{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:25:18Z","timestamp":1781018718414,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T00:00:00Z","timestamp":1774224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,3,23]]},"DOI":"10.1145\/3748522.3779985","type":"proceedings-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T14:17:49Z","timestamp":1781014669000},"page":"2088-2095","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Trajectory Prediction and Intelligent RSU Handover for Connected Vehicles Using Deep Sequential and Ensemble Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2150-952X","authenticated-orcid":false,"given":"Muhammad Azfar","family":"Yaqub","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2723-2410","authenticated-orcid":false,"given":"Attaullah","family":"Buriro","sequence":"additional","affiliation":[{"name":"University of Essex, Colchester, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1721-4681","authenticated-orcid":false,"given":"Malik Muhammad","family":"Saad","sequence":"additional","affiliation":[{"name":"Kyungpook National University, Daegu, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1731-0489","authenticated-orcid":false,"given":"Amir","family":"Aieb","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2773-4421","authenticated-orcid":false,"given":"Antonio","family":"Liotta","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Free University of Bozen-Bolzano, Italy, Bolzano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9586-0833","authenticated-orcid":false,"given":"Muhammad Rehan","family":"Usman","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Computing and the Environment, Kingston University London, London, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3115908"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-1433-9"},{"key":"e_1_3_2_1_3_1","volume-title":"Multi-access Edge Computing (MEC)","author":"ETSI GS MEC.","unstructured":"ETSI GS MEC. 2022. Multi-access Edge Computing (MEC); Framework and Reference Architecture. Tech. rep. ETSI."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2017.2745201"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2017.2682318"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"e_1_3_2_1_7_1","volume-title":"Proc. CVPR, 336\u2013345","author":"Lee N.","unstructured":"N. Lee, W. Choi, P. Vernaza, C. B. Choy, P. H. S. Torr, and M. Chandraker. 2017. Desire: distant future prediction in dynamic scenes with interacting agents. In Proc. CVPR, 336\u2013345."},{"key":"e_1_3_2_1_8_1","volume-title":"Proc. ECCV.","author":"Salzmann Tim","year":"2020","unstructured":"Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone. 2020. Trajectron++: multi-agent generative trajectory forecasting with heterogeneous data. In Proc. ECCV."},{"key":"e_1_3_2_1_9_1","volume-title":"Proc. CVPR, 11525\u201311533","author":"Jingwei","unstructured":"Jingwei Gao et al. 2020. Vectornet: encoding hd maps and agent dynamics from vectorized representation. In Proc. CVPR, 11525\u201311533."},{"key":"e_1_3_2_1_10_1","volume-title":"Proc. ICCV.","author":"Scott","unstructured":"Scott Ettinger and et al. 2021. Large scale interactive motion forecasting for autonomous driving: the waymo open motion dataset. In Proc. ICCV."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3169804"},{"key":"e_1_3_2_1_12_1","volume-title":"Siriwardhana et al","author":"A. C. P.","year":"2025","unstructured":"A. C. P. K. Siriwardhana et al. 2025. Optimizing handover mechanism in vehicular networks using deep learning and optimization techniques. Computer Networks, 219."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"R. Khoder et al. 2024. On using machine learning for vertical handover decision making in a vehicular platoon. In Springer Preprint.","DOI":"10.21203\/rs.3.rs-3847822\/v1"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317913"},{"key":"e_1_3_2_1_15_1","first-page":"3","article-title":"Vit-traj: a spatial-temporal coupling vehicle trajectory prediction model based on vision transformer","volume":"13","author":"Rui Cheng","year":"2025","unstructured":"Rui Cheng et al. 2025. Vit-traj: a spatial-temporal coupling vehicle trajectory prediction model based on vision transformer. Systems, 13, 3, 147.","journal-title":"Systems"},{"key":"e_1_3_2_1_16_1","first-page":"4","article-title":"Machine learning-based vehicle trajectory prediction using v2v communications and on-board sensors","volume":"10","author":"Dabin Choi","year":"2021","unstructured":"Dabin Choi et al. 2021. Machine learning-based vehicle trajectory prediction using v2v communications and on-board sensors. Electronics, 10, 4, 420.","journal-title":"Electronics"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3112077"},{"key":"e_1_3_2_1_18_1","first-page":"5s","article-title":"B-aware: blockage aware rsu scheduling for 5g enabled autonomous vehicles","volume":"22","author":"Michael Szeto","year":"2023","unstructured":"Michael Szeto et al. 2023. B-aware: blockage aware rsu scheduling for 5g enabled autonomous vehicles. ACM Transactions on Embedded Computing Systems, 22, 5s, 111.","journal-title":"ACM Transactions on Embedded Computing Systems"},{"key":"e_1_3_2_1_19_1","unstructured":"Niels Spring et al. 2025. Mach: multi-agent coordination for rsu-centric handovers. arXiv preprint arXiv:2505.07827."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3017474"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CCWC.2018.8301714"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-024-10759-6"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","unstructured":"Jianxin Shi Jinhao Chen Yuandong Wang Li Sun Chunyang Liu Wei Xiong and Tianyu Wo. 2025. Motion forecasting for autonomous vehicles: a survey. arXiv:2502.08664 [cs.RO]. 10.48550\/arXiv.2502.08664","DOI":"10.48550\/arXiv.2502.08664"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3547811"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2874692"},{"key":"e_1_3_2_1_27_1","unstructured":"Tim Tiernan Nicholas Richardson Philip Azeredo Wassim G Najm Taylor Lochrane et al. 2017. Test and evaluation of vehicle platooning proof-of-concept based on cooperative adaptive cruise control. Tech. rep. John A. Volpe National Transportation Systems Center (US)."},{"key":"e_1_3_2_1_28_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2014","unstructured":"Diederik P. Kingma and Jimmy Ba. 2014. Adam: a method for stochastic optimization. CoRR, abs\/1412.6980. https:\/\/api.semanticscholar.org\/CorpusID:6628106."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_1_30_1","unstructured":"F. Pedregosa et al. 2011. Scikit-learn: machine learning in Python. In Journal of Machine Learning Research. Vol. 12. JMLR.org 2825\u20132830."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v045.i03"}],"event":{"name":"SAC '26: 41st ACM\/SIGAPP Symposium on Applied Computing","location":"Grand Hotel Palace Thessaloniki Greece","acronym":"SAC '26","sponsor":["SIGAPP ACM Special Interest Group on Applied Computing"]},"container-title":["Proceedings of the 41st ACM\/SIGAPP Symposium on Applied Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3748522.3779985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T14:26:39Z","timestamp":1781015199000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3748522.3779985"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,23]]},"references-count":32,"alternative-id":["10.1145\/3748522.3779985","10.1145\/3748522"],"URL":"https:\/\/doi.org\/10.1145\/3748522.3779985","relation":{},"subject":[],"published":{"date-parts":[[2026,3,23]]},"assertion":[{"value":"2026-06-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}