{"id":"https://openalex.org/W4388936562","doi":"https://doi.org/10.1109/tiv.2023.3335862","title":"Adversarial Safety-Critical Scenario Generation Using Naturalistic Human Driving Priors","display_name":"Adversarial Safety-Critical Scenario Generation Using Naturalistic Human Driving Priors","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4388936562","doi":"https://doi.org/10.1109/tiv.2023.3335862"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2023.3335862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3335862","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2408.03200","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035069984","display_name":"Kunkun Hao","orcid":"https://orcid.org/0000-0003-0420-1347"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kunkun Hao","raw_affiliation_strings":["Research Center of Synkrotron, Inc., Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-0420-1347","affiliations":[{"raw_affiliation_string":"Research Center of Synkrotron, Inc., Xi'an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103238935","display_name":"Wen Cui","orcid":"https://orcid.org/0000-0002-7846-2534"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I4210141776","display_name":"China XD Group (China)","ror":"https://ror.org/04ceqst84","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210141776"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Cui","raw_affiliation_strings":["Institute for Interdisciplinary Information Core Technology, Xi'an, China","Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an, China; Institute for Interdisciplinary Information Core Technology, Xi'an, China; Research Center of Synkrotron, Inc., Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-7846-2534","affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Core Technology, Xi'an, China","institution_ids":["https://openalex.org/I4210141776"]},{"raw_affiliation_string":"Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an, China; Institute for Interdisciplinary Information Core Technology, Xi'an, China; Research Center of Synkrotron, Inc., Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yonggang Luo","orcid":"https://orcid.org/0009-0000-3973-7606"},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggang Luo","raw_affiliation_strings":["AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-3973-7606","affiliations":[{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","institution_ids":["https://openalex.org/I4210131649"]},{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113070463","display_name":"Lecheng Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lecheng Xie","raw_affiliation_strings":["AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0006-3887-2770","affiliations":[{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","institution_ids":["https://openalex.org/I4210131649"]},{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuqiao Bai","orcid":"https://orcid.org/0009-0000-1537-7474"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuqiao Bai","raw_affiliation_strings":["Research Center of Synkrotron, Inc., Xi'an, China"],"raw_orcid":"https://orcid.org/0009-0000-1537-7474","affiliations":[{"raw_affiliation_string":"Research Center of Synkrotron, Inc., Xi'an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jucheng Yang","orcid":"https://orcid.org/0009-0006-3431-4536"},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jucheng Yang","raw_affiliation_strings":["AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0006-3431-4536","affiliations":[{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Company Ltd, Chongqing, China","institution_ids":["https://openalex.org/I4210131649"]},{"raw_affiliation_string":"AI Laboratory, Chongqing Changan Automobile Co. Ltd, Chongqing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062132230","display_name":"Songyang Yan","orcid":"https://orcid.org/0000-0003-0628-8642"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songyang Yan","raw_affiliation_strings":["Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-0628-8642","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110687259","display_name":"Yuxi Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuxi Pan","raw_affiliation_strings":["Research Center of Synkrotron, Inc., Xi'an, China"],"raw_orcid":"https://orcid.org/0009-0008-5952-9378","affiliations":[{"raw_affiliation_string":"Research Center of Synkrotron, Inc., Xi'an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101995389","display_name":"Zijiang Yang","orcid":"https://orcid.org/0009-0002-5437-0253"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijiang Yang","raw_affiliation_strings":["Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":"https://orcid.org/0009-0002-5437-0253","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5035069984"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.749,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.94636227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"9","issue":"9","first_page":"5392","last_page":"5406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9772999882698059,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9772999882698059,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9714000225067139,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9398000240325928,"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/prior-probability","display_name":"Prior probability","score":0.826485276222229},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6541412472724915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49428892135620117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30864977836608887},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10079911351203918}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.826485276222229},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6541412472724915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49428892135620117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30864977836608887},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10079911351203918}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tiv.2023.3335862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3335862","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2408.03200","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.03200","pdf_url":"https://arxiv.org/pdf/2408.03200","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2408.03200","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.03200","pdf_url":"https://arxiv.org/pdf/2408.03200","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1733534984","display_name":null,"funder_award_id":"2022YFB4300700","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1812586646","display_name":null,"funder_award_id":"62232008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6786717514","display_name":null,"funder_award_id":"62032010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388936562.pdf"},"referenced_works_count":88,"referenced_works":["https://openalex.org/W198912494","https://openalex.org/W1847191588","https://openalex.org/W1965455100","https://openalex.org/W2023401794","https://openalex.org/W2048294994","https://openalex.org/W2056877664","https://openalex.org/W2125836634","https://openalex.org/W2126270075","https://openalex.org/W2128728535","https://openalex.org/W2194775991","https://openalex.org/W2521921275","https://openalex.org/W2525936901","https://openalex.org/W2529897811","https://openalex.org/W2580495915","https://openalex.org/W2618530766","https://openalex.org/W2798302089","https://openalex.org/W2888125957","https://openalex.org/W2912445127","https://openalex.org/W2923088732","https://openalex.org/W2951360122","https://openalex.org/W2960718452","https://openalex.org/W2962856082","https://openalex.org/W2963118571","https://openalex.org/W2963178695","https://openalex.org/W2965888130","https://openalex.org/W2967727187","https://openalex.org/W2970679500","https://openalex.org/W2976205474","https://openalex.org/W2985936292","https://openalex.org/W2999798945","https://openalex.org/W3003950977","https://openalex.org/W3032950445","https://openalex.org/W3048636285","https://openalex.org/W3096831136","https://openalex.org/W3108574066","https://openalex.org/W3110877594","https://openalex.org/W3112288498","https://openalex.org/W3127647470","https://openalex.org/W3130718496","https://openalex.org/W3132583427","https://openalex.org/W3133465684","https://openalex.org/W3138984732","https://openalex.org/W3159028934","https://openalex.org/W3173453526","https://openalex.org/W3176912151","https://openalex.org/W3179442871","https://openalex.org/W3179903080","https://openalex.org/W3184932611","https://openalex.org/W3196020871","https://openalex.org/W3212907084","https://openalex.org/W3217222744","https://openalex.org/W4210680058","https://openalex.org/W4221156702","https://openalex.org/W4224231583","https://openalex.org/W4226153564","https://openalex.org/W4250863246","https://openalex.org/W4289792821","https://openalex.org/W4293222193","https://openalex.org/W4296425724","https://openalex.org/W4297021290","https://openalex.org/W4301180680","https://openalex.org/W4307086471","https://openalex.org/W4312238169","https://openalex.org/W4312363838","https://openalex.org/W4312406013","https://openalex.org/W4312550876","https://openalex.org/W4321231431","https://openalex.org/W4323338414","https://openalex.org/W4323338447","https://openalex.org/W4361799717","https://openalex.org/W4385154238","https://openalex.org/W4386088221","https://openalex.org/W4386869725","https://openalex.org/W6631190155","https://openalex.org/W6631264276","https://openalex.org/W6640425456","https://openalex.org/W6683195989","https://openalex.org/W6684921986","https://openalex.org/W6692846177","https://openalex.org/W6718092244","https://openalex.org/W6745935785","https://openalex.org/W6754644633","https://openalex.org/W6763291628","https://openalex.org/W6764668024","https://openalex.org/W6766978945","https://openalex.org/W6768870957","https://openalex.org/W6771352390","https://openalex.org/W6774966973"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492"],"abstract_inverted_index":{"Evaluating":[0],"the":[1,28,131,166,198,202,208,217,238,247],"decision-making":[2],"system":[3],"is":[4,24],"indispensable":[5],"in":[6,34,42,183,195],"developing":[7],"autonomous":[8,250],"vehicles,":[9],"while":[10],"realistic":[11,222],"and":[12,32,58,75,110,122,125,169,188,207,229],"challenging":[13],"safety-critical":[14,223],"test":[15,69,224],"scenarios":[16,23,70,225],"play":[17],"a":[18,47,80,95,156,244],"crucial":[19],"role.":[20],"Obtaining":[21],"these":[22],"non-trivial,":[25],"thanks":[26],"to":[27,120,142,154,164],"long-tailed":[29],"distribution,":[30],"sparsity,":[31],"rarity":[33],"real-world":[35,132],"data":[36],"sets.":[37],"To":[38],"tackle":[39],"this":[40,43,91],"problem,":[41],"paper,":[44],"we":[45,65,78,93,135],"introduce":[46],"natural":[48,85,173],"adversarial":[49,174],"scenario":[50,175],"generation":[51,176],"solution":[52],"using":[53],"naturalistic":[54],"human":[55],"driving":[56],"priors":[57],"reinforcement":[59],"learning":[60],"techniques.":[61],"By":[62],"doing":[63],"this,":[64],"can":[66,150,220,242],"obtain":[67],"large-scale":[68],"that":[71,83,216],"are":[72],"both":[73,227],"diverse":[74],"realistic.":[76],"Specifically,":[77],"build":[79],"simulation":[81],"environment":[82],"mimics":[84],"traffic":[86,191],"interaction":[87],"scenarios.":[88],"Informed":[89],"by":[90,116],"environment,":[92],"implement":[94],"two-stage":[96],"procedure.":[97],"The":[98,147],"first":[99],"stage":[100],"incorporates":[101],"conventional":[102],"rule-based":[103],"models,":[104],"e.g.,":[105,201],"IDM":[106],"(Intelligent":[107],"Driver":[108],"Model)":[109],"MOBIL":[111],"(Minimizing":[112],"Overall":[113],"Braking":[114],"Induced":[115],"Lane":[117],"changes)":[118],"model,":[119,200,240],"coarsely":[121],"discretely":[123],"capture":[124],"calibrate":[126],"key":[127],"control":[128],"parameters":[129,192],"from":[130],"dataset.":[133],"Next,":[134],"leverage":[136],"GAIL":[137,149],"(Generative":[138],"Adversarial":[139],"Imitation":[140],"Learning)":[141],"represent":[143],"driver":[144],"behaviors":[145],"continuously.":[146],"derived":[148],"be":[151,243],"further":[152],"used":[153],"design":[155],"PPO":[157],"(Proximal":[158],"Policy":[159],"Optimization)-based":[160],"actor-critic":[161],"network":[162],"framework":[163],"fine-tune":[165],"reward":[167],"function,":[168],"then":[170],"optimize":[171],"our":[172],"solution.":[177],"Extensive":[178],"experiments":[179],"have":[180],"been":[181],"conducted":[182],"two":[184],"popular":[185],"datasets,":[186],"NGSIM":[187],"INTERACTION.":[189],"Essential":[190],"were":[193],"measured":[194],"comparison":[196],"with":[197,231],"baseline":[199,239],"collision":[203],"rate,":[204],"accelerations,":[205],"steering,":[206],"number":[209],"of":[210,249],"lane":[211],"changes.":[212],"Our":[213],"findings":[214],"demonstrate":[215],"proposed":[218],"model":[219],"generate":[221],"covering":[226],"naturalness":[228],"adversariality":[230],"an":[232],"advanced":[233],"44%":[234],"efficiency":[235],"gain":[236],"over":[237],"which":[241],"cornerstone":[245],"for":[246],"development":[248],"vehicles.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}