{"id":"https://openalex.org/W4414116828","doi":"https://doi.org/10.1109/tits.2025.3605735","title":"TP-GLIF: Trajectory Prediction of Surrounding Vehicles in Unsignalized Roundabouts Based on Global-Local History Information Fusion","display_name":"TP-GLIF: Trajectory Prediction of Surrounding Vehicles in Unsignalized Roundabouts Based on Global-Local History Information Fusion","publication_year":2025,"publication_date":"2025-09-11","ids":{"openalex":"https://openalex.org/W4414116828","doi":"https://doi.org/10.1109/tits.2025.3605735"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3605735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3605735","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/A5073601161","display_name":"Yun Ye","orcid":"https://orcid.org/0009-0008-0499-1354"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingnan Ye","raw_affiliation_strings":["Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0008-0499-1354","affiliations":[{"raw_affiliation_string":"Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451081","display_name":"Chunyan Wang","orcid":"https://orcid.org/0000-0002-3913-8192"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyan Wang","raw_affiliation_strings":["Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3913-8192","affiliations":[{"raw_affiliation_string":"Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031097117","display_name":"Wanzhong Zhao","orcid":"https://orcid.org/0009-0008-8651-6011"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanzhong Zhao","raw_affiliation_strings":["Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0008-8651-6011","affiliations":[{"raw_affiliation_string":"Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100335253","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0002-1857-5406"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-1857-5406","affiliations":[{"raw_affiliation_string":"Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051684117","display_name":"Yujie Zhang","orcid":"https://orcid.org/0009-0001-4184-6892"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Zhang","raw_affiliation_strings":["Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0001-4184-6892","affiliations":[{"raw_affiliation_string":"Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.4787,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63741024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"26","issue":"12","first_page":"23055","last_page":"23068"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976000189781189,"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":0.9976000189781189,"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":0.9954000115394592,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.7634000182151794},{"id":"https://openalex.org/keywords/roundabout","display_name":"Roundabout","score":0.5697000026702881},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.48489999771118164},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.44350001215934753},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.4390000104904175},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.42559999227523804},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.40610000491142273},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.39899998903274536},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38929998874664307}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7634000182151794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6297000050544739},{"id":"https://openalex.org/C109157449","wikidata":"https://www.wikidata.org/wiki/Q7371221","display_name":"Roundabout","level":2,"score":0.5697000026702881},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4390000104904175},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.42559999227523804},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3312000036239624},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.296999990940094},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27549999952316284},{"id":"https://openalex.org/C29406490","wikidata":"https://www.wikidata.org/wiki/Q1420659","display_name":"Fisher information","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.26260000467300415},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.2554999887943268},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3605735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3605735","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/G2224966717","display_name":null,"funder_award_id":"52372390","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7908308864","display_name":null,"funder_award_id":"U 24A20199","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":31,"referenced_works":["https://openalex.org/W1652644688","https://openalex.org/W2101372905","https://openalex.org/W2911286998","https://openalex.org/W2963001155","https://openalex.org/W2985871763","https://openalex.org/W2989851631","https://openalex.org/W2996287921","https://openalex.org/W3034384034","https://openalex.org/W3084512379","https://openalex.org/W3114563362","https://openalex.org/W3128196514","https://openalex.org/W3154823968","https://openalex.org/W3186771276","https://openalex.org/W3187677057","https://openalex.org/W3202283237","https://openalex.org/W3216996634","https://openalex.org/W4200202261","https://openalex.org/W4210389721","https://openalex.org/W4210511162","https://openalex.org/W4214895168","https://openalex.org/W4286358580","https://openalex.org/W4320727243","https://openalex.org/W4320802711","https://openalex.org/W4327808993","https://openalex.org/W4364856178","https://openalex.org/W4378195072","https://openalex.org/W4386078146","https://openalex.org/W4390932584","https://openalex.org/W4406657791","https://openalex.org/W4409683113","https://openalex.org/W4411023111"],"related_works":["https://openalex.org/W2093826578","https://openalex.org/W4294237266","https://openalex.org/W3195565206","https://openalex.org/W647040144","https://openalex.org/W2558143469","https://openalex.org/W2176704059","https://openalex.org/W4320802711","https://openalex.org/W2376500391","https://openalex.org/W2355579697","https://openalex.org/W4360871138"],"abstract_inverted_index":{"For":[0],"intelligent":[1],"vehicles,":[2,53],"accurate":[3,229],"prediction":[4,61,145,181,231],"of":[5,8,51,59,84,199],"the":[6,57,82,129,134,192,197,219],"trajectories":[7,195],"surrounding":[9,52,85,193],"vehicles":[10,86],"is":[11,109,116,160,177,188],"an":[12],"important":[13],"basis":[14],"for":[15,80],"identifying":[16],"potential":[17],"risks":[18],"in":[19,87,213,232],"advance":[20],"and":[21,31,37,46,62,67,104,111,136,162,208,236,241],"making":[22],"optimal":[23],"decisions.":[24],"However,":[25],"unsignalized":[26,88],"roundabouts":[27,89],"have":[28],"multiple":[29],"entrance":[30],"exit":[32],"ramps":[33],"with":[34],"uncertain":[35],"angles":[36],"numbers,":[38],"which":[39,54],"leads":[40],"to":[41,118,124,143,179,190,217],"more":[42,47],"diverse":[43,209],"driving":[44,125,173,210],"intentions":[45],"complex":[48,200,204],"multi-vehicle":[49,157,205],"interactions":[50],"significantly":[55],"reduces":[56],"accuracy":[58],"trajectory":[60,83,230],"even":[63],"causes":[64],"wrong":[65],"decisions":[66],"serious":[68],"collision":[69],"accidents.":[70],"To":[71],"this":[72,74],"end,":[73],"paper":[75],"innovatively":[76],"proposes":[77],"a":[78,98,101,112,148,151,163],"method":[79],"predicting":[81],"based":[90],"on":[91,133],"global-local":[92],"historical":[93],"information":[94,107,121],"fusion":[95],"(TP-GLIF).":[96],"From":[97,147],"global":[99],"perspective,":[100,150],"scene-adaptive":[102],"dynamic":[103,135,153],"static":[105,137],"feature":[106],"encoder":[108,159],"constructed,":[110,161],"multi-head":[113],"attention":[114,156],"mechanism":[115],"introduced":[117],"capture":[119],"environmental":[120],"closely":[122],"related":[123],"intention,":[126],"so":[127],"that":[128,139,225],"model":[130],"always":[131],"focuses":[132],"features":[138,207,212],"are":[140],"most":[141],"beneficial":[142],"improving":[144],"accuracy.":[146],"local":[149],"novel":[152,164],"heterogeneous":[154],"graph":[155],"interaction":[158,206],"hierarchical":[165],"Gaussian":[166],"mixture":[167],"model-hidden":[168],"Markov":[169],"model-support":[170],"vector":[171],"machine":[172],"intention":[174,211],"recognition":[175],"algorithm":[176],"designed":[178,189],"guide":[180],"decoding.":[182],"A":[183],"long":[184],"short-term":[185],"decoder":[186],"LS-GRU":[187],"decode":[191],"vehicle":[194],"under":[196],"influence":[198],"road":[201],"structure":[202],"features,":[203],"different":[214,233],"time":[215],"periods":[216],"reduce":[218],"cumulative":[220],"error.":[221],"Experimental":[222],"results":[223],"show":[224],"TP-GLIF":[226],"can":[227],"achieve":[228],"roundabout":[234],"scenes,":[235],"has":[237],"good":[238],"computational":[239],"efficiency":[240],"generalization":[242],"ability.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}