首页|基于时间聚类推理的立体车库车位分配策略研究

基于时间聚类推理的立体车库车位分配策略研究

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
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有效缩短顾客等待时间，表现为顾客等待时间减少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。
Research on parking allocation strategy of stereo garage based on time cluster reasoning
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 and the length of stay time,a mathematical model of parking space partition allocation in stereo garage is established. With defining the average customer waiting time as stereo garage efficiency evaluation index,the efficiency index simulations of the nearby allocation and the proposed partition clustering reasoning allocation were carried out. The simulation results show that the proposed allocation strategy,compared with nearby allocation strategy,can effectively shorten the customer waiting time,and 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.

traffic engineeringstereo garagek-means clusteringparking space allocationcustomer waiting timearrival-departure time

马尚鹏、李建国、杨波

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兰州交通大学自动化与电气工程学院 兰州730070

兰州交通大学四电BIM工程与智能应用铁路行业重点实验室 兰州730070

交通工程 立体车库 k-means聚类 车位分配 顾客等待时间 到达-离去时间

中国高校产学研创新基金甘肃省自然科学基金甘肃省教育厅优秀研究生"创新之星"四电BIM工程与智能应用铁路行业重点实验室开放基金

2021LDA0700220JR5RA3962022CXZX-620BIMKF-2021-06

2024

10.11835/j.issn.1000.582X.2024.08.005

重庆大学学报
重庆大学

重庆大学学报

CSTPCD北大核心
影响因子：0.601
ISSN：1000-582X
年,卷(期)：2024.47(8)