As part of a system for structural health monitoring, it is required to determine the spatial and temporal distributions of vertical loads arising from heavy trucks driven on flexible bridge structures. An instrumented truck is used to generate the input loads and estimate the load time histories. The truck can carry a range of sensors; however direct measurement of vertical tire loads between the tires and the structure is not considered realistic. The dynamic loads are to be estimated from the sensor outputs. These are affected by both truck and bridge dynamics and these must be accounted for within the load estimation process. Estimation may be susceptible to many factors including static mass distribution, vehicle longitudinal motion, variations in lateral position on the bridge, as well as any surface unevenness. The focus of this paper is on using high fidelity simulation models to develop appropriate methodologies for load estimation which optimize the use of sensors on the truck. The estimation methods are evaluated in the context of any loss of accuracy in the predicted bridge response and in particular the coherency between inputs and outputs. It is proposed that using only static tire load data, GPS satellite data, string-potentiometers and accelerometer measurements, a robust measurement system can be constructed. The goal is to use near real-time processing of truck sensor data so that dynamic truck loads are available; when combined with data from separate bridge-mounted sensors, the structural performance of the structure can be evaluated.