3D-ConvLSTMNet: A Deep Spatio-Temporal Model for Traffic Flow Prediction

Lihua He, Wuman Luo

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

Spatiotemporal correlations are crucial for traffic flow prediction. So far, various traffic flow prediction methods based on convolutional neural network (CNN) and long short-term memory (LSTM) network have been proposed. However, the common CNN - based models cannot preserve the temporal information after the first layer. Although the 3D CNN-based models can effectively capture short-term spatial and tempo-ral features, they are not suitable for long-term information capturing. LSTM is excellent at long-term features extraction. However, it alone cannot be used for spatial information extraction. To address these issues, we propose a deep architecture called 3D-ConvLSTMNet to better capture the spatiotemporal correlations among the traffic data. Specifically, we proposed a short-long term spatiotemporal feature extraction module called 3D-ConvLSTM, which uses 3D CNN to extract short-term spatiotemporal correlations, and uses ConvLSTM to extract the long-term spatiotemporal correlations. To get the long-distance spatial features, we adopt the residual neural network to develop the depth of 3D-ConvLSTMNet. Finally, we utilize a channel-wise attention mechanism to quantify the contribution of each grid in space domain. To evaluate the performances of ConvLSTMNet, we conduct extensive experiments on two real-world datasets. The experiment results show that our model gets better performances than the other state-of-the-art methods.

原文English
主出版物標題Proceedings - 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面147-152
頁數6
ISBN(電子)9781665451765
DOIs
出版狀態Published - 2022
事件23rd IEEE International Conference on Mobile Data Management, MDM 2022 - Virtual, Paphos, Cyprus
持續時間: 6 6月 20229 6月 2022

出版系列

名字Proceedings - IEEE International Conference on Mobile Data Management
2022-June
ISSN(列印)1551-6245

Conference

Conference23rd IEEE International Conference on Mobile Data Management, MDM 2022
國家/地區Cyprus
城市Virtual, Paphos
期間6/06/229/06/22

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