Assessment of Data Quality for Evaluations of Manual Pavement Distress

Assessment of the conditions of current assets is a task of major relevance in a transportation agency asset management program. It not only provides information on the current condition of the asset but also helps the agency make decisions on future maintenance and rehabilitation activities. Although low-volume roadways represent a large proportion of the total road network in the United States, little research on the management of these assets has been done. Two major data collection techniques are used for roadway condition assessment: manual and automated. Although automated techniques have been found to be safer and quicker, manual condition surveys have been proven to offer preciseness and cost-effectiveness. In the case of low-volume roadway assessment, for which the funds available to asset managers are limited, manual condition surveys are often preferred. Nevertheless, manual condition surveys must address the potential subjectivity of the results. Therefore, agencies could benefit from a system for ensuring quality on manual condition surveys. This paper proposes a framework for assessment of data quality and presents a case study of its implementation in the Northern New Mexico Pavement Evaluation Program. The proposed framework is easily implementable and able to identify potential and actual data collection issues. The framework can be used as part of an asset management program and could be particularly beneficial in the case of low-volume roads.