Spatiotemporal Variability of Road Weather Conditions and Optimal RWIS Density – An Empirical Investigation

This paper presents a study aiming at understanding the relationship between the spatiotemporal characteristics of road weather conditions and a number of RWIS stations using real-world case studies. Semivariogram models are constructed to determine the spatial variability of road weather conditions, especially, autocorrelation range which describes a separation distance at which the measurements are no longer correlated to each other. An optimal RWIS density is then determined through an optimization process that minimizes the total inference errors across the underlying road network. The findings suggest that the regions with less varied topography tend to have a longer spatial correlation range than the regions with more varied topography. The study further reveals that the range of spatial autocorrelation is related to the optimal density of RWIS network â the region with a longer range requires a less number of RWIS stations, than the region having a shorter range.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author