{"id":"https://openalex.org/W4391935169","doi":"https://doi.org/10.1109/access.2024.3366990","title":"Advancing Autonomous Vehicle Safety: Machine Learning to Predict Sensor-Related Accident Severity","display_name":"Advancing Autonomous Vehicle Safety: Machine Learning to Predict Sensor-Related Accident Severity","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4391935169","doi":"https://doi.org/10.1109/access.2024.3366990"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3366990","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3366990","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10439194.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10439194.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021598855","display_name":"Rahman Shafique","orcid":"https://orcid.org/0000-0001-7641-2835"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Rahman Shafique","raw_affiliation_strings":["Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-7641-2835","affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058941449","display_name":"Furqan Rustam","orcid":"https://orcid.org/0000-0001-8403-1047"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Furqan Rustam","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0001-8403-1047","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072266446","display_name":"Sheriff Murtala","orcid":"https://orcid.org/0000-0003-2695-2838"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sheriff Murtala","raw_affiliation_strings":["Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2695-2838","affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022546955","display_name":"Anca Delia Jurcut","orcid":"https://orcid.org/0000-0002-2705-1823"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Anca Delia Jurcut","raw_affiliation_strings":["School of Computer Science, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-2705-1823","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044080887","display_name":"Gyu Sang Choi","orcid":"https://orcid.org/0000-0002-0854-768X"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyu Sang Choi","raw_affiliation_strings":["Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-0854-768X","affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, South Korea","institution_ids":["https://openalex.org/I55240360"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5021598855"],"corresponding_institution_ids":["https://openalex.org/I55240360"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":10.24,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.9882793,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":null,"first_page":"25933","last_page":"25948"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9947999715805054,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7841817140579224},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6179846525192261},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6014820337295532},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5838627219200134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758495926856995},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5077682733535767},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4376547336578369},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41126465797424316},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32292288541793823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7841817140579224},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6179846525192261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6014820337295532},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5838627219200134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758495926856995},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5077682733535767},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4376547336578369},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41126465797424316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32292288541793823},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3366990","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3366990","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10439194.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3e51834baaad44d8919846a420fbbc77","is_oa":true,"landing_page_url":"https://doaj.org/article/3e51834baaad44d8919846a420fbbc77","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 25933-25948 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3366990","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3366990","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10439194.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1989376136","display_name":null,"funder_award_id":"NRF-2019R1A2C1006159","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G284234960","display_name":null,"funder_award_id":"NRF-2021R1A6A1A03039493","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4682402912","display_name":null,"funder_award_id":"2021R1A6A1A03039493","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7875769530","display_name":null,"funder_award_id":"NRF-2021R1A6A1A03039493","funder_id":"https://openalex.org/F4320321380","funder_display_name":"Yeungnam University"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321380","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391935169.pdf","grobid_xml":"https://content.openalex.org/works/W4391935169.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W147936182","https://openalex.org/W316935178","https://openalex.org/W1574446622","https://openalex.org/W1970071483","https://openalex.org/W1973965874","https://openalex.org/W1987749519","https://openalex.org/W2012240254","https://openalex.org/W2025337382","https://openalex.org/W2062786991","https://openalex.org/W2078686220","https://openalex.org/W2099005886","https://openalex.org/W2810787428","https://openalex.org/W2912230569","https://openalex.org/W2930108727","https://openalex.org/W2988412621","https://openalex.org/W3011888019","https://openalex.org/W3039354370","https://openalex.org/W3042932150","https://openalex.org/W3045954046","https://openalex.org/W3091936287","https://openalex.org/W3124201778","https://openalex.org/W3129499366","https://openalex.org/W3168865200","https://openalex.org/W3206228978","https://openalex.org/W3211740586","https://openalex.org/W4211070280","https://openalex.org/W4214904744","https://openalex.org/W4214936265","https://openalex.org/W4220874139","https://openalex.org/W4255789945","https://openalex.org/W4283716673","https://openalex.org/W4286520466","https://openalex.org/W4290719157","https://openalex.org/W4297989938","https://openalex.org/W4312793369","https://openalex.org/W4317743578","https://openalex.org/W4322731448","https://openalex.org/W4362676646","https://openalex.org/W4385059346","https://openalex.org/W4385337378","https://openalex.org/W6605900128","https://openalex.org/W6634277687"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2770593030","https://openalex.org/W2012353789","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Autonomous":[0],"vehicles":[1],"(AVs)":[2],"represent":[3],"an":[4,180,188],"exciting":[5],"frontier":[6],"in":[7,45,169],"transportation,":[8],"promising":[9],"increased":[10],"safety":[11],"and":[12,41,102],"efficiency":[13],"on":[14],"the":[15,29,68,90,120,133,148],"roads.":[16],"However,":[17],"like":[18],"any":[19],"technological":[20],"advancement,":[21],"they":[22],"are":[23],"not":[24],"immune":[25],"to":[26,66,118,132,146,160],"accidents.":[27],"Understanding":[28],"severity":[30,69],"of":[31,70,98,123,135,150,192],"accidents":[32,71],"involving":[33,72],"AVs":[34],"is":[35],"crucial":[36,168],"for":[37,141],"enhancing":[38],"their":[39],"reliability":[40],"ensuring":[42],"public":[43],"trust":[44],"this":[46,51,174],"transformative":[47],"technology.":[48],"To":[49],"address":[50],"challenge,":[52],"our":[53,124,151],"study":[54,75],"has":[55,76],"employed":[56,155],"cutting-edge":[57],"natural":[58],"language":[59],"processing":[60],"techniques":[61],"combined":[62],"with":[63],"machine":[64],"learning":[65],"predict":[67],"AVs.":[73],"Our":[74],"contributed":[77],"significantly":[78],"by":[79],"creating":[80],"a":[81,110,162],"novel":[82,111],"dataset":[83,94],"derived":[84],"from":[85],"post-disengagement":[86],"accident":[87,137,171],"reports,":[88],"covering":[89],"years":[91],"2019-2022.":[92],"This":[93],"comprises":[95],"detailed":[96],"descriptions":[97],"accidents,":[99],"sensor":[100],"information,":[101],"other":[103],"critical":[104],"parameters.":[105],"Moreover,":[106],"we":[107,144,154,178],"have":[108],"introduced":[109],"approach":[112],"called":[113],"Multi-Distance":[114],"Synthetic":[115],"Technique":[116],"(MDST)":[117],"balance":[119],"imbalanced":[121],"nature":[122],"dataset,":[125],"which":[126,183],"included":[127],"only":[128],"334":[129],"samples":[130],"due":[131],"rarity":[134],"such":[136],"data.":[138],"Utilizing":[139],"MDST":[140],"data":[142],"balancing,":[143],"aimed":[145],"enhance":[147],"robustness":[149],"analysis.":[152],"Additionally,":[153],"Recursive":[156],"Feature":[157],"Selection":[158],"(RFS)":[159],"extract":[161],"valuable":[163],"feature":[164,176],"set":[165],"that":[166],"was":[167],"predicting":[170],"severity.":[172],"Leveraging":[173],"selected":[175],"set,":[177],"trained":[179],"ensemble":[181],"model,":[182],"remarkably":[184],"outperformed":[185],"expectations,":[186],"achieving":[187],"impressive":[189],"accuracy":[190],"score":[191],"0.92.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":11}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}