{"id":"https://openalex.org/W3119236961","doi":"https://doi.org/10.1109/iv47402.2020.9304609","title":"CSG: Critical Scenario Generation from Real Traffic Accidents","display_name":"CSG: Critical Scenario Generation from Real Traffic Accidents","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3119236961","doi":"https://doi.org/10.1109/iv47402.2020.9304609","mag":"3119236961"},"language":"en","primary_location":{"id":"doi:10.1109/iv47402.2020.9304609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","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/A5100375456","display_name":"Xinxin Zhang","orcid":"https://orcid.org/0000-0002-1856-9145"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang Xinxin","raw_affiliation_strings":["Research scientist of Intelligent Driving Lab, Intel Labs China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research scientist of Intelligent Driving Lab, Intel Labs China, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740275","display_name":"Li Fei","orcid":"https://orcid.org/0000-0003-1308-4787"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Fei","raw_affiliation_strings":["Research scientist of Intelligent Driving Lab, Intel Labs China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research scientist of Intelligent Driving Lab, Intel Labs China, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043649707","display_name":"Xiangbin Wu","orcid":"https://orcid.org/0000-0001-7243-3284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu Xiangbin","raw_affiliation_strings":["Research director of Intelligent Driving Lab, Intel Labs China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Research director of Intelligent Driving Lab, Intel Labs China, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100375456"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5163,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.89166172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1330","last_page":"1336"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9902999997138977,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7077831029891968},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.6914464831352234},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6586349606513977},{"id":"https://openalex.org/keywords/scenario-testing","display_name":"Scenario testing","score":0.5696001648902893},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.522172212600708},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.49584564566612244},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.3478650450706482},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19825145602226257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15369173884391785}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7077831029891968},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.6914464831352234},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6586349606513977},{"id":"https://openalex.org/C80519477","wikidata":"https://www.wikidata.org/wiki/Q3532236","display_name":"Scenario testing","level":3,"score":0.5696001648902893},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.522172212600708},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.49584564566612244},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3478650450706482},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19825145602226257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15369173884391785},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv47402.2020.9304609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W629029206","https://openalex.org/W2057483198","https://openalex.org/W2112731915","https://openalex.org/W2525936901","https://openalex.org/W2615547864","https://openalex.org/W2747333411","https://openalex.org/W2749747771","https://openalex.org/W2810798104","https://openalex.org/W2891056855","https://openalex.org/W2912798476","https://openalex.org/W2947731191","https://openalex.org/W2955582742","https://openalex.org/W2962867954","https://openalex.org/W2963150697","https://openalex.org/W2963491064","https://openalex.org/W2963657083","https://openalex.org/W2970089253","https://openalex.org/W2970679500","https://openalex.org/W3122849182","https://openalex.org/W4295719664","https://openalex.org/W4297781990","https://openalex.org/W6620183896","https://openalex.org/W6737769214","https://openalex.org/W6745935785","https://openalex.org/W6795446406"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2121910908"],"abstract_inverted_index":{"Autonomous":[0],"driving":[1],"(AD)":[2],"is":[3,31,60],"getting":[4],"closer":[5],"to":[6,65,104,115],"our":[7,133,173],"life,":[8],"but":[9],"the":[10,20,27,37,43,50,61,67,143],"severe":[11],"traffic":[12,121],"accidents":[13],"of":[14,29,71,88,168],"autonomous":[15],"vehicle":[16],"(AV)":[17],"happened":[18],"in":[19,127],"past":[21],"several":[22],"years":[23],"warn":[24],"us":[25],"that":[26],"safety":[28,70,161,174],"AVs":[30],"still":[32],"a":[33,112,128,148,157],"big":[34],"challenge":[35],"for":[36,136,159],"AD":[38],"industry.":[39],"Before":[40],"volume":[41],"production,":[42],"automotive":[44],"industry":[45],"and":[46,69,82,86,99,124,139,153,177],"regulators":[47],"must":[48],"ensure":[49],"AV":[51,160],"can":[52,94,146],"deal":[53],"with":[54],"dangerous":[55],"scenarios.":[56,91],"Although":[57],"road":[58,105],"test":[59,66],"most":[62],"common":[63],"method":[64],"performance":[68],"an":[72,101],"AV,":[73],"it":[74,155],"has":[75],"some":[76],"manifest":[77],"disadvantages,":[78],"e.g.,":[79],"highly":[80],"risky":[81],"unrepeatable,":[83],"low":[84],"efficiency":[85],"lack":[87],"useful":[89],"critical":[90,117,149],"Critical-scenario-based":[92],"simulation":[93],"effectively":[95],"address":[96],"these":[97],"problems":[98],"become":[100],"important":[102],"complement":[103],"test.":[106,141],"In":[107],"this":[108],"paper,":[109],"we":[110,145,170],"present":[111],"novel":[113],"approach":[114],"extract":[116],"scenarios":[118],"from":[119],"real":[120],"accident":[122],"videos":[123],"re-generate":[125],"them":[126],"simulator.":[129],"We":[130],"also":[131],"introduce":[132,172],"integrated":[134],"toolkit":[135],"scenario":[137,140,150],"extraction":[138],"With":[142],"toolkit,":[144],"build":[147],"library":[151],"quickly":[152],"use":[154],"as":[156],"benchmark":[158],"assessment,":[162],"among":[163],"other":[164],"purposes.":[165],"On":[166],"top":[167],"this,":[169],"further":[171],"assessment":[175],"criteria":[176],"scoring":[178],"method.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":2}],"updated_date":"2026-01-15T23:16:33.117629","created_date":"2025-10-10T00:00:00"}