{"id":"https://openalex.org/W4414908506","doi":"https://doi.org/10.1109/jiot.2025.3618612","title":"HSIGCN: Hierarchical Spatial Interaction Graph Convolutional Network Considering Group Behavior for Pedestrian Trajectory Prediction","display_name":"HSIGCN: Hierarchical Spatial Interaction Graph Convolutional Network Considering Group Behavior for Pedestrian Trajectory Prediction","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414908506","doi":"https://doi.org/10.1109/jiot.2025.3618612"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2025.3618612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3618612","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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":null,"display_name":"Bo Wang","orcid":"https://orcid.org/0009-0002-0006-8032"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0002-0006-8032","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087977761","display_name":"Chao Sun","orcid":"https://orcid.org/0000-0002-9324-0892"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Sun","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-9324-0892","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041609487","display_name":"Jianghao Leng","orcid":"https://orcid.org/0000-0002-3577-7990"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianghao Leng","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075191866","display_name":"Zhishuai Huang","orcid":"https://orcid.org/0009-0008-1615-9813"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhishuai Huang","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0008-1615-9813","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haoyu Li","orcid":"https://orcid.org/0009-0001-5494-0220"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Li","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0001-5494-0220","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077665511","display_name":"Zitong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zitong Chen","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0008-0860-6150","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22659569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"24","first_page":"53274","last_page":"53287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962999820709229,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9912999868392944,"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/T10370","display_name":"Traffic and Road Safety","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6826000213623047},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6607000231742859},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5716000199317932},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5217000246047974},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.430400013923645},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.4009000062942505},{"id":"https://openalex.org/keywords/collective-behavior","display_name":"Collective behavior","score":0.3190999925136566}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.796500027179718},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6826000213623047},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6607000231742859},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5217000246047974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43160000443458557},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3668000102043152},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.358599990606308},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33009999990463257},{"id":"https://openalex.org/C100339178","wikidata":"https://www.wikidata.org/wiki/Q2548752","display_name":"Collective behavior","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2780806968","wikidata":"https://www.wikidata.org/wiki/Q6045196","display_name":"Interaction model","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C38764148","wikidata":"https://www.wikidata.org/wiki/Q17098245","display_name":"Interaction information","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3618612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3618612","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2518234181","display_name":null,"funder_award_id":"2022YFB2503203","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8368601664","display_name":null,"funder_award_id":"2023B0909040001","funder_id":"https://openalex.org/F4320336742","funder_display_name":"Key Research and Development Program of Liaoning Province"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320336742","display_name":"Key Research and Development Program of Liaoning Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1967777429","https://openalex.org/W1970206276","https://openalex.org/W2089584121","https://openalex.org/W2131689832","https://openalex.org/W2134944993","https://openalex.org/W2157461671","https://openalex.org/W2167052694","https://openalex.org/W2424778531","https://openalex.org/W2532516272","https://openalex.org/W2801667201","https://openalex.org/W2905097561","https://openalex.org/W2908715333","https://openalex.org/W2911498565","https://openalex.org/W2941651142","https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W2964136016","https://openalex.org/W2964230007","https://openalex.org/W2991653934","https://openalex.org/W3035096461","https://openalex.org/W3097237405","https://openalex.org/W3097402629","https://openalex.org/W3109579921","https://openalex.org/W3114484401","https://openalex.org/W3117379804","https://openalex.org/W3157779442","https://openalex.org/W3177765762","https://openalex.org/W3184914355","https://openalex.org/W3209892694","https://openalex.org/W3214003911","https://openalex.org/W4200404607","https://openalex.org/W4206209964","https://openalex.org/W4226118181","https://openalex.org/W4312517993","https://openalex.org/W4313041951","https://openalex.org/W4318570434","https://openalex.org/W4367311040","https://openalex.org/W4383109004","https://openalex.org/W4384161746","https://openalex.org/W4390748047","https://openalex.org/W4399310871","https://openalex.org/W4399493458","https://openalex.org/W4399611007","https://openalex.org/W4400228460","https://openalex.org/W4401506940","https://openalex.org/W4401528885","https://openalex.org/W4404257886","https://openalex.org/W4405963838","https://openalex.org/W4406457627","https://openalex.org/W4406857610"],"related_works":[],"abstract_inverted_index":{"Pedestrian":[0],"trajectory":[1,19],"prediction":[2,20],"is":[3,44],"crucial":[4],"in":[5,78,102],"various":[6],"fields,":[7],"but":[8],"remains":[9],"challenging":[10],"due":[11],"to":[12,27,46,59,109,127,144,163,190],"complex":[13,75,198],"spatial":[14,52,110,199],"interactions.":[15,53,138,200],"While":[16],"existing":[17,140],"pedestrian":[18,193],"methods":[21,56,142],"show":[22],"promise,":[23],"they":[24,63],"often":[25,72],"fail":[26,143],"capture":[28],"these":[29],"dynamics":[30,77],"effectively.":[31],"To":[32],"address":[33],"this":[34],"limitation,":[35],"a":[36,65,82,129,165],"Hierarchical":[37],"Spatial":[38],"Interaction":[39],"Graph":[40],"Convolutional":[41],"Network":[42],"(HSIGCN)":[43],"proposed":[45,181],"handle":[47],"both":[48,125],"group":[49,61,69,84,103],"interactions":[50,70],"and":[51,71,96,136,160,175],"Although":[54],"previous":[55],"have":[57],"attempted":[58],"model":[60],"behaviors,":[62],"lack":[64],"comprehensive":[66],"consideration":[67],"of":[68,91,155],"oversimplify":[73],"the":[74,100,153,180],"social":[76,146],"groups.":[79],"HSIGCN":[80,122,149],"introduces":[81],"novel":[83],"interaction":[85,111],"mechanism":[86],"that":[87,179],"encompasses":[88],"four":[89],"types":[90],"interactions:":[92],"all-pedestrian,":[93],"intra-group,":[94],"out-group,":[95],"inter-group":[97],"interactions,":[98],"enhancing":[99],"expressiveness":[101],"behavior":[104],"prediction.":[105],"Furthermore,":[106],"current":[107],"approaches":[108,126],"sparsification":[112,131],"either":[113],"rely":[114],"solely":[115],"on":[116,119,173],"prior-based":[117,141,168],"or":[118],"learning-based":[120],"methods.":[121],"innovatively":[123],"combines":[124],"form":[128],"mixed":[130],"mechanism,":[132],"effectively":[133,196],"filtering":[134],"all-pedestrian":[135],"out-group":[137],"Additionally,":[139],"consider":[145],"factors":[147,162],"comprehensively.":[148],"takes":[150],"into":[151],"account":[152],"field":[154],"view":[156],"(FOV),":[157],"collision":[158],"awareness,":[159],"distance":[161],"establish":[164],"more":[166],"robust":[167],"sparse":[169],"function.":[170],"Experimental":[171],"results":[172],"ETH":[174],"UCY":[176],"datasets":[177],"demonstrate":[178],"method":[182],"significantly":[183],"outperforms":[184],"baseline":[185],"models,":[186],"showcasing":[187],"its":[188],"potential":[189],"accurately":[191],"predict":[192],"trajectories":[194],"by":[195],"handling":[197]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}