Real-time Traffic Data De-noising Based on Wavelet De-noising

DOI

10.2991/iccte-16.2016.240How to use a DOI?

Keywords

Real-time Traffic Data, Wavelet, De-noising, Reconstruction, Threshold.

Abstract

As a variety of interference exists in the real-time traffic data in the actual sampling environment and the traffic data is not stable, we do wavelet decomposition for traffic data in this paper. In order to get better de-noising effect, we add the noise to a set of given similar traffic signal, and then use the soft and hard threshold to deal with the noisy signal. The simulation results show that the traffic signal after hard threshold de-noising can see the peak value and underestimate value clearly. Therefore, we select the hard threshold method to deal with the real time traffic signal, which can provide an effective basis for the prediction of the traffic intersection and the control of the signal.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qian Xiao
AU  - Yingchao Li
AU  - Shuwei Wu
AU  - Zhipeng Zhao
PY  - 2016/01
DA  - 2016/01
TI  - Real-time Traffic Data De-noising Based on Wavelet De-noising
BT  - Proceedings of the 2016 International Conference on Civil, Transportation and Environment
PB  - Atlantis Press
SP  - 1366
EP  - 1369
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccte-16.2016.240
DO  - 10.2991/iccte-16.2016.240
ID  - Xiao2016/01
ER  -