Title: A critical review of flexible pavement performance models developed for Indian perspective
Abstract: The capability to forecast future pavement condition has been a question of common interest for the economic reasons for Pavement Management Systems (PMS) and the need to develop an intelligent prioritization schedule has become even more important for the sake of efficiency. If an efficient pavement performance prediction model can be developed based on the past pavement performance data, the remaining service lives of pavements can be forecasted. The flexible pavement deterioration model involves the complex interaction between vehicles, environment and the pavement structure and surface. The road deterioration models predict the deterioration of the pavement over time and under traffic, which is manifested in various kinds of distress. But each mode of distress develops and professes at different rates in different environments, different traffic conditions and different terrains of India. As India is a vast country having different terrain and environmental conditions which gives it a continental nature, so it becomes necessary to cautiously review the performance models for particular conditions. Various performance models relating the pavement distresses like cracking, raveling potholing and roughness with pavement indexes and remaining service life of pavement are analyzed and developed by various researchers of India. But most of these models are limited to particular conditions and biased to certain environments. A detailed review of various performance models developed for flexible pavements in Indian conditions are reported in this study. With the help of this review, the authors can evaluate the usefulness of the various models in some particular condition having similar traffic characteristics, soil types, climatic conditions, terrain type and pavement composition. A brief study and discussion on the gaps and limitations of the different performance models are also given in this study. After the review of the various types of prediction models, it was found that age is by far the most significant predictor of serviceability. The traffic volume and weight expressed in terms of equivalent single-axle loads (ESALs) and the structural makeup of the pavement described by the composite structural number play only a secondary role in forecasting performance of pavements.
Publication Year: 2012
Publication Date: 2012-03-01
Language: en
Type: review
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Cited By Count: 6
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