Network-Level Pavement Condition Monitoring in Oklahoma using Continuous Pavement Deflection Data

Abstract: Traffic Speed Deflection Devices (TSDDs) offer an innovative alternative for network-level pavement condition monitoring, and provide continuous deflection measurements at traffic speed, eliminating the need for lane closures or traffic control. This modern pavement condition assessment approach facilitates comprehensive integration of both functional and structural conditions into pavement management decisions, moving beyond the traditional emphasis on functional parameters. In this study, TSDD data was collected from various sections of Interstate 35 and 40 in Oklahoma, with the aim of potentially integrating it into the Oklahoma Department of Transportation’s (ODOT) pavement maintenance planning process. Analysis of the data revealed significant variabilities in the deflection basin shape, which can be attributed to differences in pavement types, layer conditions, and external factors. To account for these influences, different analysis techniques were applied after data segmentation. One key approach involved calculating the sliding variance of deflection under wheel load, which effectively identified deflection variations caused by physical structures like approach roads, interchanges, and bridges. Additionally, wholistic analysis of the entire deflection basin, rather than individual deflection parameters, was used to assess the overall structural condition of the pavement. This process allowed for a tailored analysis of pavement deflection data based on the unique loading responses of different pavement types. By combining these analytical methods with pavement cores collected in the field, it is possible to establish threshold values that identify pavement deterioration within specific categories. Overall, this approach presents a wholistic picture of the pavement network’s condition and will facilitate accurate and effective pavement management strategies. This paper will present different data analysis techniques applied to the data in this project and will highlight key findings with potential implications to pavement maintenance and rehabilitation decisions.