{"id":"https://openalex.org/W4285507101","doi":"https://doi.org/10.1109/lra.2022.3191241","title":"Efficient Game-Theoretic Planning With Prediction Heuristic for Socially-Compliant Autonomous Driving","display_name":"Efficient Game-Theoretic Planning With Prediction Heuristic for Socially-Compliant Autonomous Driving","publication_year":2022,"publication_date":"2022-07-15","ids":{"openalex":"https://openalex.org/W4285507101","doi":"https://doi.org/10.1109/lra.2022.3191241"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2022.3191241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3191241","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","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/A5026550358","display_name":"Chenran Li","orcid":"https://orcid.org/0000-0003-0231-7741"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenran Li","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0231-7741","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102779488","display_name":"Tu Trinh","orcid":"https://orcid.org/0000-0002-2373-1469"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tu Trinh","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2373-1469","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045596261","display_name":"Letian Wang","orcid":"https://orcid.org/0000-0002-0231-6960"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Letian Wang","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0231-6960","affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040156274","display_name":"Changliu Liu","orcid":"https://orcid.org/0000-0002-3767-5517"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changliu Liu","raw_affiliation_strings":["Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3767-5517","affiliations":[{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064077634","display_name":"Masayoshi Tomizuka","orcid":"https://orcid.org/0000-0003-0206-6639"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masayoshi Tomizuka","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0206-6639","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wei Zhan","orcid":"https://orcid.org/0000-0002-1474-1200"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Zhan","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1474-1200","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.741,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.83390389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"7","issue":"4","first_page":"10248","last_page":"10255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9977999925613403,"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":0.9977999925613403,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7265974283218384},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.6501002907752991},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6347547173500061},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5894581079483032},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5074805617332458},{"id":"https://openalex.org/keywords/nash-equilibrium","display_name":"Nash equilibrium","score":0.4885933995246887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4194066524505615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.351956844329834},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.24463221430778503},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13358300924301147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265974283218384},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.6501002907752991},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6347547173500061},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5894581079483032},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5074805617332458},{"id":"https://openalex.org/C46814582","wikidata":"https://www.wikidata.org/wiki/Q23389","display_name":"Nash equilibrium","level":2,"score":0.4885933995246887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4194066524505615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.351956844329834},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.24463221430778503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13358300924301147},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2022.3191241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3191241","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2047901468","https://openalex.org/W2126316555","https://openalex.org/W2396961959","https://openalex.org/W2411577903","https://openalex.org/W2565370028","https://openalex.org/W2573637607","https://openalex.org/W2614010283","https://openalex.org/W2736563494","https://openalex.org/W2949319840","https://openalex.org/W2963787234","https://openalex.org/W2963898834","https://openalex.org/W2969076652","https://openalex.org/W2980087597","https://openalex.org/W2990116160","https://openalex.org/W3011630888","https://openalex.org/W3098945776","https://openalex.org/W3100021380","https://openalex.org/W3116651890","https://openalex.org/W3122447121","https://openalex.org/W3132311446","https://openalex.org/W3132530365","https://openalex.org/W3176726067","https://openalex.org/W3216786669","https://openalex.org/W4200635987","https://openalex.org/W4207034179","https://openalex.org/W4225997321","https://openalex.org/W6638440308","https://openalex.org/W6674884181","https://openalex.org/W6730042731","https://openalex.org/W6768870957","https://openalex.org/W6804238973","https://openalex.org/W6805248675","https://openalex.org/W6811084544"],"related_works":["https://openalex.org/W2571592646","https://openalex.org/W4247855592","https://openalex.org/W2567165815","https://openalex.org/W2740304877","https://openalex.org/W4226164546","https://openalex.org/W2766259847","https://openalex.org/W2112583639","https://openalex.org/W346633817","https://openalex.org/W2563266764","https://openalex.org/W3164818296"],"abstract_inverted_index":{"Planning":[0],"under":[1],"social":[2],"interactions":[3,23],"with":[4,169],"other":[5,30,42,157],"agents":[6],"is":[7],"an":[8,117],"essential":[9],"problem":[10,49,55],"for":[11],"autonomous":[12,19,32],"driving.":[13],"As":[14],"the":[15,18,22,38,41,48,71,76,92,98,110,156,163,166],"actions":[16],"of":[17,40,106,137,165],"vehicle":[20],"in":[21,87,175],"affect":[24],"and":[25,67,142,154],"are":[26,147],"also":[27],"affected":[28],"by":[29,57,127],"agents,":[31],"vehicles":[33],"need":[34],"to":[35,75,108,149],"efficiently":[36],"infer":[37],"reaction":[39],"agents.":[43],"Most":[44],"existing":[45],"approaches":[46],"formulate":[47],"as":[50,91,132],"a":[51,103,129,133,139,143],"generalized":[52],"Nash":[53],"equilibrium":[54],"solved":[56],"optimization-based":[58],"methods.":[59],"However,":[60,90],"they":[61],"demand":[62],"too":[63],"much":[64],"computational":[65],"resource":[66],"easily":[68],"fall":[69],"into":[70],"local":[72],"minimum":[73],"due":[74],"non-convexity.":[77],"Monte":[78],"Carlo":[79],"Tree":[80],"Search":[81],"(MCTS)":[82],"successfully":[83],"tackles":[84],"such":[85],"issues":[86],"game-theoretic":[88,119],"problems.":[89],"interaction":[93],"game":[94],"tree":[95],"grows":[96],"exponentially,":[97],"general":[99,125],"MCTS":[100,126],"still":[101],"requires":[102],"huge":[104],"amount":[105],"iterations":[107],"reach":[109],"optima.":[111],"In":[112],"this":[113],"letter,":[114],"we":[115],"introduce":[116],"efficient":[118],"trajectory":[120],"planning":[121],"algorithm":[122,131,146],"based":[123],"on":[124],"incorporating":[128],"prediction":[130],"heuristic.":[134],"On":[135],"top":[136],"it,":[138],"social-compliant":[140],"reward":[141],"Bayesian":[144],"inference":[145],"designed":[148],"generate":[150],"diverse":[151],"driving":[152,159,173],"behaviors":[153],"identify":[155],"driver's":[158],"preference.":[160],"Results":[161],"demonstrate":[162],"effectiveness":[164],"proposed":[167],"framework":[168],"datasets":[170],"containing":[171],"naturalistic":[172],"behavior":[174],"highly":[176],"interactive":[177],"scenarios.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}