Evaluation of a Machine Learning Approach for Temperature Prediction in Pavement Base and Subgrade Layers in Alberta, Canada
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 149, Issue 1
Abstract
The performance of flexible pavement is influenced by pavement material properties and the strength or the stiffness of the pavement layers. Pavement temperature significantly impacts the material properties of flexible pavements. However, to date there has not been much research that investigates the prediction of the pavement temperature in unbound material (base and subgrade layers). The goal of this research is to apply a new approach, machine learning, to predict pavement temperature in unbound material. Pavement temperature recordings collected at the Integrated Road Research Facility (IRRF) test road in Alberta from January 2013 to February 2020 were used to train and validate machine learning models. Finally, high-performance machine learning models with two parameters (air temperature and day of the year) were developed to predict the average daily pavement temperature at below the road surface. The accuracy of the temperature in the base and subgrade layers predicted using the machine learning models was found to be higher than for an existing model.
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Data Availability Statement
Some data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions (e.g., anonymized data). This includes pavement temperature data from the Integrated Road Research Facility for the time period of January 2013 to February 2020, as well as the machine learning models.
Acknowledgments
The authors would like to thank Alberta Transportation, the Edmonton Waste Management Centre, the City of Edmonton, and Alberta Recycling for their financial and in-kind support of the Integrated Road Research Facility test road. Funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) is gratefully acknowledged. Thanks also to Lana Gutwin for her assistance in the preparation of this paper.
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Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 149 • Issue 1 • March 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jul 16, 2021
Accepted: Oct 14, 2022
Published online: Dec 5, 2022
Published in print: Mar 1, 2023
Discussion open until: May 5, 2023
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