Investigation into Multi-Timestamp High-Resolution Faulting Measurements for Jointed Concrete Pavements Using 3D Pavement Surface Data

As 3D laser imaging systems have become mainstream among highway agencies for automated pavement condition assessment, obtaining high-resolution joint faulting measurements along the full length of each transverse joint in surveyed jointed concrete pavement segments has become feasible. Leveraging this newly available sensor-based data is essential to improve the understanding of faulting behavior, characterizing deterioration mechanisms, and establishing consistent reporting practices at both the joint and segment levels. This study conducts a detailed investigation of faulting behavior using multi-timestamp high-resolution measurements from a 9.2 mi undoweled jointed plain concrete pavement section on Georgia’s Interstate 16 near Macon, U.S., surveyed from 2013 to 2018 by the Georgia Tech sensing van. The analysis includes zone-based spatial analysis along the joint, examination of how representative faulting metrics influence condition reporting, assessment of negative faulting occurrences, and deterioration analysis at both the joint and segment levels. Findings show that faulting varies substantially along the transverse joint and cannot be characterized reliably by a single location such as the right wheel path. The choice of a representative faulting metric therefore plays a significant role in determining reported condition and shaping observed trends across survey cycles. A notable portion of joints exhibited partial or complete negative faulting, underscoring the need for guidance on how these cases should be treated for assessment and how they should be aggregated at the segment scale. Segment-level results showed consistent increases in faulting, while joint-level trends varied depending on factors such as slab cracking and base support conditions.