Abstract
Abstract Pervious pavements can help mitigate climate change effects while improving transportation safety by improving wet pavement friction and reducing splash and spray. Prevailing pervious pavement mix design procedures adopt laboratory-scale friction experiments which cannot capture field wet tire-pavement friction performance. To bridge this gap, this paper presents the application of a newly developed discharge-based thresholding algorithm for wet pervious pavement skid resistance estimation. In particular, x-ray computed tomography (XRCT) scanning, digital image processing (DIP) algorithms and finite-element modelling of wet tire-pavement interaction are adopted to bridge laboratory experiments and field performance. Our developed algorithm is found to be superior in performance when compared against other existing global thresholding algorithms in the literature. It was found from the case study that our developed framework is capable of predicting field skid resistance of various pervious pavement mixtures at the design stage, thereby aiding in the selection of friction-efficient pervious pavement mixtures.
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