{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:27:41Z","timestamp":1783528061326,"version":"3.55.0"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Berkeley DeepDrive"},{"DOI":"10.13039\/501100001348","name":"Agency for Science, Technology and Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001348","id-type":"DOI","asserted-by":"publisher"}]},{"name":"MTC Individual Research","award":["M22K2c0079"],"award-info":[{"award-number":["M22K2c0079"]}]},{"DOI":"10.13039\/100010449","name":"Ministry of Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010449","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tier 2","award":["MOE-T2EP50222-0002"],"award-info":[{"award-number":["MOE-T2EP50222-0002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/lra.2024.3416771","type":"journal-article","created":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T17:40:31Z","timestamp":1718818831000},"page":"7023-7030","source":"Crossref","is-referenced-by-count":20,"title":["Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1592-7215","authenticated-orcid":false,"given":"Zhiyu","family":"Huang","sequence":"first","affiliation":[{"name":"University of California, Berkeley, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7536-9983","authenticated-orcid":false,"given":"Chen","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Texas, Austin, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6897-4512","authenticated-orcid":false,"given":"Chen","family":"Lv","sequence":"additional","affiliation":[{"name":"School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0206-6639","authenticated-orcid":false,"given":"Masayoshi","family":"Tomizuka","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, The University of California, Berkeley, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1474-1200","authenticated-orcid":false,"given":"Wei","family":"Zhan","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, The University of California, Berkeley, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"A taxonomy and review of algorithms for modeling and predicting human driver behavior","author":"Brown","year":"2020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3182687"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2017.2788208"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC55140.2022.9922488"},{"key":"ref5","article-title":"BetaZero: Belief-state planning for long-horizon POMDPs using learned approximations","author":"Moss","year":"2023"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.018"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2022.3210767"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561967"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3254579"},{"key":"ref10","article-title":"MBAPPE: MCTS-built-around prediction for planning explicitly","author":"Chekroun","year":"2023"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3191241"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2024.3401683"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2016.7860383"},{"key":"ref14","article-title":"Game theoretic decision making by actively learning human intentions applied on autonomous driving","author":"Dai","year":"2023"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v28i1.13882"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-03051-4"},{"key":"ref17","first-page":"2117","article-title":"Deep variational reinforcement learning for POMDPs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Igl","year":"2018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.001"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3352811"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160609"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01713"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00781"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IROS55552.2023.10341894"},{"key":"ref24","article-title":"DTPP: Differentiable joint conditional prediction and cost evaluation for tree policy planning in autonomous driving","author":"Huang","year":"2023"},{"key":"ref25","first-page":"1006","article-title":"Deep interactive motion prediction and planning: Playing games with motion prediction models","volume-title":"Proc. Learn. Dyn. Control Conf.","author":"Espinoza","year":"2022"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.11418"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304787"},{"key":"ref28","first-page":"1587","article-title":"Addressing function approximation error in actor-critic methods","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Fujimoto","year":"2018"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00957"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3190471"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2024.3354102"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3283542"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00361"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/10561888\/10563192.pdf?arnumber=10563192","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,29]],"date-time":"2024-06-29T05:21:02Z","timestamp":1719638462000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10563192\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":33,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/lra.2024.3416771","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}