Efficient Model for Predicting Friction on Texas Highway Network

Details

• Creators:
  Sabillon, Christian ; Hernandez, Joaquin ; Li, Ruohan ; Prozzi, Jorge A.
• Corporate Creators:
  University of Texas at Austin. Center for Transportation Research
• Corporate Contributors:
  Texas Department of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Macrotexture
  • Microtexture
  • Pavements
  • Skid resistance
  • Testing equipment
  • Texture
  • Friction
  • Highways
  • Data models
  • Pavement surface
  More +
• Publication/ Report Number:
  FHWA/TX-22/0-7031-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas ; United States
• Edition:
  September 2019 – December 2021
• Corporate Publisher:
  University of Texas at Austin. Center for Transportation Research
• 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.
• Format:
  PDF
• Funding:
  0-7031
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/66238/dot_66238_DS1.pdf
• File Type:
  [PDF - 9.30 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:64976615b90574487b7c81697b8d4e48025e56e71c8cbbc804119ac997ce2a1e