{"id":"https://openalex.org/W7117306608","doi":"https://doi.org/10.1109/tvt.2025.3648427","title":"Vehicle Trajectory Prediction Based on Dynamic Spatiotemporal Density-Adaptive Fusion in Autonomous Driving","display_name":"Vehicle Trajectory Prediction Based on Dynamic Spatiotemporal Density-Adaptive Fusion in Autonomous Driving","publication_year":2025,"publication_date":"2025-12-26","ids":{"openalex":"https://openalex.org/W7117306608","doi":"https://doi.org/10.1109/tvt.2025.3648427"},"language":null,"primary_location":{"id":"doi:10.1109/tvt.2025.3648427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3648427","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5100784555","display_name":"Zhirun Li","orcid":"https://orcid.org/0009-0007-0231-1821"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilong Li","raw_affiliation_strings":["School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0006-9161-3954","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121313090","display_name":"Qiang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Liu","raw_affiliation_strings":["School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6943-1093","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037808224","display_name":"DingLi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210153682","display_name":"Intelligent Health (United Kingdom)","ror":"https://ror.org/0576zak10","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210153682"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dingli Li","raw_affiliation_strings":["CICT Connected and Intelligent Technologies Company, Ltd, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CICT Connected and Intelligent Technologies Company, Ltd, Chongqing, China","institution_ids":["https://openalex.org/I4210153682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113895333","display_name":"J. Zhu","orcid":"https://orcid.org/0009-0000-7562-3665"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinglong Zhu","raw_affiliation_strings":["School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0008-0055-9388","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077452531","display_name":"Zhangzhen Zhao","orcid":"https://orcid.org/0009-0002-3472-4851"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangzhen Zhao","raw_affiliation_strings":["School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0002-3472-4851","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090228481","display_name":"Zikai Yao","orcid":"https://orcid.org/0000-0003-1327-2366"},"institutions":[{"id":"https://openalex.org/I4210156893","display_name":"Guangdong Inspection and Quarantine Technology Center (China)","ror":"https://ror.org/059b2sn04","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156893"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zikai Yao","raw_affiliation_strings":["IQTC, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1327-2366","affiliations":[{"raw_affiliation_string":"IQTC, Guangzhou, China","institution_ids":["https://openalex.org/I4210156893"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086411702","display_name":"Q LI","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-7930-2145","affiliations":[{"raw_affiliation_string":"School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39124187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"75","issue":"6","first_page":"9448","last_page":"9461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.7730000019073486,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.7730000019073486,"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/T10524","display_name":"Traffic control and management","score":0.07989999651908875,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.07000000029802322,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.796999990940094},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.5824000239372253},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.47440001368522644},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.4675000011920929},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.42590001225471497},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40779998898506165},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.38929998874664307}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.796999990940094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6761999726295471},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.5824000239372253},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.4675000011920929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.436599999666214},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.42590001225471497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.3246999979019165},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29820001125335693},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C51675839","wikidata":"https://www.wikidata.org/wiki/Q1665681","display_name":"Intelligent Network","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2025.3648427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3648427","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"complex":[1],"driving":[2,110],"environments,":[3],"accurately":[4],"predicting":[5],"vehicle":[6,71],"trajectories":[7],"is":[8],"crucial":[9],"for":[10],"the":[11,30,42,49,145,160],"safe":[12],"operation":[13],"of":[14,32,162],"intelligent":[15],"vehicles.":[16],"This":[17],"paper":[18],"introduces":[19],"a":[20,61,68],"Dynamic":[21],"Spatiotemporal":[22],"Density-Adaptive":[23],"Fusion":[24],"Network":[25],"(DSDAF)":[26],"designed":[27],"to":[28,53,75],"address":[29],"challenges":[31],"multi-modal":[33],"trajectory":[34,86],"prediction":[35,73,91],"in":[36,152],"dynamic":[37,56,62,123],"traffic":[38,78,94],"scenarios.":[39],"To":[40],"capture":[41],"spatiotemporal":[43],"dependencies":[44],"between":[45],"vehicles,":[46],"we":[47,97],"utilize":[48],"multi-head":[50],"attention":[51,124],"mechanism":[52,65],"model":[54,127],"their":[55],"interaction.":[57],"We":[58],"further":[59,158],"propose":[60,98],"density-aware":[63],"adaptive":[64,90],"that":[66,144],"employs":[67],"transformer-based":[69],"local":[70],"density":[72],"network":[74],"quantify":[76],"future":[77],"states":[79],"and":[80,114,122,133],"dynamically":[81],"integrate":[82],"them":[83],"with":[84],"historical":[85],"information,":[87],"thereby":[88],"enabling":[89],"under":[92],"real-time":[93],"conditions.":[95],"Additionally,":[96],"an":[99],"interpretable":[100],"decoder":[101],"architecture":[102],"based":[103],"on":[104,139],"Kolmogorov-Arnold":[105],"Networks":[106],"(KAN),":[107],"which":[108],"decomposes":[109],"behaviors":[111],"into":[112],"lateral":[113],"longitudinal":[115],"components.":[116],"By":[117],"leveraging":[118],"learnable":[119],"activation":[120],"functions":[121],"mechanisms,":[125],"our":[126],"generates":[128],"more":[129],"accurate":[130],"intention":[131],"representations":[132],"multimodal":[134],"trajectories.":[135],"Extensive":[136],"experiments":[137],"conducted":[138],"two":[140],"real-world":[141],"datasets":[142],"demonstrate":[143],"proposed":[146],"method":[147],"outperforms":[148],"state-of-the-art":[149],"algorithms,":[150],"particularly":[151],"long-term":[153],"predictions,":[154],"while":[155],"ablation":[156],"studies":[157],"verify":[159],"effectiveness":[161],"each":[163],"component.":[164]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-12-26T00:00:00"}
