{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T07:10:21Z","timestamp":1775027421769,"version":"3.50.1"},"reference-count":63,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB1702703"],"award-info":[{"award-number":["2018YFB1702703"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund of China State Key Laboratory of Intelligent Manufacturing System Technology"},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1109\/tits.2020.2981118","type":"journal-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T19:56:08Z","timestamp":1584734168000},"page":"3285-3302","source":"Crossref","is-referenced-by-count":135,"title":["Pedestrian Trajectory Prediction Based on Deep Convolutional LSTM Network"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4279-426X","authenticated-orcid":false,"given":"Xiao","family":"Song","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2436-1420","authenticated-orcid":false,"given":"Kai","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Xu","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7785-2971","authenticated-orcid":false,"given":"Jinghan","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Baocun","family":"Hou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8869-6529","authenticated-orcid":false,"given":"Yong","family":"Cui","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7396-6218","authenticated-orcid":false,"given":"Baochang","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4303-5559","authenticated-orcid":false,"given":"Gang","family":"Xiong","sequence":"additional","affiliation":[]},{"given":"Zilie","family":"Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2684186"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-21233-3_6"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1177\/0278364914555543"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19457-3_1"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2018.03.085"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1118633109"},{"key":"ref37","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","author":"shi","year":"2015","journal-title":"Proc Neural Inf Process Syst (NIPS)"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2018.06.045"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-2853-4_23"},{"key":"ref34","article-title":"Context-aware trajectory prediction","author":"bartoli","year":"2017","journal-title":"arXiv 1705 02503"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00240"},{"key":"ref62","article-title":"Human trajectory prediction using spatially aware deep attention models","author":"varshneya","year":"2017","journal-title":"arXiv 1705 09436"},{"key":"ref61","article-title":"Scene-LSTM: A model for human trajectory prediction","author":"manh","year":"2018","journal-title":"arXiv 1808 04018"},{"key":"ref63","article-title":"SoPhie: An attentive GAN for predicting paths compliant to social and physical constraints","author":"sadeghian","year":"2018","journal-title":"arXiv 1806 01482"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.465"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2013.12.005"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2016.08.015"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.81.591"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/35035023"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/DS-RT.2013.21"},{"key":"ref22","first-page":"517","article-title":"Evacuation dynamics: Empirical results, modeling and applications","author":"schadschneider","year":"2008","journal-title":"Encyclopedia of Complexity and Systems Science"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2016.04.001"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966368"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.2307\/1907266"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1287\/trsc.1040.0108"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00096"},{"key":"ref51","article-title":"Towards understanding regularization in batch normalization","author":"luo","year":"2018"},{"key":"ref59","first-page":"186","article-title":"Convolutional neural network for trajectory prediction","author":"nikhil","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00135"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2007.01089.x"},{"key":"ref56","first-page":"261","article-title":"You&#x2019;ll never walk alone: Modeling social behavior for multi-target tracking","author":"pellegrini","year":"2009","journal-title":"Proc IEEE 12th Int Conf Comput Vis"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2060218"},{"key":"ref54","article-title":"Scanning the issue and beyond: Computational","author":"wang","year":"2015"},{"key":"ref53","author":"widrow","year":"1985","journal-title":"Adaptive Signal Processing"},{"key":"ref52","article-title":"An information theoretic approach to machine learning","author":"jenssen","year":"2005"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1088\/0256-307X\/29\/1\/018901"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/OSSC.2009.5416792"},{"key":"ref40","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NIPS"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/6979.892151"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/25.806795"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2005.858824"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2005.11.007"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/fi5030336"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2015.2453341"},{"key":"ref18","article-title":"Beyond regression: New tools for prediction and analysis in the behavioral sciences","author":"werbos","year":"1974"},{"key":"ref19","article-title":"Transporttechnik der fussganger","volume":"90","author":"weidmann","year":"1993","journal-title":"Transporttechnische Eigenschaften des Fussgangerverkehrs"},{"key":"ref4","first-page":"1764","article-title":"Towards end-to-end speech recognition with recurrent neural networks","author":"graves","year":"2014","journal-title":"Proc 31st Int Conf Mach Learn (ICML)"},{"key":"ref3","article-title":"Generating sequences with recurrent neural networks","author":"graves","year":"2013","journal-title":"arXiv 1308 0850 [cs]"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0169734"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.90.063305"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2542843"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2015.12.041"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460504"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.110"},{"key":"ref46","author":"barbosa","year":"2019","journal-title":"Easily Calculable Measure for the Complexity of Spatiotemporal Patterns"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1976.1055501"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/BigComp.2018.00021"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3934\/nhm.2011.6.425"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2873118"},{"key":"ref41","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3006294"},{"key":"ref43","first-page":"2879","article-title":"Convergence rates of efficient global optimization algorithms","volume":"12","author":"bull","year":"2011","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/9444590\/09043898.pdf?arnumber=9043898","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T20:49:12Z","timestamp":1635281352000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9043898\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6]]},"references-count":63,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tits.2020.2981118","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6]]}}}