{"id":"https://openalex.org/W4408696286","doi":"https://doi.org/10.1109/itsc58415.2024.10920171","title":"SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets","display_name":"SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4408696286","doi":"https://doi.org/10.1109/itsc58415.2024.10920171"},"language":"en","primary_location":{"id":"doi:10.1109/itsc58415.2024.10920171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th 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/A5108988763","display_name":"Yunlong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yunlong Li","raw_affiliation_strings":["Columbia University,Department of Electrical Engineering,New York,NY,USA,10025"],"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Electrical Engineering,New York,NY,USA,10025","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019056538","display_name":"Zhaobin Mo","orcid":"https://orcid.org/0000-0002-0465-8550"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaobin Mo","raw_affiliation_strings":["Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025"],"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049787333","display_name":"Xuan Di","orcid":"https://orcid.org/0000-0003-2925-7697"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuan Di","raw_affiliation_strings":["Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025"],"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10025","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108988763"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31293016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3251","last_page":"3256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9718000292778015,"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":0.9718000292778015,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9592999815940857,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6978263258934021}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6978263258934021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc58415.2024.10920171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2825743987","display_name":null,"funder_award_id":"CPS-2038984,ERC-2133516","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2109690032","https://openalex.org/W2115579991","https://openalex.org/W2148143831","https://openalex.org/W2404077489","https://openalex.org/W2743627947","https://openalex.org/W3034264193","https://openalex.org/W3036512832","https://openalex.org/W3042159104","https://openalex.org/W3179442871","https://openalex.org/W4226459732","https://openalex.org/W4283373979","https://openalex.org/W4312406013","https://openalex.org/W4312606716","https://openalex.org/W4378364109","https://openalex.org/W4383108597","https://openalex.org/W4389667201","https://openalex.org/W4401975664","https://openalex.org/W4402727359","https://openalex.org/W4407629424","https://openalex.org/W6870587590"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Safety-critical":[0],"driving":[1,54,86,117],"data":[2,18,55,97,118],"is":[3],"crucial":[4],"for":[5,91],"developing":[6],"safe":[7],"and":[8,42,77,84,149],"trustworthy":[9],"self-driving":[10,133],"algorithms.":[11],"Due":[12],"to":[13,50,60,80,98,104,143],"the":[14,52,57,105,144],"scarcity":[15],"of":[16,94],"safety-critical":[17,53,116],"in":[19,36],"naturalistic":[20,43,58],"datasets,":[21],"current":[22],"approaches":[23],"primarily":[24],"utilize":[25],"simulated":[26,106],"or":[27,107],"artificially":[28,108],"generated":[29,40,109],"images.":[30],"However,":[31],"there":[32],"remains":[33],"a":[34,47,131],"gap":[35],"authenticity":[37],"between":[38],"these":[39],"images":[41],"ones.":[44],"We":[45],"propose":[46],"novel":[48],"framework":[49],"augment":[51],"from":[56],"dataset":[59,139],"address":[61],"this":[62,65,137],"issue.":[63],"In":[64],"framework,":[66],"we":[67],"first":[68],"detect":[69],"vehicles":[70],"using":[71,126],"YOLOv5,":[72],"followed":[73],"by":[74],"depth":[75],"estimation":[76],"3D":[78],"transformation":[79],"simulate":[81],"vehicle":[82,95],"proximity":[83],"critical":[85],"scenarios":[87],"better.":[88],"This":[89],"allows":[90],"targeted":[92],"modification":[93],"dynamics":[96],"reflect":[99],"potentially":[100],"hazardous":[101],"situations.":[102],"Compared":[103],"data,":[110],"our":[111],"augmentation":[112],"methods":[113],"can":[114],"generate":[115],"with":[119],"minimal":[120],"compromise":[121],"on":[122,136],"image":[123],"authenticity.":[124],"Experiments":[125],"KITTI":[127],"datasets":[128],"demonstrate":[129],"that":[130],"downstream":[132],"algorithm":[134],"trained":[135],"augmented":[138],"performs":[140],"superiorly":[141],"compared":[142],"baselines,":[145],"which":[146],"include":[147],"SMOGN":[148],"importance":[150],"sampling.":[151]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
