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Real driving emission (RDE) tests are influenced by factors such as data processing methods, driving behaviors, and environmental conditions. Therefore, being able to effectively identify test influence factors is particularly important for RDE emissions-based calibrations. In order to investigate the correlation between data processing methods, driving behaviors and vehicle emissions, the moving average window (MAW) method and cumulative averaging (CA) method were used to compare and analyze the RDE tests data of a light-duty gasoline vehicle under different driving modes in this study. The results showed that in MAW method, carbon monoxide (CO) emissions of urban and total trips calculated by using the front to back window division order were slightly lower compared to the back to front window division order, with an average reduction of 4.68% and 6.33%, respectively. For carbon dioxide (CO2) emissions, the order of window division had the opposite effect as for CO emissions.