Field Performance of Deep-Learning Based Fully Automated Cracking Analysis and Its Potential for PCI Surveys

You are here: Homepage > Search

Field Performance of Deep-Learning Based Fully Automated Cracking Analysis and Its Potential for PCI Surveys

Yang, Guangwei / Wang, Kelvin C. P. / Zhang, Allen / Sun, Yangyong / Li, Baoxian / O'Connell, Kenneth J.

Pavement distress data has been widely collected through pavement survey to evaluate roadway condition. Despite rapid advancements in automated pavement distress data collection, the implementation of the widely used pavement condition index (PCI) still requires extensive manual labor either in tradition manual survey or image-based PCI inspections. This paper proposes a deep-learning (DL) based automatic pavement cracking detection algorithm and further evaluates a potential for automatic PCI survey with the obtained cracking results on asphalt pavement. The pavement two- and three-dimensional (2D and 3D) images are collected via the state-of-the-art PaveVision3D imaging system on two asphalt sites in Maryland. The automatic lane marking detection is performed on the 2D images to define the lane width for the following cracking detection. The DL based CrackNet automates the detection of the cracking information from the 3D images. Cracking information for alligator, longitudinal, and transverse cracking are summarized to automatically calculate the PCI numbers. The high correlations between the fully automated PCI results and the historical PCI results indicate the DL based automatic PCI calculation method produces reasonable PCI numbers with minimum human intervention.

Access

Check access

Check availability in my library

Order at Subito €

Export, share and cite

Document information

Title :

Field Performance of Deep-Learning Based Fully Automated Cracking Analysis and Its Potential for PCI Surveys

Contributors:

Yang, Guangwei (author) / Wang, Kelvin C. P. (author) / Zhang, Allen (author) / Sun, Yangyong (author) / Li, Baoxian (author) / O'Connell, Kenneth J. (author)

Conference:

International Airfield and Highway Pavements Conference 2019 ; 2019 ; Chicago, Illinois

Published in:

Airfield and Highway Pavements 2019 ; 1-9

Publication date :

2019-07-18

ISBN :

9780784482476

DOI :

https://doi.org/10.1061/9780784482476.001

Type of media :

Conference paper