1

Civil Engineering and Environment Faculty, Tarbiat Modares University, Tehran, Iran^2

Engineering Faculty, Islamic Azad University, Zanjan Branch, Zanjan, Iran^3

关键词: Data analysis softwares;    Linear regression models;    Negative coefficients;    Positive coefficients;    Significant variables;    Traffic characteristics;    Traffic Management Plans;    Two-lane highways;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/245/4/042024/pdf
DOI  :  10.1088/1757-899X/245/4/042024

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Analysis of vehicle speed with different weather condition and traffic characteristics is very effective in traffic planning. Since the weather condition and traffic characteristics vary every day, the prediction of average speed can be useful in traffic management plans. In this study, traffic and weather data for a two-lane highway located in Northwest of Iran were selected for analysis. After merging traffic and weather data, the linear regression model was calibrated for speed prediction using STATA12.1 Statistical and Data Analysis software. Variables like vehicle flow, percentage of heavy vehicles, vehicle flow in opposing lane, percentage of heavy vehicles in opposing lane, rainfall (mm), snowfall and maximum daily wind speed more than 13m/s were found to be significant variables in the model. Results showed that variables of vehicle flow and heavy vehicle percent acquired the positive coefficient that shows, by increasing these variables the average vehicle speed in every weather condition will also increase. Vehicle flow in opposing lane, percentage of heavy vehicle in opposing lane, rainfall amount (mm), snowfall and maximum daily wind speed more than 13m/s acquired the negative coefficient that shows by increasing these variables, the average vehicle speed will decrease.