Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3582
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dc.contributor.authorNilawfer, S-
dc.contributor.authorMadushani, S-
dc.contributor.authorSandamal, K-
dc.contributor.authorGomes, A-
dc.date.accessioned2023-11-13T10:41:27Z-
dc.date.available2023-11-13T10:41:27Z-
dc.date.issued2023-03-25-
dc.identifier.issn2961 5011-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3582-
dc.description.abstractExpressways play a pivotal role in industrial and export development in Sri Lanka by providing access to the production sector in addition to the passenger transport in between transport hubs. A reliable pavement performance prediction model is essential for pavement management systems to optimize the cost of maintenance and rehabilitation planning. In this study, pavement roughness prediction of expressways in the long-term performance was conducted using International Roughness Index (IRI) which is used as a global parameter to measure the ride comfort of road users and the unevenness of pavement. Firstly, initial IRI values for Sri Lankan expressways were established by using current data and found that, it varies between 0.90 to 1.45 m/km. Secondly, IRI prediction model developed with cumulative traffic volume, considering outer lane IRI as the dependent variable due to higher deterioration rate compared to inner lane. Moreover, it was found that, there is a good relationship between IRI with cumulative traffic with R-squared of 0.60. Further, it can be concluded that, the outcomes of this study can be effectively used for Sri Lankan context in long term performance evaluation and expressway maintenance planning.en_US
dc.language.isoenen_US
dc.publisherSri Lanka Institute of Information Technologyen_US
dc.relation.ispartofseriesProceedings of the SLIIT International Conference On Engineering and Technology;VOL 2-
dc.subjectInternational Roughness Indexen_US
dc.subjectExpresswaysen_US
dc.subjectPavement Deteriorationen_US
dc.subjectCumulative trafficen_US
dc.titleDevelopment of Roughness Prediction Model for Sri Lankan Expresswaysen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.54389/BDAD1592en_US
Appears in Collections:Proceedings of the SLIIT International Conference on Engineering and Technology Vol. 02, 2023

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