This study proposes an electric vertical takeoff and landing aircraft (eVTOL)–ground vehicle dynamic coordination optimization algorithm based on model predictive control (MPC). A multiobjective trajectory planning function is constructed, an MPC algorithm with obstacle avoidance constraints is designed, and its computational efficiency is optimized. Using the CarSim and Simulink joint simulation platform, experiments are conducted in scenarios such as urban road intersection coordination and complex obstacle distribution. The results show that the algorithm reduces the average trajectory tracking error of eVTOL and ground vehicles to 0.11 m and 0.13 m, respectively, which is about 38% higher than the traditional algorithm; the obstacle avoidance success rate reaches 98.2%, an increase of 25%; the average calculation time of a single control cycle is only 142 ms, which meets the real-time requirements. Experiments show that the algorithm can effectively realize the precise trajectory tracking of multiple vehicles and ensure the safety and efficiency of collaborative operation in complex environments.