Characterization of environmental loads related concrete pavement deflection behavior using Light Detection and Ranging technology

Abstract

Repeated deflection behavior resulting from temperature and moisture variations across concrete pavement depth causes curling and warping of Portland cement concrete (PCC) pavement systems. Although curling and warping issues have been investigated extensively, there are no standardized methods or procedures currently available to characterize the degree/magnitude of this in situ environmental load-related deflection. This study discusses the development of a detailed procedure for assessing environmental load-related deflection of concrete pavement using a Light Detection and Ranging (LiDAR) system. LiDAR systems have been recognized as an advanced technology for transportation infrastructure inspection but have not been widely investigated for measuring environmental load-related deflection of concrete pavements. In this study, field surveys were conducted on six identified concrete pavement sites in Iowa by scanning the concrete slab surfaces using the stationary LiDAR instrument. Based on dense point cloud data obtained by the LiDAR instrument, a data processing algorithm was developed to obtain the degrees of environmental load-related deflection. The degrees of deflection obtained were correlated to variations in pavement performance, mix design, pavement design, and construction details at each site. The results and findings from this study describe a potentially novel method of using LiDAR system for environmental load-related deflection characterization of concrete pavement.