Spatial Mapping of Winter Road Surface Conditions via Hybrid Geostatistical Techniques
Publication: Journal of Cold Regions Engineering
Volume 36, Issue 4
Abstract
In recent decades, road weather information systems (RWISs) have gained in popularity with road maintenance authorities. However, RWIS stations only provide point measurements that are often unrepresentative of distant surrounding areas. To address such limitations, this study employs a hybrid geostatistical interpolation method, regression kriging (RK), to fill in the large spatial gaps at unmonitored locations. Road surface temperature (RST) data collected by an automated vehicle system along selected interstate highways were used to model the RST spatial variation patterns via semivariograms, which were then used to interpolate the conditions in between RWIS stations. Cross-validation results indicated that RK successfully captured the spatial variation of RST along the highway segment. The nugget-to-sill ratio obtained from semivariograms was further utilized to characterize the weather events, and the results implied that stronger winds and heavier rainfalls were likely to form a stronger spatial dependence within RST. The findings of this research contribute to better understanding of the influences of meteorological factors in RST as well as improved models for inferring the road surface conditions between RWIS stations.
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Acknowledgments
The authors would like to thank Tina Greenfield of Iowa DOT for providing the data that were essential to complete this study. We would also like to thank the Aurora Project Team and others including Zach Hans and Neal Hawkins of Iowa State University and Khyle Clute of Iowa DOT for providing continued support to the project. This research is funded by the Aurora Program (www.aurora-program.org), an international research consortium for advancing RWIS technology.
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Journal of Cold Regions Engineering
Volume 36 • Issue 4 • December 2022
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© 2022 American Society of Civil Engineers.
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Received: Nov 11, 2020
Accepted: Jun 13, 2022
Published online: Aug 10, 2022
Published in print: Dec 1, 2022
Discussion open until: Jan 10, 2023
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