[1]贺云鹏,李建国.平面移动式立体车库客流状态聚类研究[J].深圳大学学报理工版,2020,37(3):314-322.[doi:10.3724/SP.J.1249.2020.03314]
　HE Yunpeng and LI Jianguo.Passenger flow state clustering in flat mobile automated garage[J].Journal of Shenzhen University Science and Engineering,2020,37(3):314-322.[doi:10.3724/SP.J.1249.2020.03314]
点击复制

平面移动式立体车库客流状态聚类研究()
分享到：

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第37卷
期数:
2020年第3期
页码:
314-322
栏目:
交通物流
出版日期:
2020-05-20

文章信息/Info

Title:
Passenger flow state clustering in flat mobile automated garage
文章编号:
202003015
作者:
贺云鹏; 李建国
兰州交通大学自动化与电气工程学院，甘肃兰州 730070
Author(s):
HE Yunpeng and LI Jianguo
School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, Gansu Province, P.R.China
关键词:
交通运输工程; 立体车库; 客流状态; 模糊聚类算法; 顾客到达; 服务时间
Keywords:
transport engineering;  automated garage;  passenger flow state;  fuzzy c-means (FCM) algorithm;  passenger arrival;  service time
分类号:
U491.7
DOI:
10.3724/SP.J.1249.2020.03314
文献标志码:
A
摘要:
对平面移动式立体车库客流状态进行聚类有助于获知车库客流信息，指导存取车设备调度优化，提高立体车库的运行效率．提出一种平面移动式立体车库客流状态聚类方法，建立立体车库设备运行时间模型，模拟运行得到不同顾客到达率下的运行参数，对客流模式进行划分并作为初始聚类输入条件，在此基础上使用模糊c均值算法完成对车库客流数据的聚类．以中国西安市某立体车库为研究对象，对其上位机数据库的顾客到达数据进行分析与聚类，定义内部评价指标和相对评价指标，并与其他聚类算法进行对比．实验结果表明，模糊c均值聚类算法实现了立体车库客流状态聚类，且聚类结果可靠、合理地反映出立体车库客流实际情况．
Abstract:
Clustering the flat mobile automated garage passenger flow state can help to obtain the passenger flow information, guide the scheduling optimization and improve the operating efficiency. This paper proposes a method to cluster the passenger flow in flat mobile automated garage. Firstly, we establish the travel time model for the automated garage. After getting simulated operational indicator under different arrival rates, we obtain the passenger flow pattern divisions as clustering input criteria, and use the fuzzy c-means (FCM) algorithm to cluster the garage passenger flow data. Finally, we take an automated garage in Xian, China as an example, and obtain the customer arrival data from its upper computer database, define the external evaluation index and relative evaluation index to compare with other clustering algorithms. The experimental results show that the fuzzy c-means clustering algorithm realizes the passenger flow status clustering of stereo garage, and the clustering results reflect the actual passenger flow situation reliably and reasonably.

参考文献/References:

［1］ 付翠玉, 关景泰. 立体车库发展的现状与挑战［J］. 机械设计与制造, 2005(9): 156-157.
FU Cuiyu, GUAN Jingtai. Status and challenge of the development of solid garage［J］. Machinery Design & Manufacture, 2005(9): 156-157.(in Chinese)
［2］ 冉江宇, 过秀成, 陈永茂, 等. 基于聚类非参数检验的动态停车需求分布特征［J］. 东南大学学报自然科学版, 2011, 41(4): 871-876.
RAN Jiangyu, GUO Xiucheng, CHEN Yongmao, et al. Dynamic parking demand distribution character based on clustering non-parameter tests［J］. Journal of Southeast University Natural Science Edition, 2011, 41(4): 871-876.(in Chinese)
［3］ 华文瀚, 田怀文. 堆垛式立体车库存取车策略及路径优化问题的分析研究［J］. 机械设计与制造, 2011(3):260-262.
HUA Wenhan, TIAN Huaiwen. Research on storage-retrieval operation strategy and optimization of automatic stereoscopic garage［J］. Machinery Design & Manufacture, 2011(3): 260-262.(in Chinese)
［4］ 刘美菊, 彭堰艳, 龚志恒, 等. 基于随机森林的群控立体车库运行模式识别研究［J］. 电子器件, 2014, 37(3): 514-518.
LIU Meiju, PENG Yanyan, GONG Zhiheng, et al. Stereoscopic garage group control traffic pattern recognition based on random forests［J］. Chinese Journal of Electron Devices, 2014, 37(3): 514-518.(in Chinese)
［5］ CHERIAN J, LUO Jun, GUO Hongliang, et al. Park gauge: gauging the congestion level of parking garages with crowd sensed parking characteristics［C］// Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. Seoul, South Korea: ACM, 2015: 395-396.
［6］ 陆化普, 李瑞敏. 城市智能交通系统的发展现状与趋势［J］. 工程研究——跨学科视野中的工程, 2014, 6(1): 6-19.
LU Huapu, LI Ruimin. Developing trend of ITS and strategy suggestions［J］. Journal of Engineering Studies, 2014, 6(1): 6-19.(in Chinese)
［7］ 范鲁明, 贺国光. 改进非参数回归在交通流量预测中的应用［J］. 重庆交通大学学报自然科学版, 2008, 27(1): 96-99.
FAN Luming, HE Guoguang. Application improvement of nonparametric regression to traffic flow forecast［J］. Journal of Chongqing Jiaotong University Natural Science, 2008, 27(1): 96-99.(in Chinese)
［8］ ELENI V, KONSTANTINOS1 K, VASSILEIOS T, et al. A real-time parking prediction system for smart cities［J］. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 2016, 20(2): 192-204.
［9］ JB/T 8713-1998. 机械式停车设备类别，型式与基本参数［S］.
JB/T 8713-1998. Mechanical parking systems-classification, models and basic parameters［S］.(in Chinese)
［10］ 张琳琳, 李雪玮, 李振龙, 等. 基于两阶段K-means聚类的道路运行状况评价方法［J］. 交通信息与安全, 2017, 35(5): 99-105.
ZHANG Linlin, LI Xuewei, LI Zhenlong, et al. An evaluation method of road operation condition based on two-stage K-means clustering［J］. Journal of Transport Information and Safety, 2017, 35(5): 99-105.(in Chinese)
［11］ 张亮亮, 贾元华, 牛忠海, 等. 交通状态划分的参数权重聚类方法研究［J］. 交通运输系统工程与信息, 2014, 14(6): 147-151.
ZHANG Liangliang, JIA Yuanhua, NIU Zhonghai, et al. Traffic state classification based on parameter weighting and clustering method［J］. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(6): 147-151.(in Chinese)
［12］ 陈忠辉, 凌献尧, 冯心欣, 等. 基于模糊C均值聚类和随机森林的短时交通状态预测方法［J］. 电子与信息学报, 2018, 40(8): 1879-1886.
CHEN Zhonghui, LING Xianyao, FENG Xinxin, et al. Short-term traffic state prediction approach based on FCM and random forest［J］. Journal of Electronics & Information Technology, 2018, 40(8): 1879-1886.(in Chinese)
［13］ 陈钊正, 吴聪. 多变量聚类分析的高速公路交通流状态实时评估［J］. 交通运输系统工程与信息, 2018, 18(3): 225-233.
CHEN Zhaozheng, WU Cong. A method of traffic state estimation for expressway based on multivariate clustering analysis［J］. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(3): 225-233.(in Chinese)
［14］ 李晓璐, 于昕明, 杜崇, 等. 基于权值优化的FCM-MSVM算法及其在高速公路状态判别中的应用［J］. 北京交通大学学报, 2018, 42(4): 72-78, 84.
LI Xiaolu, YU Xinming, DU Chong, et al. FCM-MSVM algorithm based on weight optimization and its application in state identification of freeway［J］. Journal of Beijing Jiaotong University, 2018, 42(4): 72-78, 84.(in Chinese)
［15］ JULIA H, KNOWLES J, KELL D B. Computational cluster validation in post-genomic data analysis［J］. Bioinformatics, 2005, 21(15): 3201-3212.
［16］ PORTILLA A I, OREA B A, BERODIA J L M, et al. Using M/M/∞ queueing model in on-street parking maneuvers［J］. Journal of Transportation Engineering, 2009, 135(8): 527-535.

相似文献/References:

[1]李伟,罗钦.基于逐步优化的轨道交通网络行车计划衔接[J].深圳大学学报理工版,2018,35(6):629.[doi:10.3724/SP.J.1249.2018.06629]
　LI Wei and LUO Qin.Rail transit network planning based on gradual optimization[J].Journal of Shenzhen University Science and Engineering,2018,35(3):629.[doi:10.3724/SP.J.1249.2018.06629]
[2]于泉,刘洋,郭骁伟.基于路口相关性的交通流量修复研究[J].深圳大学学报理工版,2019,36(3):304.[doi:10.3724/SP.J.1249.2019.03304]
　YU Quan,LIU Yang,and GUO Xiaowei.Restoration of traffic flow data based on intersection correlation[J].Journal of Shenzhen University Science and Engineering,2019,36(3):304.[doi:10.3724/SP.J.1249.2019.03304]

备注/Memo

备注/Memo:
Received：2019-07-01；Accepted：2019-10-26
Foundation：Construction Science and Technology Research Project of Gansu Province (JK2016-10)
Corresponding author：Associate professor LI Jianguo．E-mail: 394504676@qq.com
Citation：HE Yunpeng，LI Jianguo．Passenger flow state clustering in flat mobile automated garage ［J］. Journal of Shenzhen University Science and Engineering, 2020, 37(3): 314-322.（in Chinese）
基金项目：甘肃省建设厅资助项目(JK2016-10)
作者简介：贺云鹏(1994—)，兰州交通大学硕士研究生．研究方向：交通信息工程及控制．E-mail：interhyp@126.com
引文：贺云鹏，李建国．平面移动式立体车库客流状态聚类研究［J］. 深圳大学学报理工版，2020，37(3)：314-322.
更新日期/Last Update: 2020-05-30