The access of a large number of new energy sources and electric vehicles leads to large net load changes in an electric thermal transportation integrated energy system. This requires the system to have a certain flexibility to match the uncertainty on both sides of the source load. How to deal with the contradiction between uncertainty and flexibility and how to achieve the balance between economy and flexibility are difficult problems faced by the electric thermal transportation integrated energy system. In this paper, a multi-objective interval optimal operation model of electric thermal transportation integrated energy system considering flexibility is proposed. Aiming at minimizing economic cost and maximizing system flexibility, the economy and flexibility of the system are comprehensively balanced. The uncertainty of wind power output and electric vehicle load is described by interval mathematics, and the traditional equation constraint is transformed into an interval expression to make it more tractable. An improved multi-objective quantum immune algorithm is used to solve the optimization model. Taking an integrated energy system in northern Liaoning as an example, three different scenarios are set to verify the effectiveness of the proposed method. This work is supported by the Science and Technology Project of State Grid Corporation of China (No. 2021YF-48).