Development of Probabilistic Methodology for Evaluating Pavement Condition Index for Flexible Pavement

Road network, being an integral part of the development of a country must be maintained in functional condition. Generally, maintenance of the road involves prior evaluation of road condition so as to implement appropriate maintenance. Therefore, precise evaluation of road condition should be given due consideration prior to the implementation of maintenance process. This paper demonstrates a methodology that has been developed on the basis of probabilistic approach for evaluating the condition of the road. The proposed study assumes that the condition of road follows a probabilistic behavior ranging from the best condition to worst and attempt to evaluate the condition of the road using surface distress survey based on probabilistic approach. Surface distress survey was carried out on three samples of a road that can be clearly identified as best, average, and worst condition samples based on the total deduct values for different distresses in each sample. The probabilistic pavement condition index (PCI) is then evaluated using the total deduct values in each sample. Validation for six roads of Jawhar Taluka, Palghar District, Maharashtra State, India, was considered for surface distress condition survey using the proposed method. Twelve pavement distresses were inspected and measured on the field with traditional approaches avoiding expensive and sophisticated instruments. The study concluded that the proposed method can be used where limited fund and less time are available for inspection and maintenance of roads.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 417-427
  • Monograph Title: Urbanization Challenges in Emerging Economies: Energy and Water Infrastructure; Transportation Infrastructure; and Planning and Financing

Subject/Index Terms

Filing Info

  • Accession Number: 01700653
  • Record Type: Publication
  • ISBN: 9780784482025
  • Files: TRIS, ASCE
  • Created Date: Apr 1 2019 10:15AM