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Systematic Traffic Peak Period Identification Using Bottom-Up Segmentation and Wavelet Transformation

机译:使用自底向上分段和小波变换的系统交通高峰期识别

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This paper develops a framework to test Bottom-up segmentation andWavelet transform capability to distinguish on-peak from off-peak periods given the time series of the travel time. The proposed techniques are tested on the times series of travel time obtained from 15 working days of Bluetooth data on Brisbane’s busiest urban corridor. This study shows that the peak period can be systematically determined from either Bottom-up segmentation or WT on the time series of travel times. The Bottom-up segmentation technique estimated a mean peak period over the 15 working days of 106 min, compared to 99 min with Wavelet transformation. Further investigation is warranted should a recommendation be made as to which technique can more reliably estimate peak period.
机译:本文开发了一个框架,用于测试自下而上的分段和小波变换功能,以在给定旅行时间序列的情况下区分高峰时段和非高峰时段。在布里斯班最繁忙的城市走廊上,从蓝牙数据的15个工作日中获得的旅行时间序列按时间序列进行了测试。这项研究表明,可以根据行进时间的时间序列从下至上分段或WT来系统地确定高峰时段。自下而上的分割技术估计了15个工作日内的平均高峰期为106分钟,而小波变换则为99分钟。如果对哪种技术可以更可靠地估计高峰期提出建议,则有必要进行进一步研究。

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