{"id":"https://openalex.org/W7136591796","doi":"https://doi.org/10.1109/itsc60802.2025.11423669","title":"Red-Team Multi-Agent Reinforcement Learning for Emergency Braking Scenario","display_name":"Red-Team Multi-Agent Reinforcement Learning for Emergency Braking Scenario","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7136591796","doi":"https://doi.org/10.1109/itsc60802.2025.11423669"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113584976","display_name":"Yinsong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinsong Chen","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115597574","display_name":"Kaifeng Wang","orcid":"https://orcid.org/0009-0007-3331-7716"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaifeng Wang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083455882","display_name":"Xiaoqiang Meng","orcid":"https://orcid.org/0009-0001-6407-4952"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqiang Meng","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100666050","display_name":"Qi Liu","orcid":"https://orcid.org/0000-0001-5172-0989"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyuan Li","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021871852","display_name":"Zirui LI","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zirui Li","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xin Gao","orcid":"https://orcid.org/0000-0002-7317-8059"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Gao","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China"],"raw_orcid":"https://orcid.org/0000-0002-7317-8059","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6105999946594238,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6105999946594238,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.021400000900030136,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.020899999886751175,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/control","display_name":"Control (management)","score":0.3752000033855438},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3280999958515167},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.2849000096321106},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.2800000011920929},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.2630000114440918}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5266000032424927},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3492000102996826},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.27889999747276306},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.6195228099822998,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1531725372","https://openalex.org/W2142174465","https://openalex.org/W2903709398","https://openalex.org/W2953901595","https://openalex.org/W2970679500","https://openalex.org/W2981271343","https://openalex.org/W3016931720","https://openalex.org/W3090747022","https://openalex.org/W3126673337","https://openalex.org/W3127647470","https://openalex.org/W3130718496","https://openalex.org/W3196020871","https://openalex.org/W4320025943","https://openalex.org/W4386918874","https://openalex.org/W4391793356","https://openalex.org/W4397026428","https://openalex.org/W4401717567","https://openalex.org/W4405305553","https://openalex.org/W4405306098","https://openalex.org/W4405360780","https://openalex.org/W4406457478","https://openalex.org/W4406729337","https://openalex.org/W4416748522"],"related_works":[],"abstract_inverted_index":{"Current":[0],"research":[1,144],"on":[2,9],"decision-making":[3,129],"in":[4,24,145],"safety-critical":[5,146],"scenarios":[6],"often":[7],"relies":[8],"inefficient":[10],"data-driven":[11],"scenario":[12],"generation":[13],"or":[14],"specific":[15],"modeling":[16],"approaches,":[17],"which":[18],"fail":[19],"to":[20,97,105,111],"capture":[21],"corner":[22,59,134],"cases":[23,60],"real-world":[25],"contexts.":[26],"To":[27],"address":[28],"this":[29],"issue,":[30],"we":[31],"propose":[32],"a":[33,68,140],"Red-Team":[34],"Multi-Agent":[35],"Reinforcement":[36],"Learning":[37],"framework,":[38],"where":[39],"background":[40],"vehicles":[41,56,78,88,104],"with":[42,80],"interference":[43,52],"capabilities":[44],"are":[45],"treated":[46],"as":[47],"red-team":[48,55,77,103],"agents.":[49],"Through":[50],"active":[51],"and":[53,131],"exploration,":[54],"can":[57],"uncover":[58],"outside":[61],"the":[62,86,99,113,117,123],"data":[63],"distribution.":[64],"The":[65],"framework":[66,125],"uses":[67],"Constraint":[69],"Graph":[70],"Representation":[71],"Markov":[72],"Decision":[73],"Process,":[74],"ensuring":[75],"that":[76,122],"comply":[79],"safety":[81,130],"rules":[82],"while":[83],"continuously":[84],"disrupting":[85],"autonomous":[87],"(AVs).":[89],"A":[90],"policy":[91],"threat":[92,100],"zone":[93],"model":[94],"is":[95],"constructed":[96],"quantify":[98],"posed":[101],"by":[102],"AVs,":[106],"inducing":[107],"more":[108],"extreme":[109],"actions":[110],"increase":[112],"danger":[114],"level":[115],"of":[116],"scenario.":[118],"Experimental":[119],"results":[120],"show":[121],"proposed":[124],"significantly":[126],"impacts":[127],"AVs":[128],"generates":[132],"various":[133],"cases.":[135],"This":[136],"method":[137],"also":[138],"offers":[139],"novel":[141],"direction":[142],"for":[143],"scenarios.":[147]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-17T00:00:00"}
