Vehicle tracking for bridge load dynamics using vision techniques

Abstract

Structural health monitoring for bridges is an important field that is growing in necessity in the United States with the aging of the interstate and highway system. Most health monitoring systems rely on detecting the motion of the bridge through strain gauges, accelerometers and GPS units. These sensors are very good at measuring the output motion of the bridge, but do not take into account the input signal from the vehicles. Adding the ability to directly measure the location of the input forces on the bridge would improve the ability to model the bridge dynamics. In this paper we propose a system that can identify a vehicle on a bridge and track its location through multiple video frames. Previous work in vehicle tracking has focused on traffic pattern research but has not been adequately translated into a sensing application for structural dynamics. The algorithm was tested and the results show that vehicles are able to be tracked along a bridge with acceptable error in the location output. This method allows a researcher to provide a dynamic input load to his model, rather than estimating or using some load distribution. Combining this with the structural sensing on the bridge will allow for more accurate modeling of the bridge dynamics.