{"id":"https://openalex.org/W2757457009","doi":"https://doi.org/10.1109/itsc.2017.8317716","title":"Towards a real-time driver identification mechanism based on driving sensing data","display_name":"Towards a real-time driver identification mechanism based on driving sensing data","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2757457009","doi":"https://doi.org/10.1109/itsc.2017.8317716","mag":"2757457009"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2017.8317716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th 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/A5091262858","display_name":"Sasan Jafarnejad","orcid":"https://orcid.org/0000-0003-2289-1425"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":true,"raw_author_name":"Sasan Jafarnejad","raw_affiliation_strings":["Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004262628","display_name":"German Castignani","orcid":"https://orcid.org/0000-0001-5594-4904"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"German Castignani","raw_affiliation_strings":["Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009071576","display_name":"Thomas Engel","orcid":"https://orcid.org/0000-0002-7374-3927"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Thomas Engel","raw_affiliation_strings":["Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"Interdiscipl. Centre for Security, Reliability & Trust (SnT), Univ. of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091262858"],"corresponding_institution_ids":["https://openalex.org/I186903577"],"apc_list":null,"apc_paid":null,"fwci":2.8519,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.91433901,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"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":0.9995999932289124,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9952999949455261,"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/computer-science","display_name":"Computer science","score":0.7142577767372131},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5412506461143494},{"id":"https://openalex.org/keywords/telematics","display_name":"Telematics","score":0.5135217308998108},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5011706352233887},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.478523850440979},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4723968207836151},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.44826069474220276},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44256168603897095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4009197950363159},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3987797796726227},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10291057825088501}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7142577767372131},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5412506461143494},{"id":"https://openalex.org/C89074322","wikidata":"https://www.wikidata.org/wiki/Q485669","display_name":"Telematics","level":2,"score":0.5135217308998108},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5011706352233887},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.478523850440979},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4723968207836151},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.44826069474220276},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44256168603897095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4009197950363159},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3987797796726227},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10291057825088501},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2017.8317716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:orbilu.uni.lu:10993/32359","is_oa":false,"landing_page_url":"https://orbilu.uni.lu/handle/10993/32359","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"20th International Conference on Intelligent Transportation Systems (ITSC), 7 (2017); 20th International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan [JP], from 16-10-2017 to 19-10-2017","raw_type":"peer reviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W151603506","https://openalex.org/W1529355025","https://openalex.org/W1931305913","https://openalex.org/W1944886505","https://openalex.org/W1952871627","https://openalex.org/W1972441921","https://openalex.org/W2084044763","https://openalex.org/W2098824882","https://openalex.org/W2100805904","https://openalex.org/W2101234009","https://openalex.org/W2109606373","https://openalex.org/W2160595088","https://openalex.org/W2169060624","https://openalex.org/W2231673834","https://openalex.org/W2286343943","https://openalex.org/W6675061970","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561","https://openalex.org/W1502951582"],"abstract_inverted_index":{"The":[0,64],"growing":[1],"penetration":[2],"of":[3,15,34,114,117,180,193],"telematics":[4,26],"systems":[5],"and":[6,21,42,67,78,81,101,129,161],"connectivity":[7],"in":[8,32,61,71,196,201],"vehicles":[9],"has":[10],"enabled":[11],"a":[12,49,72,91,95,103,202],"large":[13],"variety":[14],"possible":[16],"value-added":[17],"services":[18],"for":[19,51,86,106,158,174],"drivers":[20,176,195,204],"service":[22],"providers.":[23],"In":[24,178],"particular":[25],"based":[27,54],"real-time":[28,181],"driver":[29,52,84],"identification":[30,53,85,121,145,182],"is":[31,187],"interest":[33],"entities":[35],"such":[36],"as":[37],"insurance":[38],"companies,":[39],"car":[40],"rentals":[41],"public":[43],"transportation":[44],"fleet":[45],"managers.":[46],"We":[47,110,149],"propose":[48],"mechanism":[50],"on":[55,120],"driving":[56],"dynamics":[57],"signals":[58],"currently":[59],"available":[60],"production":[62],"cars.":[63],"system":[65,186],"collects":[66],"filters":[68],"sensing":[69],"data":[70],"sliding":[73,124],"window":[74,88,125],"iteration,":[75],"computes":[76],"statistical":[77],"spectral":[79],"features":[80],"finally":[82],"provides":[83],"each":[87],"frame":[89],"through":[90],"classification":[92],"process.":[93],"Finally,":[94],"decision":[96],"function":[97],"takes":[98],"individual":[99],"predictions":[100,157],"outputs":[102],"single":[104],"prediction":[105],"the":[107,112,118,162,184,194],"ongoing":[108],"trip.":[109],"evaluate":[111],"impact":[113],"various":[115],"elements":[116],"process":[119],"accuracy,":[122],"including":[123],"size,":[126],"classifier":[127],"algorithms":[128],"feature":[130],"sets.":[131],"Results":[132],"show":[133,151],"that":[134,152],"complementing":[135],"gas":[136],"pedal":[137],"signal":[138],"with":[139,170],"steering":[140],"wheel":[141],"cepstral":[142],"analysis":[143],"improves":[144],"accuracy":[146],"by":[147],"22.4%.":[148],"also":[150],"Boosting":[153],"classifiers":[154],"provide":[155],"better":[156],"our":[159],"problem":[160],"best":[163],"results":[164],"have":[165],"been":[166],"achieved":[167],"using":[168],"AdaBoost":[169],"95,89,82":[171],"percent":[172],"accuracies":[173],"5,15,35":[175],"respectively.":[177],"terms":[179],"performance,":[183],"proposed":[185],"able":[188],"to":[189],"correctly":[190],"identify":[191],"75%":[192],"less":[197],"than":[198],"65":[199],"s":[200],"5":[203],"scenario.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}