查询结果:   劳超勇,胡华,刘志钢.基于Wi-Fi探针的地铁车站拥堵点客流量估计方法[J].计算机应用与软件,2019,36(2):52 - 56,167.
中文标题
基于Wi-Fi探针的地铁车站拥堵点客流量估计方法
发表栏目
应用技术与研究
摘要点击数
314
英文标题
PASSENGER FLOW ESTIMATION AT CONGESTION POINT OF METRO STATION BASED ON WI-FI PROBE
作 者
劳超勇 胡华 刘志钢 Lao Chaoyong Hu Hua Liu Zhigang
作者单位
上海工程技术大学城市轨道交通学院 上海 201600     
英文单位
School of Urban Rail Transit, Shanghai University of Engineering Science, Shanghai 201600, China     
关键词
客流量估计 Wi-Fi探针 Apriori算法 BP神经网络
Keywords
Passenger flow estimation Wi-Fi probe Apriori algorithm BP neural network
基金项目
国家自然科学基金项目(71601110);国家科技支撑计划项目子课题(2015BAG19B02-28)
作者资料
劳超勇,硕士生,主研领域:城市轨道交通大客流。胡华,副教授。刘志钢,教授。 。
文章摘要
实现地铁站拥堵位置客流流量的实时监控是提升车站运营管理的关键,也一直是运营安全的难点。Wi-Fi探针对携带Wi-Fi设备的对象进行动态跟踪,实现客流流量的精确化采集。在对Wi-Fi探针的数据采集原理、数据预处理及关联性分析的基础上,通过实测数据建立BP神经网络客流量估计模型,并以上海地铁徐泾东站为例实现模型和算法的验证。结果表明,该技术满足客流流量采集分析的要求,且证明了客流量动态估计方法的可行性和有效性。
Abstract
Real-time monitoring of passenger flow in congested locations of subway stations is the key to improving the operation and management of stations, and it has always been a problem in operational safety. The Wi-Fi probe dynamically tracked the objects carrying the Wi-Fi device to achieve accurate collection of passenger flow. Based on the data acquisition principle, data preprocessing and correlation analysis of Wi-Fi probe, the BP neural network traffic flow estimation model was established by the measured data. The verification of model and algorithm were carried out by taking Shanghai Xujingdong Station as an example. The results show that the Wi-Fi probe passenger flow acquisition technology meets the requirements of passenger flow collection and analysis. It also proves the feasibility and effectiveness of the passenger flow dynamic estimation.
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