Abstract
The main objective of this research work was to investigate the potential of integration of geographic information system (GIS), global positioning system (GPS) and computer vision system (CVS) for the purpose of flexible pavement distresses classifications and maintenance priorities. The classification process included distress type, distress severity level and options for repair. A system scheme that integrated the above-mentioned systems was developed. The system utilized the data collected by GPS and a PC-based vision system in a GIS environment. GIS Arcview software was used for the purpose of data display, query, manipulation and analysis. The developed system provided a safer pavement condition data collection technique, flexible data storage, archiving, updating and maintenance priorities updating. Maintenance priorities were assigned based on priority indices values computed by priority index (PI) or available budget criterion. This technique was cost-effective and offered wise-based decision making for different maintenance activities and programs. Using average daily traffic (ADT), distance from maintenance unit ( R), pavement section area and pavement age, statistical models were developed to forecast pavement distress quantities. It was found that ADT and pavement age variables were the most significant factors in the distresses quantification.
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