Abstract: To study the random vibration response of bridges under the combined effects of random traffic flow and road surface roughness excitation, a cellular automaton-based micro traffic-bridge coupling random vibration model (PEM-CA) is established using the pseudo excitation method. Based on D'Alembert’s principle, a multi-vehicle-bridge coupling vibration model is developed. Considering the influence of pavement roughness, the pseudo excitation method is introduced to construct a multi-point, fully independent stationary random excitation for the vehicle-bridge coupled virtual excitation load. A dual-lane cellular automaton model is used to simulate the micro traffic flow, forming the PEM-CA micro traffic-bridge coupling random vibration model. The computational results of the PEM-CA model are compared with the multi-vehicle-bridge coupled vibration response based on the pseudo excitation method (PEM-MV) and the statistical results from the multi-vehicle Monte Carlo method (MCM), verifying the accuracy of the PEM-CA model. The results show that the root mean square values of displacement, velocity, and acceleration response from the MCM fluctuate around the PEM-MV calculation values. The PEM-CA model results are identical to the PEM-MV results, with a maximum error of no more than 5.4% compared with the MCM. Under the action of free-flow traffic, the displacement, velocity vibration response of the first span of the bridge and the displacement vibration response of the middle span of the bridge are significantly affected by the fundamental frequency of the vehicle. The power spectral density curves of all of them have an obvious peak value at 2.3 Hz. The acceleration response of the first span of the bridge and the velocity and acceleration response of the middle span of the bridge are more significantly affected by the higher-order frequencies of the bridge. The study shows that different response locations on the bridge are affected by different high-order frequency components of the excitation. This study further enhances the ability to analyze the statistical effects of bridge random vibrations induced by microscopic traffic flow under road surface roughness excitation, and provides a new method for studying bridge vibrations under microscopic traffic conditions.