基于手机蓝牙的交通特征参数提取方法研究
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- 英文论文题名：A Method to Collect Traffic Characteristic Parameters Based on Mobile Phones with Bluetooth
- 论文作者：吴志周 ; 谭桂杉
- 英文论文作者：Wu Zhizhou ; Tan Guishan ; Key Laboratory of Road and Traffic Engineering ; Ministry of Education ; Tongji University
- 年：2016
- 作者机构：同济大学道路与交通工程教育部重点实验室;
- 论文关键词：手机蓝牙 ; 交通诱导参数 ; 交通控制参数 ; 聚类分析 ; 高承载车
- 英文论文关键词：Bluetooth ; Traffic Guidance Parameters ; Traffic Control Parameters ; Clustering Analysis ; HOV
- 会议召开时间：2016-11-16
- 会议录名称：第十一届中国智能交通年会大会论文集
- 语种：中文
- 分类号：U491
- 学会代码：ZJTX
- 会议名称：第十一届中国智能交通年会
- 会议地点：中国重庆
- 主办单位：中国智能交通协会
- 学会名称：中国智能交通协会
- 页数：10
- 文件大小：1093k
- 原文格式：D
- 会议级别：全国
摘要
在现有交通参数采集方式的对比研究基础上,提出利用蓝牙检测技术提取交通特征参数的方法。根据蓝牙检测器的数据结构设计了交通诱导参数(路段平均行程时间,平均行程车速,路网OD分布)和交通控制参数(路段机动车、非机动车流量)的提取算法,利用K均值聚类分析对机动车和非机动车进行划分,并判别出高承载车类型(HOV)。实测数据和VISSIM仿真建模的结果表明:模型在交通畅通路段应用效果较好,估计准确;在交通拥堵路段,由于非机动车车速与机动车车速接近,模型估计准确度降低。本文所探究的方法对于补充或替代现有交通参数采集方式具有重要意义。
Based on the contrast study of existed acquisition methods of traffic characteristic parameters,the algorithm models were proposed to collect traffic characteristic parameters by Bluetooth detection sensors.The algorithms were designed in accordance with data structure from the Bluetooth detectors,including traffic guidance parameters(average travel time,average travel speed,OD distribution of traffic network) and traffic control parameters(the traffic flows of automobile and non-motorized vehicle).Then,a K-means clustering analysis was performed to classify cars and bikes as well as HOV(High occupancy vehicle lane).The results of field measurement data and VISSIM simulation show that the modelsare effective and accurate when traffic is smooth;however,the estimation accuracy of models is reduced in heavy traffic,because of the similar speed of motor vehicles and non-motorized vehicles.And the results of this study can be meaningful in terms of supplementing or replacing the present collection methods of traffic characteristic parameters.
Based on the contrast study of existed acquisition methods of traffic characteristic parameters,the algorithm models were proposed to collect traffic characteristic parameters by Bluetooth detection sensors.The algorithms were designed in accordance with data structure from the Bluetooth detectors,including traffic guidance parameters(average travel time,average travel speed,OD distribution of traffic network) and traffic control parameters(the traffic flows of automobile and non-motorized vehicle).Then,a K-means clustering analysis was performed to classify cars and bikes as well as HOV(High occupancy vehicle lane).The results of field measurement data and VISSIM simulation show that the modelsare effective and accurate when traffic is smooth;however,the estimation accuracy of models is reduced in heavy traffic,because of the similar speed of motor vehicles and non-motorized vehicles.And the results of this study can be meaningful in terms of supplementing or replacing the present collection methods of traffic characteristic parameters.
引文
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[2]王雪.基于复杂网络理论的城市路网特性研究[D].西安:长安大学,2014.
[3]熊圣明.基于电感线圈的车辆检测器系统设计[D].重庆:重庆大学,2014.
[4]蔡晓庆.基于磁感应的交通系统辨识关键技术研究[D].广州:华南理工大学,2012.
[5]刘邹.基于DSP的测速雷达数据采集和处理[D].无锡:江南大学,2008.
[6]李戈,孟祥杰,王晓华,王重秋.国内超声波测距研究应用现状[J].测绘科学,2011(4):60-62.
[7]马明祥.基于视频的交通参数检测方法研究[D].济南:山东大学,2006:10622.
[8]王川童.基于视频处理的城市道路交通拥堵判别技术研究[D].重庆:重庆大学,2010.
[9]董均宇.基于GPS浮动车的城市路段平均速度估计技术研究[D].重庆:重庆大学,2006.
[10]Bobba Rohini.Predicting speeds on urban streets using real-time GPS data[J].Masters Abstracts International,2000,41(4):1137.
[11]Faria David Anthony.A framework to transform real-time GPS data derived from transit vehicles to determine speed-flow characterestics of arterials[J].Dissertation Abstracts Internationl,2002,64(12):6215.
[12]Yanying Li,Mcdonald M.Link travel time estimation using single GPS equipped probe vehicle[C].Proc:Intelligent Transportation Systems,2002.
[13]马占刚.基于手机的交通信息采集及处理技术[D].重庆:重庆大学,2009.
[14]关志超,胡斌,张昕,等.基于手机数据的城市交通信息采集技术研究[C].中国智能交通协会,2012.
[15]杨飞,裘炜毅.基于手机定位的实时交通数据采集技术[J].城市交通,2005,3(4).
[16]徐加伟.基于低功耗蓝牙无线通讯技术的交通数据检测方法研究[D].哈尔滨:哈尔滨工业大学,2013.
[17]郑龙,田田,喻晓峰.基于蓝牙技术的城市交通系统[J].计算机工程与设计,2005,26(6).
[18]Sawant,H.Using Bluetooth and sensor networks for intelligent transportation systems.Intelligent Transportation Systems[C].The 7th International IEEE Conference,2004.