{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T15:26:41Z","timestamp":1777994801159,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T00:00:00Z","timestamp":1708041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Project of the National Natural Science Foundation of China","award":["62262063"],"award-info":[{"award-number":["62262063"]}]},{"name":"Project of the National Natural Science Foundation of China","award":["202101AS070007"],"award-info":[{"award-number":["202101AS070007"]}]},{"name":"Project of the National Natural Science Foundation of China","award":["202205AF150013"],"award-info":[{"award-number":["202205AF150013"]}]},{"name":"Project of the National Natural Science Foundation of China","award":["2022Y561"],"award-info":[{"award-number":["2022Y561"]}]},{"name":"Project of the Key Science Foundation of Yunnan Province","award":["62262063"],"award-info":[{"award-number":["62262063"]}]},{"name":"Project of the Key Science Foundation of Yunnan Province","award":["202101AS070007"],"award-info":[{"award-number":["202101AS070007"]}]},{"name":"Project of the Key Science Foundation of Yunnan Province","award":["202205AF150013"],"award-info":[{"award-number":["202205AF150013"]}]},{"name":"Project of the Key Science Foundation of Yunnan Province","award":["2022Y561"],"award-info":[{"award-number":["2022Y561"]}]},{"name":"Dou Wanchun Expert Workstation of Yunnan Province","award":["62262063"],"award-info":[{"award-number":["62262063"]}]},{"name":"Dou Wanchun Expert Workstation of Yunnan Province","award":["202101AS070007"],"award-info":[{"award-number":["202101AS070007"]}]},{"name":"Dou Wanchun Expert Workstation of Yunnan Province","award":["202205AF150013"],"award-info":[{"award-number":["202205AF150013"]}]},{"name":"Dou Wanchun Expert Workstation of Yunnan Province","award":["2022Y561"],"award-info":[{"award-number":["2022Y561"]}]},{"name":"Science and Technology Youth lift talents of Yunnan Province","award":["62262063"],"award-info":[{"award-number":["62262063"]}]},{"name":"Science and Technology Youth lift talents of Yunnan Province","award":["202101AS070007"],"award-info":[{"award-number":["202101AS070007"]}]},{"name":"Science and Technology Youth lift talents of Yunnan Province","award":["202205AF150013"],"award-info":[{"award-number":["202205AF150013"]}]},{"name":"Science and Technology Youth lift talents of Yunnan Province","award":["2022Y561"],"award-info":[{"award-number":["2022Y561"]}]},{"name":"Scientific Research Fund Project of the Yunnan Education Department","award":["62262063"],"award-info":[{"award-number":["62262063"]}]},{"name":"Scientific Research Fund Project of the Yunnan Education Department","award":["202101AS070007"],"award-info":[{"award-number":["202101AS070007"]}]},{"name":"Scientific Research Fund Project of the Yunnan Education Department","award":["202205AF150013"],"award-info":[{"award-number":["202205AF150013"]}]},{"name":"Scientific Research Fund Project of the Yunnan Education Department","award":["2022Y561"],"award-info":[{"award-number":["2022Y561"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Traffic congestion prediction has become an indispensable component of an intelligent transport system. However, one limitation of the existing methods is that they treat the effects of spatio-temporal correlations on traffic prediction as invariable during modeling spatio-temporal features, which results in inadequate modeling. In this paper, we propose an attention-based spatio-temporal 3D residual neural network, named AST3DRNet, to directly forecast the congestion levels of road networks in a city. AST3DRNet combines a 3D residual network and a self-attention mechanism together to efficiently model the spatial and temporal information of traffic congestion data. Specifically, by stacking 3D residual units and 3D convolution, we proposed a 3D convolution module that can simultaneously capture various spatio-temporal correlations. Furthermore, a novel spatio-temporal attention module is proposed to explicitly model the different contributions of spatio-temporal correlations in both spatial and temporal dimensions through the self-attention mechanism. Extensive experiments are conducted on a real-world traffic congestion dataset in Kunming, and the results demonstrate that AST3DRNet outperforms the baselines in short-term (5\/10\/15 min) traffic congestion predictions with an average accuracy improvement of 59.05%, 64.69%, and 48.22%, respectively.<\/jats:p>","DOI":"10.3390\/s24041261","type":"journal-article","created":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T06:00:25Z","timestamp":1708063225000},"page":"1261","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["AST3DRNet: Attention-Based Spatio-Temporal 3D Residual Neural Networks for Traffic Congestion Prediction"],"prefix":"10.3390","volume":"24","author":[{"given":"Lecheng","family":"Li","sequence":"first","affiliation":[{"name":"School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bi","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanchun","family":"Dou","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing 210008, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaodong","family":"Fu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Liu, Y., Zheng, H., Feng, X., and Chen, Z. 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