{"id":"https://openalex.org/W4400111396","doi":"https://doi.org/10.1109/tits.2024.3419037","title":"Research on Vehicle Trajectory Prediction Methods in Urban Main Road Scenarios","display_name":"Research on Vehicle Trajectory Prediction Methods in Urban Main Road Scenarios","publication_year":2024,"publication_date":"2024-06-28","ids":{"openalex":"https://openalex.org/W4400111396","doi":"https://doi.org/10.1109/tits.2024.3419037"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3419037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3419037","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/A5010101374","display_name":"Sumin Zhang","orcid":"https://orcid.org/0000-0002-4860-0019"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sumin Zhang","raw_affiliation_strings":["National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-4860-0019","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033009482","display_name":"Ri Bai","orcid":"https://orcid.org/0009-0003-1106-3031"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ri Bai","raw_affiliation_strings":["National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0003-1106-3031","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101569756","display_name":"Rui He","orcid":"https://orcid.org/0000-0002-4288-5842"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui He","raw_affiliation_strings":["National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-4288-5842","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040412645","display_name":"Zhiwei Meng","orcid":"https://orcid.org/0000-0002-4770-6698"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Meng","raw_affiliation_strings":["National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005447553","display_name":"Yupeng Chang","orcid":"https://orcid.org/0009-0007-7068-0864"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yupeng Chang","raw_affiliation_strings":["National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0007-7068-0864","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032509762","display_name":"Yongshuai Zhi","orcid":"https://orcid.org/0000-0003-3512-7805"},"institutions":[{"id":"https://openalex.org/I4210127843","display_name":"First Automotive Works (China)","ror":"https://ror.org/0353t4m91","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongshuai Zhi","raw_affiliation_strings":["FAW Jiefang Qingdao Automotive Company Ltd., Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-3512-7805","affiliations":[{"raw_affiliation_string":"FAW Jiefang Qingdao Automotive Company Ltd., Qingdao, China","institution_ids":["https://openalex.org/I4210127843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101612761","display_name":"Ning Sun","orcid":"https://orcid.org/0000-0001-5750-3555"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Sun","raw_affiliation_strings":["College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5010101374"],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":1.5223,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80697244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"25","issue":"11","first_page":"16392","last_page":"16408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9625999927520752,"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":0.9625999927520752,"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/T14270","display_name":"Simulation and Modeling Applications","score":0.9246000051498413,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7666723728179932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48519256711006165},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.42667311429977417},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.4016788601875305},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.34209853410720825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2753041684627533},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.27518850564956665},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08348673582077026}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7666723728179932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48519256711006165},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.42667311429977417},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4016788601875305},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.34209853410720825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2753041684627533},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.27518850564956665},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08348673582077026},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3419037","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3419037","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":[{"score":0.75,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1978529738","https://openalex.org/W2022508996","https://openalex.org/W2064675550","https://openalex.org/W2116341502","https://openalex.org/W2157331557","https://openalex.org/W2306644740","https://openalex.org/W2343381408","https://openalex.org/W2424778531","https://openalex.org/W2592864539","https://openalex.org/W2594990650","https://openalex.org/W2607296803","https://openalex.org/W2618530766","https://openalex.org/W2766836212","https://openalex.org/W2784715585","https://openalex.org/W2883602772","https://openalex.org/W2905385096","https://openalex.org/W2932960505","https://openalex.org/W2955189650","https://openalex.org/W2963309363","https://openalex.org/W2963548793","https://openalex.org/W2963906196","https://openalex.org/W2963945905","https://openalex.org/W2964015378","https://openalex.org/W2967177252","https://openalex.org/W2971323980","https://openalex.org/W2985871763","https://openalex.org/W2989851631","https://openalex.org/W3005048145","https://openalex.org/W3034722190","https://openalex.org/W3090789587","https://openalex.org/W3104946437","https://openalex.org/W3112335585","https://openalex.org/W3116651890","https://openalex.org/W3201955064","https://openalex.org/W3204875639","https://openalex.org/W4286008117","https://openalex.org/W4297733535","https://openalex.org/W4312883633","https://openalex.org/W4323565827","https://openalex.org/W4381332009","https://openalex.org/W4383172002","https://openalex.org/W4385245566","https://openalex.org/W4388543829","https://openalex.org/W4392207805","https://openalex.org/W4402916169","https://openalex.org/W6734394903","https://openalex.org/W6782468546","https://openalex.org/W6850358656"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0],"the":[1,11,29,32,45,88,101,106,110,114,120,181],"autonomous":[2,19],"driving":[3,35],"realm,":[4],"it":[5],"is":[6],"crucial":[7],"to":[8,27,61,83,99,124],"accurately":[9],"predict":[10,28],"trajectory":[12,30,182],"of":[13,31,48,105,132,165,172],"other":[14,159],"traffic":[15],"vehicles":[16],"around":[17],"an":[18,79],"vehicle.":[20,107],"This":[21],"paper":[22],"proposes":[23],"a":[24,67,130],"novel":[25],"scheme":[26],"target":[33],"vehicle":[34,52,63],"on":[36,51,113],"urban":[37,166],"main":[38,167],"roads":[39],"efficiently":[40],"and":[41,93,119,139],"accurately.":[42],"Inspired":[43],"by":[44],"substantial":[46],"impact":[47],"road":[49,168],"geometry":[50],"trajectory,":[53],"we":[54,77],"delve":[55],"into":[56],"three":[57],"feature":[58],"input":[59],"methods":[60,161],"encode":[62],"features.":[64,74,91],"We":[65,108],"integrate":[66],"multi-head":[68],"attention":[69,80,95],"mechanism":[70,82],"for":[71],"weighting":[72],"map":[73,85],"Following":[75],"this,":[76],"utilize":[78],"gating":[81],"merge":[84],"features":[86,104],"with":[87],"vehicle\u2019s":[89],"dynamic":[90],"Spatial":[92],"temporal":[94],"mechanisms":[96],"are":[97],"employed":[98],"extract":[100],"spatial-temporal":[102],"interaction":[103],"evaluate":[109],"proposed":[111,127],"method":[112,153],"Argoverse":[115],"Motion":[116],"Prediction":[117],"dataset":[118],"INTERACTION":[121],"dataset.":[122],"Compared":[123],"VectorNet,":[125],"our":[126,152,176],"model":[128,177],"achieves":[129,154],"reduction":[131],"10.8%":[133],"in":[134,141,162,175],"Average":[135],"Displacement":[136,143],"Error":[137,144],"(ADE)":[138],"14.8%":[140],"Final":[142],"(FDE),":[145],"respectively.":[146],"The":[147,170],"experimental":[148],"results":[149],"show":[150],"that":[151],"better":[155],"prediction":[156,183],"performance":[157],"than":[158],"benchmark":[160],"various":[163,173],"types":[164],"scenarios.":[169],"designs":[171],"modules":[174],"can":[178],"effectively":[179],"improve":[180],"model\u2019s":[184],"performance.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}