为了确保智能驾驶汽车在多车协同下的自动泊车的安全性与稳定性，提出一种协同泊车系统，能在保证协同避障的前提下，实现多车自动泊车；对Hybrid A *算法进行改进，使其在搜索路径的同时考虑车辆的转角约束和车辆之间的碰撞约束，确保运动过程中的安全性与稳定性，并根据是否结合三次样条插值分为泊车系统1和泊车系统2。利用TOPSIS（technique for order preference by similarity to an ideal solution）的方法，选取指标和对应权重，量化不同泊车系统的泊车性能，通过归一化的系统得分对不同泊车系统的优劣进行评价。两车协同泊入工况以及两车协同泊入泊出工况的仿真结果表明，泊车系统2的车辆得分始终高于泊车系统1，在两车同时泊入工况下，其中一车得分提高了0.984，另一车提高了0.420 2。在协同泊入泊出工况下，两车得分均提高了0.420 2。可见泊车系统2表现更佳，有效提升了多车协同泊车的安全性与稳定性。

To ensure the safety and stability of automatic parking for intelligent vehicles in multi-vehicle scenarios, a cooperative parking system was proposed. The system enabled automatic parking of multiple vehicles while ensuring cooperative obstacle avoidance. The Hybrid A * algorithm was improved by incorporating vehicle steering constraints and inter-vehicle collision constraints during path search, enhancing motion safety and stability. The systems were categorised into parking system 1 and parking system 2 based on whether cubic spline interpolation was applied. The technique for order preference by similarity to an ideal solution (TOPSIS) method was used to select evaluation indicators and assign weights, quantifying the parking performance of different systems. Normalised scores were obtained to evaluate system performance. Simulation results under two-vehicle cooperative parking-in and parking-in/out scenarios indicate that parking system 2 consistently achieves higher scores than parking system 1. In the simultaneous parking-in scenario, one vehicle's score increases by 0.984 and the other by 0.420 2. In the parking-in/out scenario, both vehicles' scores increase by 0.420 2. The results demonstrate that parking system 2 performs better, effectively improving the safety and stability of multi-vehicle cooperative parking.