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Pavement Deterioration Predictive Models for a Section of Ijokodo-Apete Road Ibadan, Nigeria
Author(s) -
Mogbo Nwabueze Onyebuchi,
Tiza Toryila Michael,
Shajan Peter
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e7214.088619
Subject(s) - subgrade , traffic volume , transport engineering , section (typography) , regression analysis , engineering , forensic engineering , civil engineering , environmental science , computer science , statistics , mathematics , operating system
A road pavement is a structure composed of structural elements, whose function is to protect the natural subgrade and to carry the traffic safely and economically. When the roads are open to traffic, the pavements deteriorate with time due to the combined influence of the traffic, construction material and the environment. Due to the great complexity of the road deterioration process, performance models are the best approximate predictors of expected conditions. Hence, the aim of this research work is to develop a predictive model for the rate of potholes deterioration for a section of the Ijokodo –Apete road in Ido Local Government Area of Ibadan. In actualizing the above aim, a reconnaissance survey and inventory were conducted on the selected road section and potholes were discovered as the predominant pavement distresses, chainages were established for easy identification of the potholes positions, some selected potholes were measured and their volume change was monitored. The pavement structural evaluation and traffic volume data were collected. Regression models were developed for the potholes deterioration rate using SPSS (Statistical package for social sciences) package. Conclusively, the model with the highest coefficient of determinant (R2) and least standard error was selected as the reliable model and was used to determine the deterioration rate of the independent variables(traffic volume and structural number) selected at random.

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