Statistical and Spatial Analysis of the Effect of Climate Conditions on the Freeways Light-Vehicle Traffic Volume

These days the status and importance of transportation is not hidden from anyone. Since climate conditions are among the factors that affect traffic patterns in transportation network, so the main objective of this study is to provide a spatial method in combination with statistical analysis to investigate the impact of weather related parameters included visibility, wind speed, rainfall, snow depth and temperature on freeways light-vehicle traffic volume. The proposed method is evaluated on of Lowshan- Qazvin freeway. In order to measure the type of statistical correlation and identify climate variables which affect traffic volume, spearman correlation test was employed. Moreover, by classifying climate variables according to the standard thresholds extracted from related studies, statistical analysis has been performed to examine the existence of differences between the groups and number of vehicles, using the U-Mann-Whitney and Kruskal-Wallis tests. Due to the varied behavior of road users in each climate element as well as different time periods, the results are presented by emphasizing on the different seasons of the year and comparing them in each segment. In addition, to perform spatial analysis on the model outputs, evaluation the impact of digital elevation model (DEM) as well as distances between traffic station from the nearest meteorological station on the model statistical outcomes has been studied. The results of this research can be useful for the use of transportation stakeholders and relevant planners for assessing the impact of climate phenomenon on traffic volume.