采用立体车库车辆到达-离去时间数据，通过k-means聚类方法依据不同时段存取车到达频率对车辆进行类别划分，以立方聚类标准为评价指标对划分可信度进行评估。以车辆到达-离去时间划分推理结果及I/O至待存取车位的设备总服务时间与停留时间长短的关系建立立体车库车位分区分配数学模型。定义顾客平均等待时间为立体车库效率评价指标，仿真对比分析就近分配与本文设计聚类推理分区分配的效率指标。仿真结果表明：本文设计的分配策略相较于就近分配策略能够有效缩短顾客等待时间，表现为顾客等待时间减小9.5%。研究结果为此类车库车位分配过程提供参考，为提高车库运行效率提供决策支持。

Based on the arrival-departure time data of vehicles in stereo garage, k-means clustering method was used to classify vehicles according to the arrival frequency of access vehicles in different periods, and Cubic Cluster Criterion was used as the evaluation index to evaluate the classification credibility. Based on the reasoning results of vehicle arrival-departure time division and the relationship between the total service time of equipment from I/O to the parking space to be accessed and the length of stay time, a mathematical model of parking space partition allocation in stereo garage is established. Define the average customer waiting time for stereo garage efficiency evaluation index, the simulation analysis to the nearby allocation and designed in this paper based on arrival-departure time partition clustering reasoning efficiency index, the simulation results show that: In this paper, design partition strategy compared with nearby allocation strategy can effectively shorten the customer waiting time, show the customer waiting time reduced by 9.5%. The results provide reference for the parking space allocation process of such garages and provide decision support for improving the operation efficiency of garages.

中国高校产学研创新基金资助课题(2021LDA07002) 甘肃省自然科学基金(20JR5RA396) 甘肃省教育厅：优秀研究生“创新之星”项目(2022CXZX-620) 四电BIM工程与智能应用铁路行业重点实验室开放基金课题(BIMKF-2021-06)