The recorded traffic data shows that traffic loads have been increasing. In this study, based on the long-term health monitoring data collected from Anhui Province, the annual average hourly traffic (AAHT) is defined to take into account the periodical and seasonal change of traffic volumes, furthermore, an autoregressive moving average model (SARIMA) is established to simulate truck loads in the future. At the same time, several truck load models are developed with the statistics of the key parameters of truck data, and then loaded one by one on the finite element model of a T-bridge, to calculate the fatigue damage induced by the non-stationary increases of truck traffic. The results show that the AAHT-based SARIMA model is accurate and efficient for predicting traffic loads, moreover, the non-stationary increase of traffic loads will significantly jeopardize bridge structures due to the fatigue damage caused. Specifically, the fatigue damage will be increased by about 50% when considering this kind of non-stationary increase.