{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:18:33Z","timestamp":1783095513236,"version":"3.54.6"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2022ZD0115500"],"award-info":[{"award-number":["2022ZD0115500"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976039"],"award-info":[{"award-number":["61976039"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Fundamental Research Funds for the Central Universities","award":["DUT22JC09"],"award-info":[{"award-number":["DUT22JC09"]}]},{"name":"Chongqing Postdoctoral Innovation Talent Support Program","award":["CQBX2021009"],"award-info":[{"award-number":["CQBX2021009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Veh."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tiv.2023.3275164","type":"journal-article","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T17:39:40Z","timestamp":1683826780000},"page":"4055-4069","source":"Crossref","is-referenced-by-count":21,"title":["Real-Time Heterogeneous Road-Agents Trajectory Prediction Using Hierarchical Convolutional Networks and Multi-Task Learning"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2667-8800","authenticated-orcid":false,"given":"Linhui","family":"Li","sequence":"first","affiliation":[{"name":"School of Automotive Engineering, Faculty of Vehicle Engineering and Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2226-3106","authenticated-orcid":false,"given":"Xuecheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automotive Engineering, Faculty of Vehicle Engineering and Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9212-6804","authenticated-orcid":false,"given":"Dongfang","family":"Yang","sequence":"additional","affiliation":[{"name":"Chongqing Chang&#x0027;an Automobile Co., Ltd., Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3509-6738","authenticated-orcid":false,"given":"Yifan","family":"Ju","sequence":"additional","affiliation":[{"name":"School of Automotive Engineering, Faculty of Vehicle Engineering and Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongxu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chongqing Chang&#x0027;an Automobile Co., Ltd., Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2095-5563","authenticated-orcid":false,"given":"Jing","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Automotive Engineering, Faculty of Vehicle Engineering and Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"895","article-title":"TNT: Target-driven trajectory prediction","volume-title":"Proc. Conf. Robot Learn","author":"Zhao","year":"2021"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_32"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01408"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793868"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3160648"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01440"},{"key":"ref8","article-title":"Trajectory forecasts in unknown environments conditioned on grid-based plans","author":"Deo","year":"2020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00967"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.233"},{"key":"ref11","first-page":"947","article-title":"IntentNet: Learning to predict intention from raw sensor data","volume-title":"Proc. Conf. Robot Learn","author":"Casas","year":"2018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.031"},{"key":"ref13","first-page":"86","article-title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction","volume-title":"Proc. Conf. Robot Learn","author":"Chai","year":"2020"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01154"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01140"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01499"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206641"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33765-9_15"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5244\/C.16.54"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00240"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00144"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01502"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9812253"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref25","first-page":"1","article-title":"Scene transformer: A. unified architecture for predicting future trajectories of multiple agents","author":"Ngiam","year":"2022","journal-title":"Proc. Int. Conf. Learn. Representations"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00749"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/icra48891.2023.10160609"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00196"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575874"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00862"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317874"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636279"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560849"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9635903"},{"key":"ref35","article-title":"HOPE: Hierarchical spatial-temporal network for occupancy flow prediction","author":"Hu","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3151613"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00683"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636035"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9812107"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref41","first-page":"409","article-title":"One thousand and one hours: Self-driving motion prediction dataset","volume-title":"Proc. Conf. Robot Learn","author":"Houston","year":"2021"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01659"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58523-5_40"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575718"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3145090"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9982283"},{"key":"ref47","article-title":"MATS: An interpretable trajectory forecasting representation for planning and control","author":"Ivanovic","year":"2020"}],"container-title":["IEEE Transactions on Intelligent Vehicles"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274857\/10510053\/10123087.pdf?arnumber=10123087","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T19:10:13Z","timestamp":1714763413000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10123087\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":47,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tiv.2023.3275164","relation":{},"ISSN":["2379-8904","2379-8858"],"issn-type":[{"value":"2379-8904","type":"electronic"},{"value":"2379-8858","type":"print"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}