{"id":"https://openalex.org/W4413556355","doi":"https://doi.org/10.1109/tnse.2025.3602212","title":"MHTraj: A Multi-Domain Hybrid Graph Neural Network With Causal-Spatial Modeling for Multi-Agent Trajectory Prediction","display_name":"MHTraj: A Multi-Domain Hybrid Graph Neural Network With Causal-Spatial Modeling for Multi-Agent Trajectory Prediction","publication_year":2025,"publication_date":"2025-08-25","ids":{"openalex":"https://openalex.org/W4413556355","doi":"https://doi.org/10.1109/tnse.2025.3602212"},"language":"en","primary_location":{"id":"doi:10.1109/tnse.2025.3602212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2025.3602212","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"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 Network Science and Engineering","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/A5044075519","display_name":"Jiuyu Chen","orcid":"https://orcid.org/0000-0001-6718-4172"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiuyu Chen","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024824662","display_name":"Chun-Xiao Jia","orcid":"https://orcid.org/0000-0002-9792-3594"},"institutions":[{"id":"https://openalex.org/I4210141966","display_name":"China Academy of Railway Sciences","ror":"https://ror.org/051wv2j09","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210141966"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxiao Jia","raw_affiliation_strings":["Signal &amp; Communication Research Institute of China Academy of Railway Sciences Corporation Ltd., Beijing, China","Signal &amp; Communication Research Institute of China Academy of Railway Sciences Corporation Limited, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Signal &amp; Communication Research Institute of China Academy of Railway Sciences Corporation Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210141966"]},{"raw_affiliation_string":"Signal &amp; Communication Research Institute of China Academy of Railway Sciences Corporation Limited, Beijing, China","institution_ids":["https://openalex.org/I4210141966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014747872","display_name":"Wei Xie","orcid":"https://orcid.org/0000-0003-4984-6659"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Xie","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103113902","display_name":"Donglin Zhu","orcid":"https://orcid.org/0000-0003-2568-0412"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donglin Zhu","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034055615","display_name":"Xiaotao Shao","orcid":"https://orcid.org/0000-0003-0758-518X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotao Shao","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100674334","display_name":"Zhongli Wang","orcid":"https://orcid.org/0000-0002-3236-8219"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongli Wang","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044075519"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.9575,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78082372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"1786","last_page":"1799"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9947999715805054,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9947999715805054,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9384999871253967,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6566808223724365},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6284107565879822},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5432807207107544},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4494299292564392},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4296586215496063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4148847460746765},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25884708762168884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20702990889549255}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6566808223724365},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6284107565879822},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5432807207107544},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4494299292564392},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4296586215496063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4148847460746765},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25884708762168884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20702990889549255},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnse.2025.3602212","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2025.3602212","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"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 Network Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5586581773","display_name":null,"funder_award_id":"61573057","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1970206276","https://openalex.org/W2064675550","https://openalex.org/W2424778531","https://openalex.org/W2519586580","https://openalex.org/W2532516272","https://openalex.org/W2799059904","https://openalex.org/W2963001155","https://openalex.org/W3034634510","https://openalex.org/W3035096461","https://openalex.org/W3035339264","https://openalex.org/W3035574168","https://openalex.org/W3042505632","https://openalex.org/W3097237405","https://openalex.org/W3097402629","https://openalex.org/W3104079458","https://openalex.org/W3108262631","https://openalex.org/W3108908812","https://openalex.org/W3116651890","https://openalex.org/W3127663353","https://openalex.org/W3130052032","https://openalex.org/W3139491754","https://openalex.org/W3177765762","https://openalex.org/W3184258555","https://openalex.org/W3194018559","https://openalex.org/W3199505925","https://openalex.org/W3207304742","https://openalex.org/W4200078715","https://openalex.org/W4214593147","https://openalex.org/W4280497349","https://openalex.org/W4285106399","https://openalex.org/W4292794796","https://openalex.org/W4308080785","https://openalex.org/W4312305613","https://openalex.org/W4312517993","https://openalex.org/W4312580307","https://openalex.org/W4312731878","https://openalex.org/W4312750092","https://openalex.org/W4312893480","https://openalex.org/W4313041951","https://openalex.org/W4313196348","https://openalex.org/W4315926739","https://openalex.org/W4317385013","https://openalex.org/W4317772253","https://openalex.org/W4361029803","https://openalex.org/W4366351460","https://openalex.org/W4377030580","https://openalex.org/W4384271202","https://openalex.org/W4385326851","https://openalex.org/W4386071549","https://openalex.org/W4386075642","https://openalex.org/W4386076060","https://openalex.org/W4386101142","https://openalex.org/W4386474133","https://openalex.org/W4387592386","https://openalex.org/W4388452210","https://openalex.org/W4388543829","https://openalex.org/W4390037774","https://openalex.org/W4390872831","https://openalex.org/W4390874083","https://openalex.org/W4391092980","https://openalex.org/W4393148290","https://openalex.org/W4396830568","https://openalex.org/W4401415045","https://openalex.org/W4401506940","https://openalex.org/W4401863317","https://openalex.org/W4402816840","https://openalex.org/W4402816933","https://openalex.org/W4404096706","https://openalex.org/W4404177755","https://openalex.org/W4404439861","https://openalex.org/W4404769984","https://openalex.org/W4404820308","https://openalex.org/W4410636960"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W4248382324","https://openalex.org/W3023605104","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W2383578611","https://openalex.org/W2987583674"],"abstract_inverted_index":{"As":[0],"a":[1,83,91,117,131],"crucial":[2],"part":[3],"of":[4,17,25,105],"social":[5],"behavior":[6],"modeling,":[7],"multi-agent":[8],"trajectory":[9],"prediction":[10],"with":[11],"dynamic":[12],"interactions":[13,38],"has":[14],"become":[15],"one":[16],"the":[18,26,78,106,142,158,169,176],"core":[19,103],"technologies":[20],"for":[21,97,181],"unmanned":[22],"systems.":[23],"One":[24],"main":[27],"research":[28],"streams":[29],"is":[30,134,184],"to":[31,36,125,136],"leverage":[32],"relational":[33],"graph":[34,132],"Transformers":[35],"learn":[37],"among":[39],"agents,":[40],"as":[41],"this":[42,88,182],"method":[43,107,160],"demonstrates":[44],"superior":[45],"capability":[46],"in":[47,60,109],"capturing":[48],"implicit":[49],"features":[50],"and":[51,81,120,166],"modeling":[52],"complex":[53],"relationships.":[54],"However,":[55],"such":[56],"researches":[57],"fall":[58],"short":[59],"efficiently":[61],"utilizing":[62],"multi-domain":[63],"features,":[64],"consequently":[65],"being":[66],"constrained":[67],"by":[68,172],"spatial":[69,138],"attention":[70,124],"layers":[71],"that":[72,157],"hinder":[73],"accuracy":[74],"improvements.":[75],"To":[76],"address":[77],"above":[79],"limitations":[80],"achieve":[82],"more":[84],"lightweight":[85],"map-free":[86],"architecture,":[87],"work":[89,183],"introduces":[90],"Multi-domain":[92],"Hybrid":[93],"Graph":[94],"Transformer":[95,133],"(MHTraj)":[96],"predicting":[98],"multi-modal":[99],"future":[100],"trajectories.":[101],"The":[102,179],"insight":[104],"lies":[108],"its":[110],"well-designed":[111],"encoder,":[112],"which":[113],"enhances":[114],"inputs":[115],"via":[116],"frequency-domain":[118],"mixer":[119],"employs":[121],"causal":[122],"convolution":[123],"capture":[126],"global":[127],"temporal":[128],"information.":[129],"Furthermore,":[130],"incorporated":[135],"aggregate":[137],"relationships,":[139],"thereby":[140],"yielding":[141],"final":[143],"hybrid":[144],"features.":[145],"Extensive":[146],"experiments":[147],"on":[148,175],"4":[149],"real-world":[150],"datasets":[151],"(NBA,":[152],"ETH/UCY,":[153],"SDD,":[154],"nuScenes)":[155],"show":[156],"proposed":[159],"achieves":[161],"competitive":[162],"state-of-the-art":[163],"(SOTA)":[164],"performances,":[165],"meanwhile":[167],"reducing":[168],"parameter":[170],"count":[171],"nearly":[173],"50%":[174],"ETH/UCY":[177],"datasets.":[178],"code":[180],"available":[185],"at":[186],"<underline":[187],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[188],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><uri>https://github.com/iRobotVision/socialea-human</uri></u>.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
