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contributor authorKhasawneh, Mohammad Ali
contributor authorMewada, Hiren
contributor authorRababah, Samer
contributor authorNayeemuddin, Mohammed
contributor authorKhasawneh, Ahmad Ali
contributor authorAlsheyab, Mohammad Ahmad
date accessioned2026-08-20T12:01:40Z
date available2026-08-20T12:01:40Z
date copyright2026/04/19
date issued2026
identifier otherJPEODX.PVENG-1822.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312994
description abstractAbstract This study investigated the feasibility of predicting skid numbers (SNs) measured by a locked-wheel skid trailer (LWST) using more-accessible surface friction and texture data from a dynamic friction tester (DFT), British pendulum tester (BPT), ... Practical Applications Accurately measuring pavement friction is crucial for maintaining roadway safety, but traditional methods, such as locked-wheel skid trailer (LWST) testing, are time-consuming, expensive, and require traffic disruptions. This study ...
publisherAmerican Society of Civil Engineers
titleField Data–Driven Machine-Learning Approach for Estimating Pavement Skid Numbers from LWST Measurements for Improved Asphalt Pavement Safety
typeJournal Article
journal volume152
journal issue3
journal titleJournal of Transportation Engineering, Part B: Pavements
identifier doi10.1061/JPEODX.PVENG-1822
journal fristpage04026020-1
journal lastpage04026020-16
page16
treeJournal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 003
contenttypeFulltext


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