Data Processing Techniques for Real-Time Traveler Information: Use of Dedicated Short-Range Communications Probes on Suburban Arterial

Q3 Social Sciences
Jinhwan Jang
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引用次数: 0

Abstract

In this study, data processing methods for addressing the two issues are proposed. After investigating the characteristic of the travel times on the test section, the modified z-score was suggested for censoring outliers contained in probe travel times. To mitigate the time-lag phenomenon, a recurrent neural network, a class of deep learning where temporal sequence data are normally treated, was applied to predict travel times.
实时旅行者信息的数据处理技术:在郊区干线上使用专用短程通信探头
在本研究中,提出了解决这两个问题的数据处理方法。在研究了测试段上行程时间的特征后,建议使用修正的z分数来审查包含在探针行程时间中的异常值。为了缓解时滞现象,将递归神经网络(一类通常处理时间序列数据的深度学习)应用于预测旅行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Open Transportation Journal
Open Transportation Journal Social Sciences-Transportation
CiteScore
2.10
自引率
0.00%
发文量
19
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