详情

原文传递 DETERMINING AGGREGATION LEVEL FOR ITS DATA VIA WAVELET TRANSFORMATION.

题名：	DETERMINING AGGREGATION LEVEL FOR ITS DATA VIA WAVELET TRANSFORMATION.
作者：	Qiao-Fengziang; Wang-Xin; Yu-Lei
关键词：	Data-processing; Databases-; Planning-; Real-time-information; Traffic-flow
摘要：	In addition to the intended use of Intelligent Transportation System (ITS) data for traffic operational purposes, it is possible and desirable to use these data for various transportation planning purposes. The nature and sheer amount of data requires careful and judicious processing to appropriate aggregation levels and sampling frames to make the real-time traffic data more meaningful to transportation planners. Some pioneer approaches determine the aggregation levels empirically by testing whether the difference between the aggregated series and the original series is statistically significant. However, there is a risk that the measuring errors are also included, and further more, no one knows that what kinds of information have been omitted and what remain. In this research, the original real time ITS data, were first decomposed via the wavelet transformation. Then the measuring noises as well as the various useful signal components were identified. The next step goes to find out what the physical meaning for each of the retained components in the decomposed series is. The well-designed sampling frequency can serve as the proper aggregation level that is able to capture the required frequency component and eliminate other unnecessary ones. Different transportation planning purposes need different frequency components from the original ITS data series, so the wavelet transformation approach can help us determine what's the proper value of the aggregation level for a particular planning purpose.
总页数：	ITS America. Meeting (12th : 2002 : Long Beach, Calif.). Securing our future : ITS America 12th Annual Meeting and Exposition 2002 : conference proceedings. 2002. pp18
报告类型：	科技报告