摘要
智能交通系统的关键技术环节之一是能够准确地获取实时交通参数,包括交通流量、车速、车道占有率等,无线传感器网络在智能交通方面有潜在的广泛应用前景.设计实现了面向交通信息采集的无线传感器网络节点,提出了一系列相关交通信息采集专用算法,包括基于数字滤波和匹配滤波的交通流量监测算法、车速测量算法和车辆识别算法,在道路上进行了实测验证并对节点功耗进行了分析.实测结果表明,交通信息采集节点能以较高精度得到交通流量、车速、车道占有率等信息,并能较准确地对机动车和自行车进行识别.
With the rapid development of modern cities and fast increasing amount of vehicles, ITS has become crucial nowadays. Many elements of ITS are based on the real-time road condition represented mainly by the traffic volume, velocity and lane occupancy. Traditional traffic information detection systems can＇t meet the requirements of deployment convenience, detection accuracy and overall cost. WSN technology has potential wide prospect of applications. In this paper, the network architecture of a WSN- based wireless traffic information detection system, the hardware design of the detection nodes, and a series of detection algorithms are presented. Two kinds of algorithms are developed for traffic volume detection, which are a digital filter based algorithm （DiFiA） and a matched filter based algorithm （MaFiA） respectively. Two nodes for velocity detection are adopted and a velocity detection algorithm, namely VeDA is proposed. An efficient vehicle/non-vehicle classification algorithm is also designed to improve the accuracy of traffic volume, which is called ReSDiRA. And a lightweight synchronization method between two nodes is described for both velocity detection and vehicle/non-vehicle classification. On-road experiments are carried out to test and verify the accuracy and efficiency of the proposed methods, and the power consumption of the node is analytically evaluated. Experimental results indicate potential promises that the developed sensor node may be used in real-time traffic information detection as a new technique.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2008年第1期110-118,共9页
Journal of Computer Research and Development
基金
国家自然科学基金面上项目(60572060)
国家“八六三”高技术研究发展计划基金项目(2006AA01Z215)
国家“九七三”重点基础研究发展规划基金项目(2006CB303000)~~
关键词
无线传感器网络
交通信息采集
匹配滤波
时间同步
车辆识别
wireless sensor networks
traffic information detection
matched filter
time synchronization
vehicle classification
