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Travel Characteristics Extracting Method Based on Cellular Network Recording Data

机译：基于蜂窝网络记录数据的出行特征提取方法

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Compared to other types of cellular signaling data, cellular network recording data has several unique advantages on extracting travel characteristics, including comprehensive samples, high location accuracy, elaborate trajectory, and high data stability. With such advantageous attributes, a series of methods are proposed in order to extract valuable information. First, in order to build candidate default trajectory point set, Bowyer-Watson algorithm is applied to delimit Voronoi diagram of base station coverage. Second, a user's trajectory is segmented based on motion state discriminant algorithms. This is done in which sample filtering and noise reduction are helpful for parameter extraction. Third, the MBR of trajectory point subset is introduced to improve conventional piecewise map-matching algorithms. Lastly, the proposed algorithm will be evaluated by verifying the accuracy of the parameters. Preliminary results show that the extracted parameters are acceptable for further traffic modeling application at both macro and micro levels and are expected to replace the traditional individual trip survey.
机译：与其他类型的蜂窝信令数据相比，蜂窝网络记录数据在提取旅行特征方面具有多个独特优势，包括全面的样本，较高的定位精度，精细的轨迹以及较高的数据稳定性。具有这样的有利属性，提出了一系列方法以提取有价值的信息。首先，为了建立候选的默认轨迹点集，应用Bowyer-Watson算法定界基站覆盖的Voronoi图。其次，基于运动状态判别算法对用户的轨迹进行分段。在此过程中，样本过滤和降噪有助于参数提取。第三，引入了轨迹点子集的MBR，以改进传统的分段地图匹配算法。最后，将通过验证参数的准确性来评估所提出的算法。初步结果表明，所提取的参数对于宏观和微观层面的进一步交通建模应用都是可以接受的，并且有望替代传统的个人出行调查。

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