Validation of an indirect data collection method to assess airport pavement condition

Abstract

In this study the authors compare two methods for airport asphalt pavement distress data collection applied on the main runway of Amílcar Cabral international airport, located at Sal Island in Cape Verde. The two methods used for testing were traditional visual inspection (on-foot) and an indirect method using a vehicle equipped with image capture and recording, lasers and geolocation devices (in-vehicle inspection). The aim of this research is to contribute to the validation of the proposed low-cost in-vehicle pavement distress inspection system with semiautomatic data processing in order to be considered in the implementation of the pavement condition assessment component of airport pavement management systems (APMS). This is a particularly important component as from the collected distress data it is possible to assess the condition of the pavements and define intervention strategies. Validation of the indirect data collection method is evaluated by statistical comparison of the collected distress data and pavement condition index (PCI) obtained from both methods. Statistically non-significant differences between the result sets validate the proposed indirect method, however the analysis evidenced two aspects that need improvement in the proposed system, namely the quality of the captured images to identify distresses with lower severity level and inspector training for proper allocation of severity levels during image analysis. This results in significant advantages considering that the total amount of the runway pavement area is inspected. Inspection time is reduced and data collection cost can be reduced. Processing and results visualization on GIS environment allows revaluation of the dataset on the in-vehicle method. Data interpretation and measurements quality control becomes simpler and faster.

Keywords

• Airport pavement management system
• Data collection
• Image processing
• Statistical comparison