RESEARCH ARTICLE


The Impact of Cold and Snow on Weekday and Weekend Highway Total and Passenger Cars Traffic Volumes



Hyuk-Jae Roh*, 1, Satish Sharma1, Sandeep Datla2
1 Faculty of Engineering, University of Regina, Regina, SK, S4S 0A2, Canada
1 City of Edmonton, Edmonton, Alberta, Canada


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Creative Commons License
© 2014 Rohet al ;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Correspondence: * Address correspondence to this author at the Faculty of Engineering, University of Regina, Regina, SK, S4S 0A2, Canada; Tel: (306) 533-1825; Fax: (306) 585-4855; E-mail: roh204@uregina.ca


Abstract

Presented in this paper is an investigation of the impact of cold and snow on daily traffic volumes of total traffic and passenger cars. It is based on a detailed case study of five years of Weigh-In-Motion data recorded continuously at a highway site in Alberta, Canada. Dummy-variable regression models are used to relate daily traffic volumes with snowfall and categorized cold variables. The importance of all the independent variables used in the model are established by conducting tests of statistical significance. The total traffic and passenger car volumes are influenced by both the snowfall and the cold categories. Plots of the partial effect of each independent variable on the dependent variable are generated. It is found that a daily snowfall of 10 cm may cause a 25% reduction in the daily volume of passenger cars, and temperatures below -25°C may reduce the passenger car volumes by 10% or more. It is believed that the developed traffic-weather models of this study can benefit highway agencies in developing more advanced imputation method or identifying weather adjustment factors for accurate estimation of AADT from short duration traffic counts.

Keywords: Dummy variable regression, traffic statistics, vehicle classification, weigh-in-motion, winter-weather traffic model.