Performance model for asphalt concrete pavement based on the fuzzy logic approach

    Mustafa Karaşahin Info
    Serdal Terzi Info
DOI: https://doi.org/10.3846/16484142.2014.893926

Abstract

Accurate pavement performance estimation is very important for the managing and maintaining of surface transportation infrastructure. In the present study, a new model for the prediction of present and future performance of flexible pavements is developed using the fuzzy logic approach. The database of the model is able to use numerical measurements and also linguistic statements. Many models developed in the literature neglect the parameters that have little bearing on performance. However, it is a well known fact that these parameters do have an effect on performance to some degree. Different parameters were considered in the model as accepted by the authorities, and as having little bearing on performance. For each parameter, a certain weight was appointed, and the parameters that affected performance were assigned greater weights while the others were assigned smaller weights. As a result, the current model in the fuzzy logic approach is more flexible than the current Pavement Serviceability Index (PSI) and Pavement Condition Index (PCI) models. The model is different from previous fuzzy logic based models. Two stages of the fuzzy logic approach were used in these models. Since this new methodology does not need any mechanical tests, the model can be adopted by the Pavement Management System (PMS) of developing countries.

First Published Online: 25 Mar 2014

Keywords:

pavement performance, performance prediction, fuzzy logic

How to Cite

Karaşahin, M., & Terzi, S. (2014). Performance model for asphalt concrete pavement based on the fuzzy logic approach. Transport, 29(1), 18–27. https://doi.org/10.3846/16484142.2014.893926

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March 31, 2014
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2014-03-31

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Original Article

How to Cite

Karaşahin, M., & Terzi, S. (2014). Performance model for asphalt concrete pavement based on the fuzzy logic approach. Transport, 29(1), 18–27. https://doi.org/10.3846/16484142.2014.893926

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