dc.description.abstract |
Pavement maintenance management system motivates to provide a scientific
tool for maintenance and rehabilitation of roads pavement at desired serviceability
levels. In view of the fund’s constraints and the need for judicious spending
of available resources, the maintenance planning and budgeting are required to be
done based on scientific methods. Unfortunately, the current maintenance practices
are ad-hoc and subjective in nature. Pavement condition responsive maintenance is
very useful for judicious disbursement of maintenance funds. The objective of this
paper is to select a feasible treatment for routine maintenance based on pavement
condition parameters of flexible pavement using Fuzzy Logic Expert System (FLES).
Six different national highways have been selected to provide the maintenance based
on the PCI, traffic volume, pavement age, precipitation, temperature and budget.
FLES offers a convenient tool to better represent the uncertainty involved in pavement
condition rating and assessment. The pavement maintenance treatment needs
are generally determined based on the results of visual inspection, which in most of
the cases does not give an adequate representation of pavement condition. Treatment
selection FLES model has considered anticipated distresses-based condition index,
anticipated traffic, and prevailing climate, age of the pavement and budget for treatments.
Model predicts treatment types based upon their expected life. The triangular
membership function for all the parameter is considered and analyzed with sufficient
number of fuzzy rules as suggested by the maintenance engineers. The predicted
result was compared with the twenty-five maintenance engineer’s responses, which
shows homological results. Hence, this approach may provide an appropriate and
economically viable maintenance treatment. |
en_US |