{"id":"https://openalex.org/W3012055358","doi":"https://doi.org/10.1109/tits.2020.2981118","title":"Pedestrian Trajectory Prediction Based on Deep Convolutional LSTM Network","display_name":"Pedestrian Trajectory Prediction Based on Deep Convolutional LSTM Network","publication_year":2020,"publication_date":"2020-03-20","ids":{"openalex":"https://openalex.org/W3012055358","doi":"https://doi.org/10.1109/tits.2020.2981118","mag":"3012055358"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2020.2981118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2981118","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050439131","display_name":"Xiao Song","orcid":"https://orcid.org/0000-0003-4279-426X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Song","raw_affiliation_strings":["School of Automation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027855551","display_name":"Kai Chen","orcid":"https://orcid.org/0000-0002-2436-1420"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Chen","raw_affiliation_strings":["School of Automation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342475","display_name":"Xu Li","orcid":"https://orcid.org/0000-0002-8916-1489"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu Li","raw_affiliation_strings":["China State Key Laboratory of Intelligent Manufacturing System Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China State Key Laboratory of Intelligent Manufacturing System Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045322182","display_name":"Jinghan Sun","orcid":"https://orcid.org/0000-0001-7785-2971"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinghan Sun","raw_affiliation_strings":["Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113433007","display_name":"Baocun Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baocun Hou","raw_affiliation_strings":["Beijing Aerospace Smart Manufacturing Technology Development Company, Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Aerospace Smart Manufacturing Technology Development Company, Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022362043","display_name":"Yong Cui","orcid":"https://orcid.org/0000-0002-8869-6529"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Cui","raw_affiliation_strings":["School of Automation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015525872","display_name":"Baochang Zhang","orcid":"https://orcid.org/0000-0001-7396-6218"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baochang Zhang","raw_affiliation_strings":["School of Automation, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088979194","display_name":"Gang Xiong","orcid":"https://orcid.org/0000-0002-4303-5559"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Xiong","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010604471","display_name":"Zilie Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilie Wang","raw_affiliation_strings":["School of Software, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5050439131"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":14.6581,"has_fulltext":false,"cited_by_count":150,"citation_normalized_percentile":{"value":0.99521948,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"6","first_page":"3285","last_page":"3302"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.8160381317138672},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8122755885124207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.738844096660614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6402394771575928},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.554825484752655},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.550722062587738},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5120144486427307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44552767276763916},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.316339373588562},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12699681520462036}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8160381317138672},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8122755885124207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.738844096660614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6402394771575928},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.554825484752655},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.550722062587738},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5120144486427307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44552767276763916},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.316339373588562},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12699681520462036},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2020.2981118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2981118","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G8693496991","display_name":null,"funder_award_id":"2018YFB1702703","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W192919555","https://openalex.org/W639708223","https://openalex.org/W1485009520","https://openalex.org/W1500076871","https://openalex.org/W1504411444","https://openalex.org/W1554187497","https://openalex.org/W1573503290","https://openalex.org/W1579548549","https://openalex.org/W1686810756","https://openalex.org/W1810943226","https://openalex.org/W1857884451","https://openalex.org/W1888172398","https://openalex.org/W1966041161","https://openalex.org/W1970206276","https://openalex.org/W2000832731","https://openalex.org/W2007008940","https://openalex.org/W2017990047","https://openalex.org/W2058105398","https://openalex.org/W2061732708","https://openalex.org/W2071292957","https://openalex.org/W2071860582","https://openalex.org/W2072956256","https://openalex.org/W2077770566","https://openalex.org/W2092685486","https://openalex.org/W2094256875","https://openalex.org/W2102113734","https://openalex.org/W2102204212","https://openalex.org/W2111373303","https://openalex.org/W2117561707","https://openalex.org/W2129589491","https://openalex.org/W2132505539","https://openalex.org/W2133747588","https://openalex.org/W2163272476","https://openalex.org/W2163605009","https://openalex.org/W2216310657","https://openalex.org/W2317615359","https://openalex.org/W2345324220","https://openalex.org/W2424778531","https://openalex.org/W2482792214","https://openalex.org/W2508755380","https://openalex.org/W2532516272","https://openalex.org/W2546124871","https://openalex.org/W2572202106","https://openalex.org/W2595328592","https://openalex.org/W2617510024","https://openalex.org/W2735109634","https://openalex.org/W2766836212","https://openalex.org/W2795276939","https://openalex.org/W2796117272","https://openalex.org/W2801667201","https://openalex.org/W2808902547","https://openalex.org/W2886483202","https://openalex.org/W2891058410","https://openalex.org/W2895674046","https://openalex.org/W2896266951","https://openalex.org/W2897277736","https://openalex.org/W2952258850","https://openalex.org/W2962687116","https://openalex.org/W2962835968","https://openalex.org/W2963001155","https://openalex.org/W2963084334","https://openalex.org/W2963816519","https://openalex.org/W2963993701","https://openalex.org/W2964172739","https://openalex.org/W3102751229","https://openalex.org/W3121926921","https://openalex.org/W4230809916","https://openalex.org/W6628877408","https://openalex.org/W6629842857","https://openalex.org/W6634288218","https://openalex.org/W6637373629","https://openalex.org/W6638273328","https://openalex.org/W6675365184","https://openalex.org/W6677764299","https://openalex.org/W6684191040","https://openalex.org/W6737845821","https://openalex.org/W6738445818","https://openalex.org/W6752001723","https://openalex.org/W6753653501","https://openalex.org/W6754520643","https://openalex.org/W6754615192","https://openalex.org/W6812174136"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1,112],"prediction":[2],"is":[3,43,71,105],"vital":[4],"for":[5,140],"transportation":[6],"systems.":[7],"Generally":[8],"we":[9,89],"can":[10,119,135],"divide":[11],"pedestrian":[12,33],"behavior":[13],"modeling":[14],"into":[15],"two":[16],"categories,":[17],"i.e.,":[18],"knowledge-driven":[19],"and":[20,28,67,107,117,126,146],"data-driven.":[21],"The":[22,40,69],"former":[23],"might":[24],"bring":[25],"expert":[26],"bias,":[27],"it":[29],"sometimes":[30],"generates":[31],"unrealistic":[32],"movement":[34],"due":[35],"to":[36,63,91,94,109],"unnecessary":[37],"repulsive":[38],"forces.":[39],"latter":[41],"approach":[42],"popular":[44],"nowadays":[45],"but":[46],"most":[47],"existing":[48],"neural":[49],"networks,":[50,58],"including":[51],"fully":[52],"connected":[53],"long":[54],"short-term":[55],"memory":[56],"(LSTM)":[57],"use":[59,92],"a":[60,83,102,141],"1D":[61],"vector":[62],"model":[64],"their":[65],"input":[66],"state.":[68],"shortcoming":[70],"that":[72,131],"these":[73],"works":[74],"cannot":[75],"learn":[76,120],"spatial":[77],"information":[78],"about":[79],"pedestrians,":[80],"especially":[81],"in":[82,144],"dense":[84,142],"crowd.":[85],"To":[86],"tackle":[87],"this,":[88],"propose":[90],"tensors":[93],"represent":[95],"essential":[96],"environment":[97],"features":[98],"of":[99],"pedestrians.":[100],"Accordingly,":[101],"convolutional":[103],"LSTM":[104],"designed":[106],"deepened":[108],"predict":[110],"spatiotemporal":[111,122],"sequences.":[113],"As":[114],"the":[115,132],"tensor":[116],"convolution":[118],"better":[121],"interactions":[123],"among":[124],"pedestrians":[125],"environments,":[127],"experimental":[128],"results":[129],"show":[130],"proposed":[133],"network":[134],"estimate":[136],"more":[137],"realistic":[138],"trajectories":[139],"crowd":[143],"evacuation":[145],"counterflow.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":29},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}