基于大数据分析的青岛地铁客流画像分析*
罗情平1左旭涛1张蓓蓓1杜可亮2
Research on Passenger Flow Portrait Analysis of Qingdao Metro Based on Big Data Analysis
LUO QingpingZUO XutaoZHANG BeibeiDU Keliang
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作者信息:1.青岛地铁集团有限公司，266045,青岛；
2.北京北大千方科技有限公司，100193,北京
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Affiliation:Qingdao Metro Group Co., Ltd., 266045, Qingdao, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2020.10.028
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中图分类号/CLCN:U293.1+3;F530.7
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栏目/Col:研究报告
摘要:
青岛地铁线网运营管理与指挥中心采用大数据分析方法实现了城市轨道交通客流分析及画像功能。采用AFC(自动售检票)数据结合ATS(列车自动监控)信息的方法实现更精确的出行路径匹配，克服了传统客流分析算法的准确性缺陷。从客流角度实现了乘客、车站、列车、区间画像功能，结合ISCS(综合监控系统)数据实现电扶梯画像功能，为更精确的客流预测及设备维修维护提供了数据支撑。
Abstracts:
Qingdao MMCC (metro management and control center) uses the big data analysis method to realize passenger flow analysis and portrait function for urban rail transit. By combining AFC (automatic fare collection) data with ATS (automatic train supervisory) data, Qingdao MMCC has achieved more accurate travel path matching, which overcomes the accuracy defects of traditional passenger flow analysis algorithm. From the perspective of passenger flow, MMCC realizes the portrait functions of passenger, station, train and section, as well as the function of escalator portrait combined with ISCS system data to provide a data support for more accurate passenger flow prediction and equipment maintenance.
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