Assessment of Image-Based Data Collection and the AASHTO Provisional Standard for Cracking on Asphalt-Surfaced Pavements

The network-level pavement management system of the Kansas Department of Transportation (KDOT) is known as the Network Optimization System (NOS). For input, KDOT manually collects data on cracking severity and extent on its network annually. In this study, pavement surface images were collected and analyzed to evaluate the impact of AASHTO provisional standard PP 44-01 for asphalt-surfaced pavement-cracking data collection on NOS. The study covered approximately 262 km (164 mi) of in-service bituminous and composite pavements in Kansas. Nearly 50,000 images of the pavement surface were obtained for manual and automated evaluation of pavement condition. Two different processes of image analysis were compared with existing results from the KDOT annual survey. Transverse and fatigue crack severity and extent were manually interpreted following KDOT crack-rating algorithms for all sections. In addition, the sections were analyzed with an automated crack identification procedure following PP 44-01. The images corresponding to approximately a 5% sample rated by KDOT were identified. Comparative data were available for a manual distress survey on 5% samples (by KDOT) and image-based manual and automated interpretation on the 5% and 100% samples. Statistical analysis shows good agreement between the 5% sample and 100% sample results from the manual survey and image-based manual interpretation, respectively, for both crack types. This implies that a 5% pavement sample is adequate for describing crack severity and extent in NOS. Severity of fatigue cracks from the images was more difficult to rate, probably because of the descriptive nature of severity levels in the NOS algorithm. Agreement between the results from the manual image analysis on both 5% and 100% pavement samples and the KDOT manual survey is acceptable. However, the automated image analysis technique following the provisional AASHTO standard tends to overestimate severity of cracking.
Raman, M., Hossain, M., Miller, R., Cumberledge, G., Lee, H., & Kang, K. Assessment of Image-Based Data Collection and the AASHTO Provisional Standard for Cracking on Asphalt-Surfaced Pavements. 1889 1 116 - 125. 10.3141/1889-13.