【作者】 王荣杰；

【导师】 赵毅； 何翔；

【作者基本信息】 哈尔滨工业大学 ， 应用数学， 2010， 硕士

【摘要】 有关基于浮动点车辆数据的动态交通实时路况信息的研究在我国刚刚起步,在最近两年里,在我国导航仪市场上相继出现了附有动态路况的导航产品,但一些产品存在路况信息不准确、路况信息不能及时更新及信息覆盖率低等问题。本文主要针对上述问题,基于浮动点交通数据,建立路况分析判断模型,实现动态实时更新及为深圳市车主出行提供动态路况信息服务的应用。本课题研究的目的在于解决传统基于浮动点判断交通路况信息准确性的提高及降低对浮动点数据量要求。实时读取浮动车辆上传的GPS数据,分析车辆所处路段路况信息,再将判断后的路况信息存入数据库,方便查询及路况信息的及时发布。此外,为充分提高单个车辆提供路况信息的利用率,在车载终端安装路况分析仪(Mobile Navigation Assistance,MNA),车辆在路面上一旦发生拥堵,主动上报拥堵信息。从而实现分布式计算,不但减轻了中心系统的计算压力,而且还降低了判断动态交通路况信息对于数据量的要求。最后融合两种判断信息的数据,以网站形式发布路况信息。本文的研究内容主要包括以下几个方面:首先,为克服大规模浮动点数据定位时间长的现象,我们将地图网格化,经纬度数据首先定位网格,再定位网格内的路段,实现了将数据点经纬度定位时间的指数级降低。其次,对大规模浮动点车辆数据的过滤,排序,确定模型计算。再次,通过对单一车辆数据的采集,分析特征,建立判断路况模型,再实际验证模型,通过反复验证修改模型,最后到确定模型,再到模型算法向车台移植,车台与中心实现实时通讯。最后,融合各种路况判断信息,建立优先级标准,将路况信息存入数据库,利用网站实时读取数据库数据,实现动态路况信息的实时发布。本文通过真实路况检测及模拟拥堵状态,验证了两种判断路况模型的正确率及实时性;突破了传统集中式计算,实现了车载终端GPS模块实时探测路况信息的应用。更多还原

【Abstract】 The research about vehicle data based on floating point in real-time traffic information has just started in China in the last two years, navigation products with dynamic real-time traffic information have appeared on the market w in China, but some products with dynamic real-time traffic information is not accurate , and traffic information didn’t timely update and the information on a low coverage. In response to solve the issues above, we build traffic analysis model based on the floating car datas and achieve dynamic real-time traffic information update and provide owners for dynamic real-time traffic information service at Shenzhen.The purpose of this research project is to increase the accuracy of traditional judge road traffic information based on floating-point and reduce the requriements for amount of data. Real-timely read the GPS data uploaded by vehicles, analysis road traffic information , then put the traffic information into a database for convenient inquiries and timely release.In addition, in order to make full use of single vehicle for provide road traffic information, we install traffic analyzer (Mobile Navigation Assistance, MNA) in vehiche terminal, once there is a event of congestion, congestion information was reported initiativly so achieved distributed computing. There is not only reduce the center system compute pressure, but also reduces the amount of data requirements ,the data which for judge road traffic information. In finally integration of two kinds of information and release it in Web site form. This paper mainly include the following aspects:Firstly, in order to overcome the phenomenon that the large-scale floating point data spent a lot of time to local position, we divide the map into grid. First,local longitude and latitude data into grid, then locate the road section within the grid, so reduce the local time for latitude and longitude at exponential level.Secondly, large-scale floating-point vehicle data filter, sort and determine the model calculations.Once again, by a single vehicle data collection, analysis features, the establishment of traffic models to determine the road traffic conditon, and then the actual verification model changes through repeated verification model, and finally to determine the model, then model algorithm transplanted to vehicle, realize vehicle platform real-time communication with the central.Finally, integration variety of traffic information and establish the priority standards, put traffic information into the database, using the Web site to read real-time database data, realiz dynamic traffic information broadcast in real time.In this paper, the real state of traffic congestion detection and simulation to verify the two kinds of traffic models to determine the correct rate and real-time; break the traditional centralized computing, achieve applicaton for vehicle terminal real-time detection traffic information with GPS module.更多还原