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Consequently, some traffic data collected at checkpoints may be incomplete, which complicates data analysis. To address this issue, we propose using a neural network based on embedding synchronized spatio-temporal map data. Firstly, we designed a trajectory vectorization algorithm using word embedding techniques, modeling the road network with vehicle trajectories to capture spatial correlations among road checkpoints. Secondly, we constructed a spatio-temporal synchronization graph recovery neural network (STSGRN) that uses graph convolutional networks (GCNs) and gated recurrent units (GRUs) to account for the spatio-temporal characteristics of traffic data and fill in missing data across multiple dimensions. Finally, we developed an attention mechanism module for the spatio-temporal graph to extract dynamic dependencies at the spatio-temporal level. This architecture enhances the flexibility of the STSGRN in processing complex data with missing values. Experimental results demonstrate that the model effectively identifies spatial and temporal correlations in traffic data, enabling the accurate imputation of missing values. Compared to existing methods, it demonstrates significant improvements and superior generalization performance.<\/jats:p>","DOI":"10.1145\/3807952","type":"journal-article","created":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T14:48:16Z","timestamp":1775832496000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Traffic Data Imputation Method Based on Spatial-temporal Synchronous Graph Recovery Neural Network"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4595-8215","authenticated-orcid":false,"given":"Chaolong","family":"Jia","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5183-2551","authenticated-orcid":false,"given":"Zigao","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0170-2454","authenticated-orcid":false,"given":"Wenhui","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7963-1766","authenticated-orcid":false,"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2846-3571","authenticated-orcid":false,"given":"Yunpeng","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,20]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2025.3531221"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC55140.2022.9922425"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3172447"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.03.009"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106549"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2024.3423348"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1155\/int\/3715086"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcan.2020.03.002"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125531"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3161792"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110814"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2024.124611"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128948"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119972"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3203791"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.02.017"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/CAC.2017.8244105"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3233890"},{"key":"e_1_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Yiming Wang Hao Peng Senzhang Wang Haohua Du Chunyang Liu Jia Wu and Guanlin Wu. 2025. 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