, Professor, Electrical and Computer Engineering
Correct interpretation of the results of load response tests requires precise measurement of the relative position between sensors embedded into the pavement and the path followed by a test vehicle. The goal of this project is to replace the current laborious and error prone vehicle localization process by a reliable automated system that determines the vehicle position relative to the pavement sensors with an accuracy of 2 cm or better using primarily real-time RTK-GPS data. Using this information, the system will determine whether to accept or reject sensor data. An optional project component is to reconstruct the actual load test data that would have been recorded by a sensor positioned along the path actually followed by the test vehicle. The project consists of two connected sub-projects: vehicle position tracking and automated faultmeter control software. The vehicle position tracking subproject develops a reliable method for collecting accurate load response test data regardless of the actual path followed by the test vehicle. The automated faultmeter control software subproject develops LabView compatible software to control data collection and automate the transfer of the data to the MnROAD database.