{"id":"https://openalex.org/W4401726056","doi":"https://doi.org/10.1109/tvt.2024.3437412","title":"Urban Vehicle Trajectory Generation Based on Generative Adversarial Imitation Learning","display_name":"Urban Vehicle Trajectory Generation Based on Generative Adversarial Imitation Learning","publication_year":2024,"publication_date":"2024-08-21","ids":{"openalex":"https://openalex.org/W4401726056","doi":"https://doi.org/10.1109/tvt.2024.3437412"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2024.3437412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3437412","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/A5003963034","display_name":"Min Wang","orcid":"https://orcid.org/0000-0002-6043-5191"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Wang","raw_affiliation_strings":["School of Computer Science, Central China Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-6043-5191","affiliations":[{"raw_affiliation_string":"School of Computer Science, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077574591","display_name":"Jianqun Cui","orcid":"https://orcid.org/0000-0003-1447-8761"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqun Cui","raw_affiliation_strings":["School of Computer Science, Central China Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-1447-8761","affiliations":[{"raw_affiliation_string":"School of Computer Science, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014151234","display_name":"Yew Wee Wong","orcid":null},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yew Wee Wong","raw_affiliation_strings":["School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102903734","display_name":"Yanan Chang","orcid":"https://orcid.org/0000-0001-7101-5750"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan Chang","raw_affiliation_strings":["School of Computer Science, Central China Normal University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108047844","display_name":"Libing Wu","orcid":"https://orcid.org/0000-0001-9897-1953"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libing Wu","raw_affiliation_strings":["School of Cyber Science and Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9897-1953","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080328538","display_name":"Jiong Jin","orcid":"https://orcid.org/0000-0002-0306-2691"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiong Jin","raw_affiliation_strings":["School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-0306-2691","affiliations":[{"raw_affiliation_string":"School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I57093077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4707,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54772161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"73","issue":"12","first_page":"18237","last_page":"18249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9672999978065491,"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":0.9672999978065491,"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/T12290","display_name":"Human Motion and Animation","score":0.9581000208854675,"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9093999862670898,"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":0.7217594385147095},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6538494825363159},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5142056941986084},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.5129658579826355},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.47100841999053955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43643486499786377},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36544960737228394},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11768278479576111},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1017257571220398}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7217594385147095},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6538494825363159},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5142056941986084},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5129658579826355},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.47100841999053955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43643486499786377},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36544960737228394},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11768278479576111},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1017257571220398},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2024.3437412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3437412","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G186019246","display_name":null,"funder_award_id":"62402193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2220268943","display_name":null,"funder_award_id":"62,272,189","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7147304087","display_name":null,"funder_award_id":"62372206","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"},{"id":"https://openalex.org/F4320324638","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W6346207","https://openalex.org/W1607069473","https://openalex.org/W2005088464","https://openalex.org/W2110922380","https://openalex.org/W2126270075","https://openalex.org/W2317389958","https://openalex.org/W2395594804","https://openalex.org/W2580495915","https://openalex.org/W2604382266","https://openalex.org/W2768629321","https://openalex.org/W2794743921","https://openalex.org/W2802384791","https://openalex.org/W2883955855","https://openalex.org/W2903383997","https://openalex.org/W2906647810","https://openalex.org/W2942278707","https://openalex.org/W2945991855","https://openalex.org/W2962787969","https://openalex.org/W2963169753","https://openalex.org/W2963219401","https://openalex.org/W2963815829","https://openalex.org/W2978273467","https://openalex.org/W2991318568","https://openalex.org/W2997207453","https://openalex.org/W3008653537","https://openalex.org/W3019298229","https://openalex.org/W3031124855","https://openalex.org/W3034269714","https://openalex.org/W3037624214","https://openalex.org/W3038088335","https://openalex.org/W3091902532","https://openalex.org/W3131404656","https://openalex.org/W3138984732","https://openalex.org/W3155986819","https://openalex.org/W3157716083","https://openalex.org/W3191742182","https://openalex.org/W4200483037","https://openalex.org/W4210444794","https://openalex.org/W4246659208","https://openalex.org/W4281686250","https://openalex.org/W4285193415","https://openalex.org/W4378531115","https://openalex.org/W6638018090","https://openalex.org/W6639086533","https://openalex.org/W6640443443","https://openalex.org/W6674884181","https://openalex.org/W6718092244","https://openalex.org/W6745347688","https://openalex.org/W6753207554","https://openalex.org/W6779639970","https://openalex.org/W6797004501"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2502115930"],"abstract_inverted_index":{"With":[0],"the":[1,7,72,82,122,126,131],"rapid":[2],"development":[3],"of":[4,9,75,84],"smart":[5],"cities,":[6],"collection":[8],"vehicle":[10,59,77,104,141],"trajectory":[11,33,60,85,160],"data":[12],"through":[13],"sensors":[14],"has":[15],"increased":[16],"significantly.":[17],"While":[18],"many":[19],"studies":[20],"have":[21],"utilized":[22],"calibrated":[23],"physical":[24],"car-following":[25],"models":[26,81],"(CFM)":[27],"and":[28,110,117,148,156],"machine":[29],"learning":[30,54],"techniques":[31],"for":[32,57],"prediction,":[34],"these":[35],"approaches":[36,158],"often":[37],"falter":[38],"in":[39,140,159],"complex,":[40],"dynamic":[41],"traffic":[42],"scenarios.":[43],"Addressing":[44],"this":[45,47],"gap,":[46],"paper":[48],"introducesPS-TrajGAIL,":[49],"a":[50,67,88,100,111],"generative":[51,68],"adversarial":[52],"imitation":[53,96],"framework":[55,80],"tailored":[56],"urban":[58,76],"generation.":[61,161],"Contrary":[62],"to":[63,70,106],"conventional":[64],"discriminative":[65],"models,PS-TrajGAILemploys":[66],"model":[69],"capture":[71],"inherent":[73],"distribution":[74],"trajectories.":[78,119],"This":[79],"tasks":[83],"generation":[86],"as":[87],"partially":[89],"observable":[90],"Markov":[91],"decision":[92],"process":[93],"based":[94],"on":[95,145],"learning.PS-TrajGAIL\u2019s":[97],"architecture":[98],"features":[99],"generator,":[101],"which":[102],"simulates":[103],"behavior":[105],"produce":[107],"synthetic":[108,147],"trajectories,":[109],"discriminator":[112],"that":[113],"distinguishes":[114],"between":[115],"authentic":[116],"generated":[118],"In":[120],"addition,":[121],"driving":[123],"policy":[124],"within":[125],"generator":[127],"is":[128],"fine-tuned":[129],"using":[130],"Trust":[132],"Region":[133],"Policy":[134],"Optimization":[135],"(TRPO)":[136],"algorithm,":[137],"ensuring":[138],"safety":[139],"driving.":[142],"Experimental":[143],"evaluations":[144],"both":[146],"real-world":[149],"datasets":[150],"highlight":[151],"thatPS-TrajGAILnotably":[152],"surpasses":[153],"existing":[154],"baselines":[155],"state-of-the-art":[157]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
