交通运输系统工程与信息 ›› 2007, Vol. 7 ›› Issue (3): 100-104 .

• 系统工程理论与方法 • 上一篇    下一篇

浮动车采样周期优化方法研究

张存保 1,2 ,杨晓光2 ,严新平1   

  1. 1 武汉理工大学 智能交通系统研究中心,武汉 430063
    2 同济大学 交通运输工程学院,上海 200092
  • 收稿日期:2006-11-30 修回日期:1900-01-01 出版日期:2007-06-25 发布日期:2007-06-25

Method for Floating Cars Sampling Cycle Optimization

ZHANG Cun-bao1,2 YANG Xiao-guang2 YAN Xin-ping1   

  1. 1 ITS Center, Wuhan University of Technology, Wuhan 430063
    2 School of Traffic and Transportation, Tongji University, Shanghai 200092
  • Received:2006-11-30 Revised:1900-01-01 Online:2007-06-25 Published:2007-06-25

摘要: 利用安装GPS设备的浮动车采集动态交通信息,具有数据精度高、覆盖范围广、实时性强等优点。阐述了基于浮动车的交通信息采集系统的原理和组成,针对目前浮动车采样周期主要凭主观经验确定的问题,提出了采样周期优化的理论方法:将浮动车瞬时速度当作随机信号,利用傅立叶变换对其进行频域分析,然后依据Shannon采样定理,确定浮动车的优化采样频率。结果表明:本文方法确定的采样周期可以获得较高的数据采集精度,满足实用要求。

关键词: 交通信息采集, 浮动车, 采样周期, 频谱分析, 智能交通系统

Abstract: Floating-car system has become a new way to collect real-time traffic data, which has many advantages such as high precision, large coverage area, etc. This paper describes composing of floating-car system, presents a theoretical method for floating-car sampling cycle optimization: regards speed as a stochastic signal, analyzes its frequency spectrum using Fourier transform, and decides the optimal sampling frequency by Shannon sampling theory. The result shows that the optimal sampling frequency can acquire high data precision, which is suitable for practical application.

Key words: traffic data collection, floating cars, sampling cycle, frequency spectrum, ITS

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