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Mean travel speed estimation using GPS data without ID number on inner city road

机译:在市区道路上使用不带ID号的GPS数据估算平均行驶速度

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Due to the expansive use of GPS, GPS data can be used to provide valuable travel time and the travel speed data for the traffic information system. However, to access ID number for personal car would have problems with privacy. Thus, mean travel speed (MTS), which requires individual vehicle tracking, cannot be calculated directly. In this research, we try to estimate the MTS of the road by using GPS data without ID number. The estimation is done by considering the relationship between MTS and time mean speed (TMS), and experiment with relation between MTS and estimated space mean speed (eSMS). In addition, vehicle speed has high variance on inner city roads. Therefore, we proposed grouping method of spot speed data on the road segment, which is called segmentation, to reduce the traffic variance and analyze the collected data for MTS estimation. The results show the correlation between TMS and MTS is 0.94 and the relationship graphs between TMS and MTS have a linear trend line. Hence, TMS and MTS are very correlative. In summary, MTS estimation can be improved and developed into the model or equation if TMS is calculated under short segment (50 m), low traffic variance data, and under suitable time period (5 minutes).
机译:由于GPS的广泛使用,GPS数据可用于为交通信息系统提供有价值的行驶时间和行驶速度数据。但是,访问个人汽车的ID号会遇到隐私问题。因此,无法直接计算需要单独跟踪车辆的平均行驶速度(MTS)。在这项研究中,我们尝试使用不带ID号的GPS数据估算道路的MTS。通过考虑MTS与时间平均速度(TMS)之间的关系并进行MTS与估计的空间平均速度(eSMS)之间的关系的实验来进行估计。另外,在市区内道路上,车速变化很大。因此,我们提出了在路段上的点速度数据的分组方法,称为分段,以减少交通差异并分析所收集的数据以进行MTS估计。结果表明,TMS和MTS之间的相关性为0.94,并且TMS和MTS之间的关系图具有线性趋势线。因此,TMS和MTS是非常相关的。总之,如果在短段(50 m),低流量方差数据和合适的时间段(5分钟)下计算TMS,则可以改进MTS估计并将其发展为模型或方程式。

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