United States Department of Transportation
i
Efficient Model for Predicting Friction on Texas Highway Network
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2023-01-01
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[PDF-9.30 MB]
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Edition:September 2019 – December 2021
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Abstract:The objective of this project was to develop a model to predict friction that could be applied at the network level to overcome some of the issues associated with friction measuring equipment. This project developed an instrument that can collect high-resolution surface profiles to determine macrotexture and microtexture under different conditions and on different surface types. These data were used to develop a model to predict friction and skid number with a high degree of accuracy. The instrument is able to collect data at highway speed, allowing accurate texture data collection on the entire network on an annual basis, and is small enough to attach to any surveying vehicle, so texture data can be collected as part of other operations, eliminating the need for an independent data collection effort. The development of this instrument provides not only savings but also enhances operational safety. The model was calibrated for 29 pavement sections in the Austin District, so the researchers recommend implementing the findings of this project and extending the calibration of the model to more pavement sections around the state.
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