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Maintenance prioritization of interlocking concrete block pavement using fuzzy logic

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The combined influence of traffic and environment causes every pavement to deteriorate over time. Maintenance actions help to delay the rate of pavement deterioration. Pavement maintenance demand large amount of fund, resources and time. Prioritization of maintenance work enables to allocate fund and resources in an effective way based on the performance evaluation of the pavement section(s). There are different maintenance prioritization mechanisms exist to evaluate a pavement. From the review of past literature, it is observed that fuzzy logic has not been used to evaluate interlocking concrete block pavements (ICBP). This research is an attempt to implement fuzzy logic for the purpose of maintenance prioritization on ICBP. The distresses of ICBP considered in this study are rutting, depression and damaged paver blocks. The distress density is given as inputs in the fuzzy prioritization model. The outputs are the pavement condition index (PCI) and the maintenance strategy to be adopted. An experts’ survey was conducted to define the boundaries of the membership functions of the input (distresses) and output (PCI and maintenance strategies) parameters. The triangular membership function is used in this study. The maintenance strategies suggested are routine and preventive maintenance, major and minor rehabilitation and reconstruction. The fuzzy model developed in this work has been demonstrated with a case study.

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Correspondence to Ripunjoy Gogoi.

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Peer review under responsibility of Chinese Society of Pavement Engineering.

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Gogoi, R., Dutta, B. Maintenance prioritization of interlocking concrete block pavement using fuzzy logic. Int. J. Pavement Res. Technol. 13, 168–175 (2020).

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