{"id":"https://openalex.org/W4412939564","doi":"https://doi.org/10.1109/tits.2025.3592741","title":"TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework With Group-Based Monte Carlo Tree Search","display_name":"TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework With Group-Based Monte Carlo Tree Search","publication_year":2025,"publication_date":"2025-08-04","ids":{"openalex":"https://openalex.org/W4412939564","doi":"https://doi.org/10.1109/tits.2025.3592741"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3592741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3592741","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/A5068874919","display_name":"Ze Fu","orcid":"https://orcid.org/0000-0002-1060-8445"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ze Fu","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056126166","display_name":"Licheng Wen","orcid":"https://orcid.org/0000-0003-2707-3165"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Wen","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062614549","display_name":"Pinlong Cai","orcid":"https://orcid.org/0000-0002-3993-0913"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pinlong Cai","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006841536","display_name":"Daocheng Fu","orcid":"https://orcid.org/0000-0001-5660-5904"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daocheng Fu","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101045429","display_name":"Song Mao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Mao","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058342038","display_name":"Botian Shi","orcid":"https://orcid.org/0000-0003-3677-7252"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Botian Shi","raw_affiliation_strings":["Shanghai Artificial Intelligence Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Artificial Intelligence Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5068874919"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4391012619"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2494398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"10","first_page":"15453","last_page":"15470"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9896000027656555,"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":0.9896000027656555,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9779000282287598,"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/monte-carlo-method","display_name":"Monte Carlo method","score":0.6940963268280029},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.558258056640625},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.5378299355506897},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5266218781471252},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5008490085601807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4627618193626404},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.4103556275367737},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.3658951222896576},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3319038450717926},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20829558372497559},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.159685879945755},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13079068064689636},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07161849737167358}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6940963268280029},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.558258056640625},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.5378299355506897},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5266218781471252},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5008490085601807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4627618193626404},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.4103556275367737},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.3658951222896576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3319038450717926},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20829558372497559},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.159685879945755},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13079068064689636},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07161849737167358},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3592741","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3592741","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/G7533693698","display_name":null,"funder_award_id":"22DZ1100102","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"}],"funders":[{"id":"https://openalex.org/F4320311779","display_name":"Shanghai Association for Science and Technology","ror":"https://ror.org/05j0k2q54"},{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W600444827","https://openalex.org/W1973215488","https://openalex.org/W2031836078","https://openalex.org/W2085842743","https://openalex.org/W2107338474","https://openalex.org/W2126316555","https://openalex.org/W2163411428","https://openalex.org/W2167265903","https://openalex.org/W2343568200","https://openalex.org/W2406067508","https://openalex.org/W2514762535","https://openalex.org/W2761568138","https://openalex.org/W2903709398","https://openalex.org/W2947742306","https://openalex.org/W2963165400","https://openalex.org/W2969076652","https://openalex.org/W2990116160","https://openalex.org/W3012553802","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3181350748","https://openalex.org/W3197234345","https://openalex.org/W3207915602","https://openalex.org/W4221146589","https://openalex.org/W4226239849","https://openalex.org/W4226440390","https://openalex.org/W4285012713","https://openalex.org/W4285507101","https://openalex.org/W4293682399","https://openalex.org/W4308081004","https://openalex.org/W4312550876","https://openalex.org/W4312862130","https://openalex.org/W4313162271","https://openalex.org/W4313189526","https://openalex.org/W4383108499","https://openalex.org/W4385195088","https://openalex.org/W4387448538","https://openalex.org/W4390284951","https://openalex.org/W4390429597","https://openalex.org/W4391768764","https://openalex.org/W4393078713","https://openalex.org/W4404563280"],"related_works":["https://openalex.org/W2571592646","https://openalex.org/W4247855592","https://openalex.org/W2740304877","https://openalex.org/W24774503","https://openalex.org/W2978000411","https://openalex.org/W4226164546","https://openalex.org/W2766259847","https://openalex.org/W2112583639","https://openalex.org/W2014821076","https://openalex.org/W2567165815"],"abstract_inverted_index":{"Traffic":[0],"flow":[1,83],"simulation":[2],"within":[3,163,188],"the":[4,64,122,148,151,164,170,194],"domain":[5],"of":[6,66,124,129,150,172,197],"intelligent":[7],"transportation":[8],"systems":[9],"is":[10],"garnering":[11],"significant":[12],"attention,":[13],"and":[14,18,51,73,88,109,138,154],"generating":[15],"realistic,":[16],"diverse,":[17],"human-like":[19,198],"traffic":[20,82,165,182],"patterns":[21],"presents":[22],"critical":[23],"challenges":[24],"that":[25,62],"must":[26],"be":[27],"addressed.":[28],"Current":[29],"approaches":[30],"often":[31],"hinge":[32],"on":[33,41,47],"predefined":[34],"driver":[35],"models,":[36],"objective":[37],"optimization,":[38],"or":[39],"reliance":[40],"pre-recorded":[42],"driving":[43,86,199],"datasets,":[44],"imposing":[45],"limitations":[46],"their":[48,104],"scalability,":[49],"versatility,":[50],"adaptability.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56,120,142,168],"introduce":[57],"TrafficMCTS,":[58],"an":[59],"innovative":[60],"framework":[61,97,153],"harnesses":[63],"synergy":[65],"group-based":[67],"Monte":[68],"Carlo":[69],"tree":[70],"search":[71],"(MCTS)":[72],"Social":[74],"Value":[75],"Orientation":[76],"(SVO)":[77],"to":[78,100,103,146,158,178],"engender":[79],"a":[80,93,189],"multifaceted":[81],"with":[84,117],"varying":[85],"styles":[87],"cooperative":[89],"tendencies.":[90],"Anchored":[91],"by":[92,174],"closed-loop":[94],"architecture,":[95],"our":[96,125],"enables":[98],"vehicles":[99,187],"dynamically":[101],"adapt":[102],"environment":[105],"in":[106,127],"real":[107],"time,":[108,137],"ensure":[110],"feasible":[111],"collision-free":[112],"trajectories.":[113],"Through":[114],"comprehensive":[115],"comparisons":[116],"state-of-the-art":[118],"methods,":[119],"illuminate":[121],"advantages":[123],"approach":[126],"terms":[128],"computational":[130],"efficiency,":[131],"planning":[132],"success":[133],"rate,":[134],"intention":[135],"completion":[136],"diversity":[139],"metrics.":[140],"Besides,":[141],"simulate":[143,180],"multiple":[144],"scenarios":[145,183],"illustrate":[147],"effectiveness":[149],"proposed":[152],"highlight":[155],"its":[156,176],"ability":[157],"induce":[159],"diverse":[160,181],"social":[161],"behaviors":[162],"flow.":[166],"Finally,":[167],"validate":[169],"scalability":[171],"TrafficMCTS":[173],"demonstrating":[175],"capability":[177],"efficiently":[179],"involving":[184],"numerous":[185],"interacting":[186],"complex":[190],"road":[191],"network,":[192],"capturing":[193],"intricate":[195],"dynamics":[196],"behaviors.":[200]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}