Weight-in-Motion-Based Ambient Truck Characteristic Identification in Highway Bridges

Abstract

Ambient truck classification and weight data have been used in numerous transportation applications, focusing on highway safety. Specifically, ambient truck characteristics identified from Weight-In-Motion (WIM) data obtained from vehicle weigh stations have been considered to be likely candidates to better understand structural response of highway bridges to live-load events. This paper provides a framework to explicitly identify WIM-based ambient truck characteristics specific to highway bridges of interest. As an application of the framework, a highway steel I-girder bridge in the United States was selected and a network of strain sensors was installed on the bridge deck. Multiple strain time history data sets resulting from ambient trucks were measured and evaluated via a structural health monitoring (SHM) system with strain sensors. Each set of strain data representing a single truck, which cross the bridge, was used to identify its features, such as axle numbers and spacings. WIM trucks specific to each set were also characterized by examining the monitored strain time history patterns. These patterns make it possible to the identification of ambient WIM truck configurations. WIM data were obtained from weigh stations located adjacent the bridge. It is anticipated that this work will result in the creation of ambient truck pools on a specific bridge. Their pools will be used as live load inputs in the bridge model to investigate the structural behavior and to evaluate the bridge health conditions..