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A graph\u2010transformer intention generator running on roadside and metro\u2010edge nodes fuses V2X trajectory snippets from up to 120 agents into kilobyte\u2010size probability maps of future maneuvers. Each vehicle keeps feasibility checks on board, while large\u2010scale collision resolution is off\u2010loaded to a metro\u2010edge mixed\u2010integer solver. A Coq\u2010verified safety shield triggers emergency braking whenever network latency exceeds a derived bound. Deployed on 10 Jetson Orin NX cars and 4 Xeon Silver edge servers over a standalone 5\u2009G link, SafeEdge clears four\u2010way intersections with a 96% success rate and a 95th\u2010percentile decision latency of 32\u2009ms\u2014well below the 50\u2009ms safety envelope. Relative to an on\u2010board MPC baseline, emergency\u2010brake events drop by 70% and energy per kilometer falls by 11%. These results demonstrate that intention\u2010aware, edge\u2010partitioned planning can simultaneously satisfy real\u2010time and safety requirements in dense urban driving.<\/jats:p>","DOI":"10.1002\/itl2.70143","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T05:35:39Z","timestamp":1759469739000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>SafeEdge<\/scp>\n                    : Intention\u2010Aware Cooperative Motion Planning for Autonomous Vehicles Over Mobile Edge Networks"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0182-0744","authenticated-orcid":false,"given":"Jindan","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Automotive Engineering, Jilin Engineering Vocational College  Jilin China"}]}],"member":"311","published-online":{"date-parts":[[2025,10,2]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3028424"},{"key":"e_1_2_8_3_1","doi-asserted-by":"crossref","unstructured":"T. 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