Impact of Condition Monitoring Frequency for Multiple Lane Highways on Pavement Management Decisions

摘要

Highway agencies collect pavement condition data over time to manage their road network.While most agencies collect sensor-based data (roughness, rut depth, and faulting) on a yearlybasis, image-based data (cracking and other pavement defects) are collected every other year oron a three-year interval. The main reason for variable monitoring frequency is the relativedifficulties (cost, resources, and technology) in collecting and processing imaging data.Furthermore, pavement condition data are generally collected only for outer lanes on multilanehighways. However, for these roads, there is a need to evaluate the appropriate condition datacollection interval for inner lanes, since most highway agencies use different timings to fix andmaintain those lanes. In this paper, pavement condition data from MnRoad test sections wereanalyzed to determine the appropriate monitoring frequency for roads with multiple lanes.Results of the analyses show that for load-related distress (i.e., fatigue cracking and rutting); alonger monitoring interval can be adopted for inner lanes. In the case of non-load-relateddistresses (i.e., transverse and block cracking), the distress growth could be similar betweenouter and inner lanes; therefore, only monitoring of outer lane is warranted. For functionaldistresses (e.g., ride quality), the difference in international roughness index (IRI) can beattributed to both load and non-load related distress in multiple lanes; thus, a differentmonitoring interval can be adopted. In addition, the paper documents a statistical methodology todetermine the most appropriate monitoring intervals for inner lanes considering performancepredictions.