LAUSR

Abstract Structural condition data is one of the critical data elements in pavement design and management for determining the needs of pavements rehabilitation. However, it is time-consuming and may raise safety concerns to use Falling Weight Deflectometer (FWD) for collecting pavement structure data at network-level. The traffic-speed deflection device seems to be a promising way to collect network-level structural capacity information in a safe and timely manner. To better understand the deflection collected from traffic-speed deflection devices, this paper focused on the influence of pavement data on deflection measurements. The pavement data in this study included pavement structure and surface condition data. The associations between deflection and pavement data was assessed by non-parametric rank correlation analysis. The pavement data elements that may influence deflection measurement were identified by random forest regression models. The relationship between deflection indices and surface condition indices were quantified by Tukey’s HSD test. Results indicated that D0 and SCI appeared to be more influenced by pavement type, surface roughness and distress than SCI of subgrade. IRI on the right wheel path tended to be more closely associated with SCI than other surface condition data. The change of surface condition indices appeared to be more sensitive to deflection indices on flexible pavements than on composite pavements.