Plenty of bridges in U.S. are suffering from prestress force loss and foundation settlements. The loss of prestress force in bridge load-carrying members such as girders may lead to the malfunction and even failure of the prestressed bridges that comprises more than 55% of all new and replaced bridges built in US between the year 2000 and 2012. Settlement of foundations supporting the bridge piers and abutments impairs the superstructure integrity and serviceability of the bridge, or even collapses the bridge if the settlement is over a certain limit. In present study, the dynamic interaction between vehicles and the bridges subjected to prestress force loss and foundation settlement has been investigated. Based on modal superposition technique and principal of virtual works, new bridge-vehicle interaction models have been created to take the effects of prestress and foundation settlement on dynamic bridge and vehicle responses into account. With the developed models, numerical simulations have been performed to show that the prestress force makes the distribution of impact factors along the bridge unbalanced and the existence of foundation settlement may couple with road surface roughness of the bridge deck to possess an aggregated overall effect amplifying the bridge responses. In general, the vehicle responses are vulnerable to the prestress force loss and foundation settlement, which harms the riding comfort of passengers. The existed direct and indirect methods used for prestress loss identification are all based on the measurement collected from sensors deployed on the outside or inside of the bridge, which is not only costly but also inconvenient. The current study proposes to detect the prestress force loss of the bridge through the analysis of vehicle responses. Through simulations, it is found that light, low-frequency vehicles moving at low speeds have a better performance in detecting the bridge prestress loss than the heavy, high-frequency vehicles with high speeds. The advantage of the proposed method is that it only needs a few sensors installed on the vehicle, and works without interrupting the ongoing traffic, which is efficient and cost-effective.