基于大数据的VANET拥塞检测研究  

Research on congestion detection in VANET based on big data

作　　者：李佩君 侯大有 赵正平 肖卓磊 史晓凤 刘淑影 LI Peijun;HOU Dayou;ZHAO Zhengping;XIAO Zhuolei;SHI Xiaofeng;LIU Shuying(School of Computer and Information Engineering,Fuyang Normal University,Fuyang,Anhui 236037,China)

机构地区：[1]阜阳师范大学计算机与信息工程学院,安徽阜阳236037

出　　处：《阜阳师范大学学报（自然科学版）》2020年第2期72-76,共5页Journal of Fuyang Normal University:Natural Science

基　　金：阜阳师范学院科学研究项目(2019FSKJ09);阜阳师范大学质量工程项目(2019JYXM11);阜阳师范大学-阜阳市政府合作横向课题重大项目(XDHX201702)资助。

摘　　要：道路交通的拥塞问题是城市中长期存在且急需解决的问题.而车联网(vehicular Ad hoc networks,VANET)的出现为智能管理交通,事故隐患预警和舒适的乘车环境提供了技术支持.为了保证道路的畅通和交通的流动性,可通过VANET网络传播有关交通状况的有用信息.论文提出了一种基于大数据工具的车辆对车辆通信方式的城市道路状况检测方法,为驾驶员提前换道提供了有力证据,从而降低车辆拥塞概率.In urban areas,congestion in road has been a very persistent problem which requires solutions.The emergence of VANETs(Vehicular Ad hoc Networks)provides technical support for intelligent management of traffic,early warning of accidents and a comfortable ride environment.In order to ensure the smooth flow of roads and the mobility of traffic,useful information about traffic conditions can be disseminated through the VANET network.An approach to detect the state of road traffic in urban areas based on the vehicle-to-vehicular communication method and big data tools is proposed in this paper,which provides strong evidence for drivers to change lanes in advance,thereby reducing vehicle congestion probability.

关 键 词：VANETS 大数据 拥塞检测 道路状况 

分 类 号：TN929.5[电子电信—通信与信息系统]