{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T05:35:12Z","timestamp":1769837712261,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,5]],"date-time":"2019-09-05T00:00:00Z","timestamp":1567641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010248","name":"Zhejiang Province Public Welfare Technology Application Research Project","doi-asserted-by":"publisher","award":["LGG19F030012"],"award-info":[{"award-number":["LGG19F030012"]}],"id":[{"id":"10.13039\/501100010248","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 61603339"],"award-info":[{"award-number":["No. 61603339"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scientific Research Project of Education Department of Zhejiang","award":["No. Y201840830"],"award-info":[{"award-number":["No. Y201840830"]}]},{"DOI":"10.13039\/501100012279","name":"Zhejiang Xinmiao Talents Program","doi-asserted-by":"publisher","award":["No. 2019R403073"],"award-info":[{"award-number":["No. 2019R403073"]}],"id":[{"id":"10.13039\/501100012279","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Short-term traffic speed prediction has become one of the most important parts of intelligent transportation systems (ITSs). In recent years, deep learning methods have demonstrated their superiority both in accuracy and efficiency. However, most of them only consider the temporal information, overlooking the spatial or some environmental factors, especially the different correlations between the target road and the surrounding roads. This paper proposes a traffic speed prediction approach based on temporal clustering and hierarchical attention (TCHA) to address the above issues. We apply temporal clustering to the target road to distinguish the traffic environment. Traffic data in each cluster have a similar distribution, which can help improve the prediction accuracy. A hierarchical attention-based mechanism is then used to extract the features at each time step. The encoder measures the importance of spatial features, and the decoder measures the temporal ones. The proposed method is evaluated over the data of a certain area in Hangzhou, and experiments have shown that this method can outperform the state of the art for traffic speed prediction.<\/jats:p>","DOI":"10.3390\/s19183836","type":"journal-article","created":{"date-parts":[[2019,9,6]],"date-time":"2019-09-06T02:59:22Z","timestamp":1567738762000},"page":"3836","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Traffic Speed Prediction: An Attention-Based Method"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1466-0627","authenticated-orcid":false,"given":"Duanyang","family":"Liu","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7498-1783","authenticated-orcid":false,"given":"Longfeng","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojiang","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3478-964X","authenticated-orcid":false,"given":"Xiao","family":"Han","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.trc.2014.01.005","article-title":"Short-term traffic forecasting: Where we are and where we\u2019re going","volume":"43","author":"Vlahogianni","year":"2014","journal-title":"Transp. 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