摘要
为了提高实时的ITS数据对交通规划的实用性,需要对原始的ITS数据进行合理的集成,以满足不同类型用户的需求。首先对运用统计分析和小波变换两种方法进行ITS数据集成的原理做了分析和评述,然后重点建立了基于小波变换理论的ITS数据集成方法,该方法将一段时间内的ITS数据视为随时间变化的随机信号,利用小波变换将ITS数据分解为低频成分和高频成分来进一步处理,最后应用MATLAB软件结合实际数据进行了编程实现,并给出了不同分解层次下的建议集成度。
In order to make the real-time ITS data more significant to transportation planners, ITS datas require careful and reasonable processing to appropriate aggregation levels. Conventional aggregation techniques can not eliminate the unnecessary noise and are unable to tell out what information is attracted and remained. In this research, the real-time ITS datas are decomposed by the wavelet transformation. The measuring noise as well as the various useful signal components is then identified. The proper aggregation level,which is able to capture the required component and eliminate other unnecessary ones, is conducted from the well-designed sampling frequency. As a result of this research, computer software compiled in MATLAB is developed which can provide the aggregation level and aggregated data series for different traffic planning purposes.
出处
《中国公路学报》
EI
CAS
CSCD
北大核心
2004年第3期82-86,共5页
China Journal of Highway and Transport
基金
国家"十五"科技攻关项目(2002BA404A)
关键词
交通工程
数据集成
小波变换法
智能交通
traffic engineering
data aggregation
method of wavelet transform
ITS
