A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Pavement Deterioration Prediction Models for Non-urban Road Networks in Kerala
A properly maintained road network enhances the economic, industrial, and social development of the country. Furthermore, an efficient road network can provide better accessibility and mobility only when the road surface is in a good condition. As soon as the construction of pavement is completed, and the road is allowed to traffic, it starts deteriorating due to various reasons mainly due to the adverse climatic conditions, traffic loading, and age of the pavement. This necessitates the need for pavement maintenance. Pavement deterioration prediction models enable authorities to predict the possible condition of the pavement in the future, which aids in identifying the appropriate maintenance action over a period and reducing the life cycle cost. This study attempts to develop distress-based deterioration prediction models for flexible pavements for non-urban road networks in Kerala, India. The data collected from eleven road sections are used to model such as alligator cracking, pothole, patching, rutting and raveling, roughness, and Pavement Condition Index (PCI). The age of the pavement after the last renewal was found to influence the development and progression of deterioration of alligator carking, raveling, potholing, and roughness. The percentage density of raveling and age of pavement after the last renewal were found to influence the PCI value. The percentage of truck traffic volume during peak hours has the most minor influence on the models. These models can help the authorities to enhance the efficiency of decision-making by predicting the future condition of the pavement. This also can help in the maintenance planning and budget requirements for the maintenance alternatives.
Pavement Deterioration Prediction Models for Non-urban Road Networks in Kerala
A properly maintained road network enhances the economic, industrial, and social development of the country. Furthermore, an efficient road network can provide better accessibility and mobility only when the road surface is in a good condition. As soon as the construction of pavement is completed, and the road is allowed to traffic, it starts deteriorating due to various reasons mainly due to the adverse climatic conditions, traffic loading, and age of the pavement. This necessitates the need for pavement maintenance. Pavement deterioration prediction models enable authorities to predict the possible condition of the pavement in the future, which aids in identifying the appropriate maintenance action over a period and reducing the life cycle cost. This study attempts to develop distress-based deterioration prediction models for flexible pavements for non-urban road networks in Kerala, India. The data collected from eleven road sections are used to model such as alligator cracking, pothole, patching, rutting and raveling, roughness, and Pavement Condition Index (PCI). The age of the pavement after the last renewal was found to influence the development and progression of deterioration of alligator carking, raveling, potholing, and roughness. The percentage density of raveling and age of pavement after the last renewal were found to influence the PCI value. The percentage of truck traffic volume during peak hours has the most minor influence on the models. These models can help the authorities to enhance the efficiency of decision-making by predicting the future condition of the pavement. This also can help in the maintenance planning and budget requirements for the maintenance alternatives.
Pavement Deterioration Prediction Models for Non-urban Road Networks in Kerala
Lecture Notes in Civil Engineering
Veeraragavan, A. (editor) / Mathew, Samson (editor) / Ramakrishnan, Priya (editor) / Madhavan, Harikrishna (editor) / Divya, M. (author) / Ashalakshmi, V. M. (author) / Anjaneyulu, M. V. L. R. (author) / Sivakumar, M. (author)
International Conference on Innovative Methods and Practical Applications for Cognizant Transportation Systems ; 2023 ; Thiruvananthapuram, India
Cognizant Transportation Systems: Challenges and Opportunities ; Chapter: 16 ; 213-224
2024-11-30
12 pages
Article/Chapter (Book)
Electronic Resource
English
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