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Paper Published on Using Machine Learning to Evaluate Road Roughness

Posted: Oct 24, 2018

"Application of Machine Learning Method to Evaluate Road Roughness from Connected Vehicles" was recently published in the Journal of Transportation Engineering, Part B: Pavements. UGPTI's Raj Bridgelall was a co-author of the article. Zhiming Zhang, lead author on the article, earned his doctorate in civil engineering from NDSU. Bridgelall was his co-advisor at NDSU and is co-advisor as Zhang pursues a second doctorate at Louisiana State University. His other co-advisor, Chao Sun, is also an author of the article. Sun is an assistant professor of civil and environmental engineering at LSU. Mingxuan Sun, the final author, is an assistant professor of computer science and engineering at LSU.

The paper proposes a method for evaluating road roughness by applying machine learning to the acceleration responses of connected vehicles. The authors applied a machine learning method to features extracted from the speed normalization and convolution of at least two simulated vehicle acceleration signals. View the paper at DOI: 10.1061/JPEODX.0000074.

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