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作 者:刘云翔 陈斌 林涛 施伟 LIU Yunxiang;CHEN Bin;LIN Tao;SHI Wei(School of Computer Science and Information Engineering,Shanghai Institute of Technology,Shanghai 201400,China;School of Automobile Engineering,Jiangsu Automobile Technician Institute,Yangzhou 225000,China)
机构地区:[1]上海应用技术大学计算机科学与信息工程学院,上海201400 [2]江苏汽车技师学院汽车工程学院,江苏扬州225000
出 处:《现代电子技术》2019年第21期134-140,共7页Modern Electronics Technique
基 金:国家自然科学基金项目(61702334);上海市自然科学基金项目(17ZR1429700)~~
摘 要:为了降低HOV车道检测所需的建设成本和设备维护费用,进一步扩大监管区域,提出以优化ST-DBSCAN算法建立手机及车辆定位分析模型,能在一定程度上有效判断出在HOV车道上运行车辆的实际乘客数,为执行HOV车道中车辆实时监测提供一种新的辅助检测手段。通过采集道路上运行车辆及移动智能手机GPS和基站定位数据,运用优化的ST-DBSCAN聚类算法进行分类建立定位分析模型,计算出各个簇的关键对象度量值,根据HOV车道实际规定车载人数作为其最小支持度,满足最小支持度的数据集就是最后挖掘建立模型的依据。实验结果表明,该模型在HOV车道上的应用能有效辅助检测HOV车道车辆并有较高的检测准确率。In order to reduce the cost of construction and equipment maintenance required for HOV lane detection and further expand the regulatory area,a model of mobile phone and vehicle positioning analysis is proposed by optimizing the ST-DBSCAN algorithm,with which the quantity of actual passengers in vehicles running on the HOV lane can be effectively judged to a certain extent,and a new auxiliary detection method is provided for the implementation of real-time monitoring of vehicles in the HOV lane.The optimized ST-DBSCAN clustering algorithm is used to achieve classification establishment of positioning analysis models classify and by collecting GPS and base station positioning data of mobile smart phones and vehicles running on the road,and figure out the key object metrical values of each cluster.The HOV lane regulation about the actual number of persons on the vehicle is taken as the minimum support to meet the data sets with minimum support for the final mining and model building.The experiment result indicates that the model used in the HOV lane can effectively assist the detection of vehicles on HOV lane and has high detection accuracy.
关 键 词:定位分析模型 ST-DBSCAN聚类算法 HOV车道 GPS定位 基站定位 结果分析
分 类 号:TN929.5[电子电信—通信与信息系统] 34[电子电信—信息与通信工程]
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