{"id":"https://openalex.org/W4391768508","doi":"https://doi.org/10.1109/itsc57777.2023.10422230","title":"Modeling Interaction-Aware Driving Behavior using Graph-Based Representations and Multi-Agent Reinforcement Learning","display_name":"Modeling Interaction-Aware Driving Behavior using Graph-Based Representations and Multi-Agent Reinforcement Learning","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4391768508","doi":"https://doi.org/10.1109/itsc57777.2023.10422230"},"language":"en","primary_location":{"id":"doi:10.1109/itsc57777.2023.10422230","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-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/A5054864095","display_name":"Fabian Konstantinidis","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Fabian Konstantinidis","raw_affiliation_strings":["Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016304876","display_name":"Moritz Sackmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moritz Sackmann","raw_affiliation_strings":["Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103156082","display_name":"Ulrich Hofmann","orcid":"https://orcid.org/0000-0001-9339-7948"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ulrich Hofmann","raw_affiliation_strings":["Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440"],"affiliations":[{"raw_affiliation_string":"Pre-Development of Automated Driving, CARIAD SE,Wolfsburg,Germany,38440","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091574711","display_name":"Christoph Stiller","orcid":"https://orcid.org/0000-0003-4165-2075"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph Stiller","raw_affiliation_strings":["Institute of Measurement and Control Systems,Karlsruhe In-stitute of Technology (KIT),Karlsruhe,Germany,76131"],"affiliations":[{"raw_affiliation_string":"Institute of Measurement and Control Systems,Karlsruhe In-stitute of Technology (KIT),Karlsruhe,Germany,76131","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054864095"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.345,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59224067,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1643","last_page":"1650"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.8604999780654907,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.8604999780654907,"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/T10524","display_name":"Traffic control and management","score":0.8590999841690063,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.8395000100135803,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8323692679405212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193689942359924},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4473584294319153},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.42133229970932007},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4176154136657715},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3986126482486725},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3096824884414673},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12184712290763855}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8323692679405212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193689942359924},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4473584294319153},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.42133229970932007},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4176154136657715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3986126482486725},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3096824884414673},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12184712290763855},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc57777.2023.10422230","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1191599655","https://openalex.org/W1522301498","https://openalex.org/W1592601589","https://openalex.org/W2056877664","https://openalex.org/W2152374007","https://openalex.org/W2519106163","https://openalex.org/W2736601468","https://openalex.org/W2739974901","https://openalex.org/W2768629321","https://openalex.org/W2782474430","https://openalex.org/W2905509562","https://openalex.org/W2968983352","https://openalex.org/W2971007756","https://openalex.org/W2980087597","https://openalex.org/W3034722190","https://openalex.org/W3035700320","https://openalex.org/W3099689767","https://openalex.org/W3108486966","https://openalex.org/W3116294947","https://openalex.org/W3125605478","https://openalex.org/W3128782524","https://openalex.org/W3196864007","https://openalex.org/W3204875639","https://openalex.org/W3209837334","https://openalex.org/W3210638693","https://openalex.org/W4214717370","https://openalex.org/W4286285622","https://openalex.org/W4299802797","https://openalex.org/W4385245566","https://openalex.org/W6627932998","https://openalex.org/W6631190155","https://openalex.org/W6738796088","https://openalex.org/W6741002519","https://openalex.org/W6745935785","https://openalex.org/W6747473740","https://openalex.org/W6768870957","https://openalex.org/W6779282036","https://openalex.org/W6780226713","https://openalex.org/W6782468546","https://openalex.org/W6790684878","https://openalex.org/W6866376193"],"related_works":["https://openalex.org/W2920061524","https://openalex.org/W4310083477","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856","https://openalex.org/W1987513656","https://openalex.org/W2072376847","https://openalex.org/W2089013912","https://openalex.org/W2145821588"],"abstract_inverted_index":{"Modeling":[0],"the":[1,21,25,42,55,103,113,147],"driving":[2,89],"behavior":[3],"of":[4,27,38,41,54,58,72,96,170],"traffic":[5,10,28],"partici-pants":[6],"in":[7,142],"highly":[8],"interactive":[9],"situations,":[11],"such":[12],"as":[13],"roundabouts,":[14],"poses":[15],"a":[16,36,51,69,88,93,127,143,154],"significant":[17],"challenge":[18],"due":[19],"to":[20,86,100,121,153],"complex":[22,187],"interactions":[23,191],"and":[24,68,108,150,185,190],"variety":[26],"situations.":[29],"To":[30,134],"address":[31],"this":[32,81],"task,":[33],"we":[34,139],"propose":[35],"combination":[37],"graph-based":[39,52,178],"representations":[40],"environment":[43,57],"with":[44,76],"Multi-Agent":[45],"Reinforcement":[46,130],"Learning":[47,131],"(MARL).":[48],"By":[49],"utilizing":[50],"representation":[53,179],"local":[56],"each":[59,77],"vehicle,":[60],"our":[61,136,165,177],"approach":[62],"efficiently":[63],"accounts":[64],"for":[65,183],"road":[66,104,188],"structures":[67],"varying":[70],"number":[71],"surrounding":[73],"vehicles":[74],"interacting":[75],"other.":[78],"Building":[79],"upon":[80],"representation,":[82],"MARL":[83],"enables":[84],"us":[85,120],"learn":[87],"policy":[90,115,128],"based":[91],"on":[92],"minimal":[94],"set":[95],"principles:":[97],"drivers":[98],"want":[99],"move":[101],"along":[102],"while":[105],"avoiding":[106],"collisions":[107],"maintaining":[109],"comfortable":[110],"accelerations.":[111],"Sharing":[112],"learned":[114,156],"among":[116],"all":[117],"agents":[118],"allows":[119],"leverage":[122],"Proximal":[123],"Policy":[124],"Optimization":[125],"(PPO),":[126],"gradient":[129],"(RL)":[132],"algorithm.":[133],"evaluate":[135],"proposed":[137,166],"model,":[138],"conduct":[140],"experiments":[141],"roundabout":[144],"scenario":[145],"from":[146],"INTERACTION":[148],"dataset":[149],"compare":[151],"it":[152],"model":[155,167],"via":[157],"Behavior":[158],"Cloning":[159],"(BC).":[160],"The":[161],"results":[162],"demonstrate":[163],"that":[164,176],"is":[168,180],"capable":[169],"maneuvering":[171],"through":[172],"dense":[173],"traffic,":[174],"indicating":[175],"well":[181],"suitable":[182],"modeling":[184],"understanding":[186],"layouts":[189],"between":[192],"agents.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}