{"id":"https://openalex.org/W4408564192","doi":"https://doi.org/10.1109/tits.2025.3549744","title":"Vehicle Trajectory Prediction by Integrating Data-Driven and Knowledge-Guided Technique","display_name":"Vehicle Trajectory Prediction by Integrating Data-Driven and Knowledge-Guided Technique","publication_year":2025,"publication_date":"2025-03-18","ids":{"openalex":"https://openalex.org/W4408564192","doi":"https://doi.org/10.1109/tits.2025.3549744"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3549744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3549744","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/A5003318831","display_name":"Jinghua Guo","orcid":"https://orcid.org/0000-0001-9123-6817"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinghua Guo","raw_affiliation_strings":["Pen-Tung Sah Institute of Micro-Nano Science and Technology and the Institute of Artificial Intelligence, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Pen-Tung Sah Institute of Micro-Nano Science and Technology and the Institute of Artificial Intelligence, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010547906","display_name":"Zhifei He","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifei He","raw_affiliation_strings":["Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102533391","display_name":"Huinian Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huinian Wang","raw_affiliation_strings":["Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100696194","display_name":"Jingyao Wang","orcid":"https://orcid.org/0000-0003-1013-5374"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyao Wang","raw_affiliation_strings":["School of Aerospace Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031855986","display_name":"Keqiang Li","orcid":"https://orcid.org/0000-0002-9333-7416"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keqiang Li","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5003318831"],"corresponding_institution_ids":["https://openalex.org/I75867142"],"apc_list":null,"apc_paid":null,"fwci":6.1966,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.96083,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"26","issue":"5","first_page":"5888","last_page":"5898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.982200026512146,"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":0.982200026512146,"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":0.9508000016212463,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9136999845504761,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/trajectory","display_name":"Trajectory","score":0.7903749942779541},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5329298377037048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37669143080711365},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10210677981376648}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7903749942779541},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5329298377037048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37669143080711365},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10210677981376648},{"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.2025.3549744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3549744","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":[],"awards":[{"id":"https://openalex.org/G2213368870","display_name":null,"funder_award_id":"62473323","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3560361723","display_name":null,"funder_award_id":"52372419","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6266362482","display_name":null,"funder_award_id":"61803319","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G904980392","display_name":null,"funder_award_id":"KFY2206","funder_id":"https://openalex.org/F4320326925","funder_display_name":"State Key Laboratory of Automotive Safety and Energy"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326925","display_name":"State Key Laboratory of Automotive Safety and Energy","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1592601589","https://openalex.org/W2784715585","https://openalex.org/W2803184913","https://openalex.org/W2883602772","https://openalex.org/W2913159621","https://openalex.org/W2963309363","https://openalex.org/W2963906196","https://openalex.org/W2963914175","https://openalex.org/W2969040309","https://openalex.org/W2997958396","https://openalex.org/W3013376041","https://openalex.org/W3016826426","https://openalex.org/W3046791050","https://openalex.org/W3128196514","https://openalex.org/W3131831820","https://openalex.org/W3136121014","https://openalex.org/W3145470822","https://openalex.org/W3194668998","https://openalex.org/W3205464992","https://openalex.org/W4226239849","https://openalex.org/W4320024127","https://openalex.org/W4323568099","https://openalex.org/W4402568881","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4323768008"],"abstract_inverted_index":{"In":[0,52,148],"the":[1,7,68,74,98,121,140,174,177,181,184,188,195,198,218,223,227],"context":[2],"of":[3,9,70,83,100,115,139,176,183,205,222,229],"autonomous":[4,15],"driving,":[5],"acquiring":[6],"trajectories":[8,133],"surrounding":[10,77],"vehicles":[11,16,84],"in":[12,21,85,203],"advance":[13],"by":[14,150],"is":[17,64,104,118,166,191],"a":[18,49,92,144,169],"crucial":[19],"factor":[20],"ensuring":[22],"high-level":[23],"road":[24],"safety.":[25],"While":[26],"trajectory":[27,61,94,231],"prediction":[28,62,95,126,199],"methods":[29],"based":[30,161],"on":[31,162,194],"deep":[32],"learning":[33],"have":[34,143],"achieved":[35],"promising":[36],"results,":[37],"these":[38],"data-driven":[39,101],"models":[40],"lack":[41],"interpretability":[42,182,221],"and":[43,73,88,102,109,134,179,197,207,220,225],"transparency,":[44],"making":[45],"their":[46],"reliable":[47],"use":[48],"significant":[50],"challenge.":[51],"this":[53,137],"paper,":[54],"firstly,":[55],"an":[56,157],"intention-aware":[57,122],"spatial-temporal":[58,123],"attention":[59,124],"network-based":[60],"model":[63,127,178,190],"constructed,":[65],"which":[66],"considers":[67],"coupling":[69],"driving":[71],"intention":[72],"interaction":[75],"with":[76],"vehicles,":[78],"extracts":[79],"important":[80],"feature":[81],"information":[82],"both":[86,107],"temporal":[87],"spatial":[89],"dimensions.":[90],"Secondly,":[91],"vehicle":[93,116],"method":[96],"via":[97],"integration":[99],"knowledge-guided":[103],"proposed,":[105],"considering":[106],"hard":[108,113],"soft":[110,170],"constraints.":[111],"A":[112],"constraint":[114,164,171],"kinematics":[117],"incorporated":[119],"into":[120],"network":[125,141],"to":[128,135,154,172],"generate":[129],"physically":[130],"feasible":[131],"predicted":[132],"make":[136],"part":[138],"structure":[142],"human-understandable":[145],"physical":[146],"meaning.":[147],"addition,":[149],"leveraging":[151],"knowledge":[152,163,214],"related":[153],"traffic":[155],"rules,":[156],"auxiliary":[158],"loss":[159],"function":[160],"penalties":[165],"designed":[167],"as":[168],"optimize":[173],"training":[175,185],"improve":[180,226],"process.":[186],"Finally,":[187],"proposed":[189],"experimentally":[192],"evaluated":[193],"datasets":[196],"results":[200,211],"are":[201],"analyzed":[202],"terms":[204],"reliability":[206,219],"accuracy.":[208],"The":[209],"experimental":[210],"demonstrate":[212],"that":[213],"guidance":[215],"effectively":[216],"enhance":[217],"prediction,":[224],"accuracy":[228],"long-term":[230],"prediction.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
