{"id":"https://openalex.org/W7161762962","doi":"https://doi.org/10.48550/arxiv.2605.18895","title":"KG-ASG: Collision-Knowledge-Guided Closed-Loop Adversarial Scenario Generation With Primary-Support Attribution","display_name":"KG-ASG: Collision-Knowledge-Guided Closed-Loop Adversarial Scenario Generation With Primary-Support Attribution","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7161762962","doi":"https://doi.org/10.48550/arxiv.2605.18895"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.18895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.18895","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136566107","display_name":"Cheng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128734017","display_name":"Chen Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136540987","display_name":"Ziwen Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136554360","display_name":"Yuchen Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yuchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136597265","display_name":"Qiang Liu","orcid":"https://orcid.org/0000-0003-2919-3195"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Qiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.7213000059127808,"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":0.7213000059127808,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.17880000174045563,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.03819999843835831,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/adversarial-system","display_name":"Adversarial system","score":0.8400999903678894},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.5895000100135803},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.5536999702453613},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5120000243186951},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.4731000065803528},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.43149998784065247},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3873000144958496},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.37470000982284546}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8400999903678894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6782000064849854},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.5895000100135803},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.5536999702453613},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5120000243186951},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.4731000065803528},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3865000009536743},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.37470000982284546},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.32409998774528503},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.18895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.18895","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18895","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Safety":[0],"validation":[1],"of":[2],"autonomous":[3,207],"driving":[4,208],"systems":[5],"requires":[6],"high-risk":[7],"scenario":[8,21,56],"coverage,":[9],"clear":[10],"collision":[11,42,66,79],"semantics,":[12],"executable":[13],"trajectories,":[14],"and":[15,69,87,113,128,155,179,187,196,204],"attributable":[16],"multi-vehicle":[17,46,96],"interactions.":[18],"Existing":[19],"safety-critical":[20],"generation":[22,57,98],"methods":[23],"often":[24],"rely":[25],"on":[26,159],"low-level":[27],"trajectory":[28],"perturbations,":[29],"collision-proxy":[30],"optimization,":[31],"or":[32,44],"single-adversary":[33],"search,":[34],"which":[35],"may":[36],"produce":[37],"adversarial":[38,55,97,170,201],"samples":[39],"with":[40,59],"ambiguous":[41],"causes":[43],"uncontrolled":[45],"collisions.":[47],"This":[48],"paper":[49],"proposes":[50],"KG-ASG,":[51],"a":[52,64,71,102],"collision-knowledge-guided":[53],"closed-loop":[54,181],"framework":[58],"primary-support":[60,103,197],"attribution.":[61],"KG-ASG":[62,167],"constructs":[63],"structured":[65],"knowledge":[67],"base":[68],"trains":[70],"lightweight":[72],"Collision":[73],"Expert":[74,188],"to":[75,136],"infer":[76],"the":[77,81,106,110,117],"target":[78],"mode,":[80],"unique":[82],"primary":[83,107],"adversary,":[84],"support":[85,114],"vehicles,":[86],"their":[88],"interaction":[89],"roles.":[90],"Guided":[91],"by":[92],"this":[93],"semantic":[94],"prior,":[95],"is":[99,147],"formulated":[100],"as":[101,133],"process,":[104],"where":[105],"adversary":[108],"induces":[109],"main":[111],"conflict":[112],"vehicles":[115],"shape":[116],"surrounding":[118],"risk":[119],"structure":[120],"without":[121],"becoming":[122],"additional":[123],"colliders.":[124],"Rule,":[125],"physical,":[126],"interaction-safety,":[127],"single-collider":[129,198],"constraints":[130],"are":[131],"imposed":[132],"hard":[134],"gates":[135],"filter":[137],"non-executable":[138],"samples.":[139],"To":[140],"handle":[141],"reactive":[142],"ego":[143],"behaviors,":[144],"planner-controller":[145],"feedback":[146],"further":[148],"used":[149],"for":[150,206],"failure":[151],"diagnosis,":[152],"candidate":[153],"re-ranking,":[154],"terminal":[156],"refinement.":[157],"Experiments":[158],"WOMD":[160],"scenarios":[161],"reconstructed":[162],"in":[163],"MetaDrive":[164],"show":[165],"that":[166,193],"achieves":[168],"strong":[169],"effectiveness":[171],"while":[172],"improving":[173],"Valid":[174],"Primary":[175],"Attack,":[176],"reducing":[177],"multi-collision,":[178],"obtaining":[180],"recovery":[182],"gains":[183],"under":[184],"IDM,":[185],"Cruise,":[186],"controllers.":[189],"These":[190],"results":[191],"demonstrate":[192],"collision-knowledge":[194],"guidance":[195],"reasoning":[199],"improve":[200],"effectiveness,":[202],"interpretability,":[203],"executability":[205],"safety":[209],"validation.":[210]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-21T00:00:00"}