摘要
发掘并掌握站内乘客群体的聚集时空变化规律,对于优化城市轨道交通线网间车辆的调度,特别是优化灾害条件下的客流组织管理等,具有积极的作用.针对具有密度分布非均匀特征的车站乘客位置数据集,提出一种基于高斯混合模型的DBSCAN聚类算法.首先,利用高斯混合模型对数据集进行密度的分层处理;然后,面向不同密度层次的数据集进行局部聚类,确定各密度层数据集的参数,并选取恰当的种子以完成局部聚类簇扩展;最后,将各密度层次数据集的聚类结果进行合并.通过标准和实测数据的计算结果表明,基于高斯混合模型优化后的DBSCAN算法,对于非均匀密度分布的乘客位置分布数据具有更好的聚类效果.
Exploring and grasping the temporal and spatial variation rules of passenger group’s aggregation in the station has a positive effect on optimizing the scheduling of vehicles in the urban rail transit network, especially optimizing the organization and management of passengers under disaster conditions. In this paper, a density based spatial clustering of applications with noise(DBSCAN) clustering algorithm based on the Gaussian mixture model is proposed for the station passenger location data set with non uniform density distribution. Firstly, the Gaussian mixture model is used to process the density of data sets. Then, local clustering is performed on data sets with different density levels to determine the parameters of each density layer data set. The appropriate seeds are selected to expand the local cluster cluster. Finally, the clustering results of each density hierarchical data set are merged. Through the calculation of the standard and measured data, it is illustrated that the DBSCAN algorithm based on the Gaussian mixture model has better clustering effect for the passenger location distribution data with non-uniform density distribution.
作者
李晓璐
于昕明
郗艳红
杨晨光
张溪
张彭
朱广宇
LI Xiao-lu;YU Xin-ming;XI Yan-hong;YANG Chen-guang;ZHANG Xi;ZHANG Peng;ZHU Guang-yu(MOE Key Laboratory for Transportation Complex Systems Theory and Technology,Beijing Jiaotong University,Beijing 100044,China;School of Civil Engineering and Architecture,Beijing Jiaotong University,Beijing 100044,China;Beijing Key Laboratory of Urban Traffic Operation Simulation and Decision Support,Beijing Transport Institute,Beijing 100073,China)
出处
《控制与决策》
EI
CSCD
北大核心
2019年第1期18-24,共7页
Control and Decision
基金
科技部国家重点研发计划项目(2016YFC0802206-2
2016YFB1200203-02)
国家自然科学基金项目(61872037
61572069
61503022
71501011)
中央高校基本科研业务费专项基金项目(2017YJS308
2017JBM301
2017JBM095)
北京市科技计划项目(Z171100004417024)
深圳市交通公用设施建设项目(BYTD-KT-002-2)
关键词
城市轨道交通
乘客聚集特征
非均匀分布
高斯混合模型
密度分层
聚类算法
urban rail transit
passenger aggregation characteristics
non-uniform distribution
Gaussian mixture model
density layering
clustering algorithm
作者简介
李晓璐(1992-), 女, 博士生, 从事群体行为模式挖掘的研究;通讯作者:朱广宇(1972-), 男, 教授,博士生导师, 从事智能交通系统数据仿真与分析等研究.E-mail: gyzhu@bjtu.edu.cn.
