Development of roughness prediction models using Alberta transportation's pavement management system

Alberta Transportation conducts annual automated International Roughness Index (IRI) surveys on the core highway network in the province. The measures are used to rate the physical condition of each pavement section in the Pavement Management System (PMS) to establish rehabilitation strategies for the year. Future rehabilitation needs are predicted based on highway sections' age, using the Highway Pavement Management Application (HPMA) sigmoidal IRI function, which does not consider the effect of climatic and pavement distresses or structural design. IRI prediction models incorporated in the Mechanistic Empirical Pavement Design Guide (MEPDG) and Highway Development and Management (HDM) require comprehensive and detailed distress records. Such data records are not fully available for Alberta yet, making it difficult to calibrate these models for local conditions. The present study focuses on identifying the significant climatic, structural and distress-related variables to IRI for Alberta's highway network. The data available in Alberta's PMS was used to develop two new IRI prediction models for New, and Straight Overlaid Asphalt Concrete (AC) sections with Granular Base Course (GBC). Regression analysis revealed that variables such as age, traffic, subgrade fines, rutting, transverse and miscellaneous cracking are most significant to IRI for new AC sections. Further, IRI for overlaid AC sections was found to be dependent upon age, traffic, Freezing Index (FI), GBC and AC overlay thickness, subgrade soil plasticity and rutting. The model for new AC sections was able to predict IRI for the General Pavement Sections (GPS)-1 of the Long Term Pavement Performance (LTPP) in Alberta, Manitoba and Saskatchewan.

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  • English

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Filing Info

  • Accession Number: 01505296
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 27 2014 11:03AM