ANALYSIS AND MODELLING OF PAVEMENT CONDITION INDEX

The development of a PCI (Pavement Condition Index) model integrated with Paver and ArcGIS involves creating a robust system for assessing and managing pavement conditions. Paver software facilitates data collection and analysis, while ArcGIS enables spatial visualization and analysis. This integration aims to enhance the accuracy and efficiency of evaluating pavement conditions, leading to better-informed decision-making in prioritizing maintenance strategies. To determine the Level of Service (LOS) for a specific road segment using PCI, the model evaluates the pavement condition by considering various distress factors such as cracking, rutting, surface deterioration, and other observable issues. These distresses are assigned numerical values, allowing the PCI to quantify the overall pavement condition, which in turn determines the LOS. Following the PCI assessment, maintenance priorities can be established based on the severity of distresses identified. Higher priority should be given to segments with lower PCI scores, indicating more significant distresses that require immediate attention. Conversely, segments with higher PCI scores may need less urgent maintenance but should still be monitored to prevent further deterioration. The integration of PCI, Paver, and ArcGIS offers a comprehensive approach to pavement management, enabling data-driven decision-making and efficient allocation of resources for pavement maintenance and rehabilitation, thereby ensuring safer and more durable road infrastructure.