Autonomous driving is an important direction for the future development of the transportation and the automotive field. Planning and decision-making as a key module has always been an important area of autonomous driving research. The research interest of the community is expanding from single-vehicle driving to multi-vehicle driving in hybrid traffic scenarios. The main forthcoming challenge is to generate high-quality trajectories that conform to vehicle dynamics and do not collide with road boundaries and other traffic participants in complicated and dynamical scenarios with multiple tasks. Multi-vehicle driving can be treated as competitive utilization of the spatial-temporal resources of the road, hence game theory can provide an important theoretical and technical tool for multi-vehicle interactive decision-making. This paper provides a review on applying game theory to the decision-making of intelligent driving. We summary and classify the literatures on the interactive decision-making of intelligent driving based on game theory into three commonly used game methods, including the receding horizon games, the differential games, and the Markovian games. At first, the basic knowledge of game theory is introduced, and then the common intelligent driving scenarios are introduced and the key problems of interactive decision-making are summarized. Then, the above three game methods are used to model the multi-vehicle interactive decision-making, and the solution algorithms in literatures are introduced respectively. Finally, the relevant simulation experiments and test methods are summarized. The remaining challenges for the future development of areas are discussed with a personal perspective.