{"id":"https://openalex.org/W2991212029","doi":"https://doi.org/10.1109/tits.2019.2954183","title":"Driver Danger-Level Monitoring System Using Multi-Sourced Big Driving Data","display_name":"Driver Danger-Level Monitoring System Using Multi-Sourced Big Driving Data","publication_year":2019,"publication_date":"2019-11-27","ids":{"openalex":"https://openalex.org/W2991212029","doi":"https://doi.org/10.1109/tits.2019.2954183","mag":"2991212029"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2954183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2954183","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","raw_type":"journal-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/A5079784316","display_name":"Jia-Li Yin","orcid":"https://orcid.org/0000-0002-8087-9769"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Li Yin","raw_affiliation_strings":["Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan","Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]},{"raw_affiliation_string":"Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003990275","display_name":"Bo\u2010Hao Chen","orcid":"https://orcid.org/0000-0002-7999-3396"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bo-Hao Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan","Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-7999-3396","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]},{"raw_affiliation_string":"Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044292096","display_name":"K. Robert Lai","orcid":"https://orcid.org/0000-0002-3365-3927"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kuo-Hua Robert Lai","raw_affiliation_strings":["Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-3365-3927","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99908691"],"apc_list":null,"apc_paid":null,"fwci":1.6013,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.83207665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"21","issue":"12","first_page":"5271","last_page":"5282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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":0.9998999834060669,"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/T10370","display_name":"Traffic and Road Safety","score":0.9986000061035156,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9955000281333923,"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/variety","display_name":"Variety (cybernetics)","score":0.8032199144363403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5742800235748291},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5631780624389648},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.49087435007095337},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.4735870957374573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3994004726409912},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3455032706260681},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32765406370162964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.318434476852417}],"concepts":[{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.8032199144363403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5742800235748291},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5631780624389648},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.49087435007095337},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4735870957374573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3994004726409912},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3455032706260681},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32765406370162964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.318434476852417},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2954183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2954183","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2110824475","display_name":"Lossless Image Power-Constrained Algorithm for Display System on Mobile Devices","funder_award_id":"MOST108-2221-E155-034-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G4175826614","display_name":"Investigation on Driving Behavior Recognition and Monitoring Algorithm for Next Generation Driver Assistance System","funder_award_id":"MOST107-2221-E155-052-MY2","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W181929850","https://openalex.org/W1504178287","https://openalex.org/W1505840745","https://openalex.org/W1975484590","https://openalex.org/W2006290150","https://openalex.org/W2052123415","https://openalex.org/W2052770734","https://openalex.org/W2058899199","https://openalex.org/W2084217799","https://openalex.org/W2100798515","https://openalex.org/W2103618108","https://openalex.org/W2108920441","https://openalex.org/W2110801681","https://openalex.org/W2118223742","https://openalex.org/W2126105956","https://openalex.org/W2127624552","https://openalex.org/W2128678906","https://openalex.org/W2143381319","https://openalex.org/W2144330966","https://openalex.org/W2146976664","https://openalex.org/W2148933727","https://openalex.org/W2151005775","https://openalex.org/W2153762265","https://openalex.org/W2159132531","https://openalex.org/W2165171393","https://openalex.org/W2171801645","https://openalex.org/W2177486042","https://openalex.org/W2177953264","https://openalex.org/W2325060691","https://openalex.org/W2343970958","https://openalex.org/W2548005016","https://openalex.org/W2556398113","https://openalex.org/W2568320856","https://openalex.org/W2571783659","https://openalex.org/W2621443519","https://openalex.org/W2765992395","https://openalex.org/W2792776757","https://openalex.org/W2896342389","https://openalex.org/W6630398147"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W4233347783","https://openalex.org/W2910064364","https://openalex.org/W4255224757","https://openalex.org/W4382644535"],"abstract_inverted_index":{"Danger-level":[0],"analysis":[1,15,24,37,54,82,120],"is":[2,16,25,55,121,134],"widely":[3],"used":[4],"to":[5,59,142],"prevent":[6],"potential":[7],"driving":[8,12,32,47,72,95,111,157,179],"risks":[9],"based":[10],"on":[11],"performance.":[13,21],"Such":[14,53],"essential":[17],"for":[18,27,84,113,177],"monitoring":[19],"driver":[20],"Moreover,":[22],"danger-level":[23,36,81,119],"vital":[26],"automotive":[28],"safety":[29],"systems":[30],"and":[31,43,67,89],"assistance":[33],"applications.":[34],"However,":[35],"that":[38,168],"simultaneously":[39],"considers":[40],"driver-,":[41],"vehicle-,":[42],"road-related":[44],"information":[45],"from":[46,155],"data":[48,158],"has":[49],"rarely":[50],"been":[51],"conducted.":[52],"very":[56],"challenging":[57],"due":[58],"the":[60,64,104,115,144,148,161,169],"issues":[61],"associated":[62],"with":[63,86],"high":[65,68,87,90],"volume":[66,91,145],"variety":[69,88,116],"in":[70,103,128],"multisourced":[71,94,110,156,178],"data.":[73,96,180],"In":[74],"this":[75],"paper,":[76],"we":[77,107],"propose":[78],"a":[79,99,124,129,138],"novel":[80],"framework":[83,171],"dealing":[85],"problems":[92],"of":[93],"Built":[97],"upon":[98],"feature":[100],"extraction":[101],"method":[102],"proposed":[105,162,170],"framework,":[106],"first":[108],"profile":[109],"features":[112],"overcoming":[114],"problem.":[117],"Next,":[118],"formulated":[122],"as":[123],"multiobjective":[125],"pursuit":[126],"problem":[127,133],"linear":[130],"model.":[131],"The":[132,164],"then":[135],"solved":[136],"using":[137,160],"semisupervised":[139],"learning":[140,175],"strategy":[141],"overcome":[143],"issue.":[146],"Therefore,":[147],"danger":[149],"level":[150],"can":[151],"be":[152],"accurately":[153],"estimated":[154],"by":[159],"framework.":[163],"experimental":[165],"results":[166],"indicate":[167],"outperforms":[172],"existing":[173],"machine":[174],"techniques":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
