Optimal Pavement Maintenance Strategy Based on the Relationship between Pavement Condition Index and Roughness Index

Pavement maintenance is crucial for ensuring road safety, reducing congestion, and minimizing repair costs. However, determining the optimal timing and strategy for pavement maintenance remains a challenge. This study investigated the correlation between the Pavement Condition Index (PCI) and Roughness Index (RI) to develop a numerical model for describing relationship of the two indices for pavement maintenance decision-making. Using statistical analysis and data visualization techniques, a significant correlation was found between PCI and RI. The study revealed a moderate correlation between PCI and IRI (R² = 0.47), indicating that 47% of PCI variations can be explained by IRI. While this suggests that the model is capturing a significant amount of the relationship between PCI and IRI, there is still room for improvement, as about 53% of the variance in PCI is not explained by the model. Since the PCI is a measure of road pavement conditions (on a scale typically ranging from 0 to 100), an RMSE of 7.77 means that the model's predictions for PCI are, on average, about 7 to 8 PCI units off from the actual value. The study established a clear relationship between pavement condition and surface roughness, enabling the development of a model to guide maintenance decisions. The study recommends prioritizing roads with PCI ≥ 50.3 and RI ≤ 5.12 m/km, alongside regular monitoring to ensure timely, cost-effective maintenance. Regular monitoring of PCI and RI values is also recommended to ensure timely maintenance and prevent costly repairs.