Prediction of Road Condition and Smoothness for Flexible and Rigid Pavements in Louisiana Using Neural Networks [Technical Summary]

Details

• Creators:
  Wu, Zhong ; Zhang, Zhongjie "Doc"
• Corporate Creators:
  Louisiana Transportation Research Center
• Subject/TRT Terms:
  • Pavement performance
  • Pavement management systems
  • Neural networks
  • Flexible pavements
  • Smoothness
  • Rigid pavements
  • pavement performance modeling
  • artificial neural network
• Publication/ Report Number:
  694
• Resource Type:
  Brief
• Geographical Coverage:
  Louisiana ; United States
• Edition:
  Technical Summary
• Corporate Publisher:
  Louisiana Transportation Research Center
• Abstract:
  The objective of this research was to develop both short- and long- term pavement performance and deterioration models that can be used to estimate future pavement conditions and smoothness using ANN modeling. Specifically, the short-term models were for the prediction of 2- and 4-year future pavement surface cracking percentages for the current Louisiana interstate and national highway system (NHS) pavement network. The long-term models were developed as alternatives to DOTD's family curve models used in asphalt pavement maintenance and rehabilitation treatment selection.
• Format:
  PDF
• Funding:
  SPR: TT-Fed/TT-Reg - 5 ; DOTLT1000376 ; LTRC Project No. 21-1P
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/74079/dot_74079_DS1.pdf
• File Type:
  [PDF - 228.01 KB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:9a7572786348abb3ae295ab9dc3638ea5646f4ad3fbbb4f0087bb850a3cc2ce361ee346f0bb3c0a79d5a5e7f3169144c048b328c996d2d34dac3ac415ec0dc49