The transportation industry is a high carbon emission industry, and China has also put forward strict requirements for the transportation industry to achieve carbon emission reduction. By measuring the total factor carbon emission efficiency of the transportation industry, we can understand the change trend and the influencing factors of the total factor carbon emissions. To fully consider the problem of multiple inputs and outputs in the transportation industry and obtain a more accurate efficiency evaluation value, this paper adopted the slack-based model-data envelopment analysis method and global Malmquist—Luenberger index to study the change in the total factor carbon emission performance of the transportation industry. The combination of static analysis and dynamic analysis was used to calculate the TFP of the transportation industry and increase the content of output indicators. The results indicate that the average TFP and GML index values exhibited significant heterogeneity nationwide. The values in Anhui and Hebei Provinces were greater than 1, and the average GML index values in Shanxi, Guangxi, and Yunnan were greater than 1. The eastern region performed well in terms of technical efficiency and scale efficiency. The technical efficiency in the central, western, and northeastern regions was optimal. In terms of influencing factors, the influencing factors causing the different carbon emission efficiencies in the four regions varied. Finally, corresponding policy suggestions were proposed.