Overlooking the dynamic nature of vehicle paths and the suddenness of vehicular network services, traditional popularity-based caching strategies tend to concentrate data on specific base stations (BSs), leading to imbalanced cache distribution. To address this problem, a balanced caching mechanism for heterogeneous vehicular networks based on multi-tier-leadership Stackelberg games is proposed. In the game process, based on hierarchical relationship of network architecture, BSs act as leaders, road side units (RSUs) as access points subordinate to the BS as sub-leaders, and vehicles as followers. By integrating the utility functions of leaders, sub-leaders, and followers in multi-tier-leadership Stackelberg games framework to derive optimal pricing and caching strategies. Simulation results demonstrate that the total system profit converges after approximately 200 iterations. Additionally, this mechanism improves cache stability by 16.2% and reduces transmission delay by 38% compared to the DQN algorithm.