Sensor Fusion Approach to Assess Pavement Condition and Maintenance Effectiveness,, the Issue, Findings and Research. PROJECT BRIEF.

摘要

This research developed an approach to enable smart pavements. The embedded sensors report parameters to determine traffic-loading characteristics, structural health, and the ride quality pavements provide to the traveling public. This technology will enable agencies to remotely monitor pavement assets comprehensively, without regularly deploying expensive field equipment and personnel. In addition to making the sensors more rugged so that they would last throughout the asset lifecycle, this research developed a new method that extended the capability of the sensors beyond an ability to measure just pavement loading and condition parameters. Specifically, the research linked the sensor output to common roughness indices. To maintain a high accuracy of measuring numerous pavement loading and condition parameters throughout the life cycle of the pavement asset, an external method of roughness measurement provided continuous calibration for the sensors. The connected vehicle method is a novel technique that utilizes regular vehicles with wireless connectivity to measure localized roughness.