{"id":"https://openalex.org/W4296558723","doi":"https://doi.org/10.1109/tmc.2022.3208265","title":"$\\mathtt {Radar}$: Adversarial Driving Style Representation Learning With Data Augmentation","display_name":"$\\mathtt {Radar}$: Adversarial Driving Style Representation Learning With Data Augmentation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296558723","doi":"https://doi.org/10.1109/tmc.2022.3208265"},"language":"en","primary_location":{"id":"doi:10.1109/tmc.2022.3208265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2022.3208265","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","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/A5065782705","display_name":"Zhidan Liu","orcid":"https://orcid.org/0000-0002-0211-877X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhidan Liu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-0211-877X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036475202","display_name":"Junhong Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhong Zheng","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020960309","display_name":"Jinye Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinye Lin","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456543","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0002-5897-4401"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0002-5897-4401","affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001188748","display_name":"Kaishun Wu","orcid":"https://orcid.org/0000-0003-2216-0737"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaishun Wu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2216-0737","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065782705"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.3917,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.57472249,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983000159263611,"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":0.9983000159263611,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9932000041007996,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6602532863616943},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.6310466527938843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6116148829460144},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.578709065914154},{"id":"https://openalex.org/keywords/alias","display_name":"Alias","score":0.5114651918411255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49942731857299805},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.49680212140083313},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4257204234600067},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3322600722312927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2196219563484192},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21433326601982117},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.10635170340538025}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6602532863616943},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.6310466527938843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6116148829460144},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.578709065914154},{"id":"https://openalex.org/C46681722","wikidata":"https://www.wikidata.org/wiki/Q4725589","display_name":"Alias","level":2,"score":0.5114651918411255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49942731857299805},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.49680212140083313},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4257204234600067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3322600722312927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2196219563484192},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21433326601982117},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.10635170340538025},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmc.2022.3208265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2022.3208265","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","raw_type":"journal-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-133483","is_oa":false,"landing_page_url":"https://repository.hkust.edu.hk/ir/Record/1783.1-133483","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W1527702126","https://openalex.org/W1968701380","https://openalex.org/W1991801742","https://openalex.org/W2068997453","https://openalex.org/W2096733369","https://openalex.org/W2103568877","https://openalex.org/W2108263314","https://openalex.org/W2126194848","https://openalex.org/W2135822894","https://openalex.org/W2162833336","https://openalex.org/W2165232124","https://openalex.org/W2343480289","https://openalex.org/W2412510955","https://openalex.org/W2479935243","https://openalex.org/W2522004770","https://openalex.org/W2539417147","https://openalex.org/W2578339457","https://openalex.org/W2586847113","https://openalex.org/W2619371851","https://openalex.org/W2761751533","https://openalex.org/W2768061942","https://openalex.org/W2782078221","https://openalex.org/W2786973885","https://openalex.org/W2791677100","https://openalex.org/W2792440251","https://openalex.org/W2808113502","https://openalex.org/W2808766325","https://openalex.org/W2886287742","https://openalex.org/W2895746990","https://openalex.org/W2897668826","https://openalex.org/W2912870707","https://openalex.org/W2948401540","https://openalex.org/W2959675813","https://openalex.org/W2963373786","https://openalex.org/W2963535483","https://openalex.org/W2964092202","https://openalex.org/W2974739964","https://openalex.org/W3005144376","https://openalex.org/W3006838039","https://openalex.org/W3007103823","https://openalex.org/W3008872739","https://openalex.org/W3020256244","https://openalex.org/W3024061508","https://openalex.org/W3029550486","https://openalex.org/W3035308866","https://openalex.org/W3037504576","https://openalex.org/W3046296398","https://openalex.org/W3080657898","https://openalex.org/W3090971127","https://openalex.org/W3112483519","https://openalex.org/W3118519864","https://openalex.org/W3119906317","https://openalex.org/W3128835168","https://openalex.org/W3129829771","https://openalex.org/W3130684690","https://openalex.org/W3132889715","https://openalex.org/W3134343811","https://openalex.org/W3140035367","https://openalex.org/W3146169861","https://openalex.org/W3150200192","https://openalex.org/W3167628356","https://openalex.org/W3178411657","https://openalex.org/W3199966054","https://openalex.org/W4200440619","https://openalex.org/W4287330027","https://openalex.org/W4320013936","https://openalex.org/W6630424276","https://openalex.org/W6676249281","https://openalex.org/W6684050148","https://openalex.org/W6715189028","https://openalex.org/W6718379498","https://openalex.org/W6721527053","https://openalex.org/W6727056986","https://openalex.org/W6738597727","https://openalex.org/W6773950905","https://openalex.org/W6780093649","https://openalex.org/W6790697996","https://openalex.org/W6790709279"],"related_works":["https://openalex.org/W4385605198","https://openalex.org/W4256550813","https://openalex.org/W2056017980","https://openalex.org/W2333004434","https://openalex.org/W2151266859","https://openalex.org/W1557487237","https://openalex.org/W2502115930","https://openalex.org/W275149381","https://openalex.org/W4386805122","https://openalex.org/W613665429"],"abstract_inverted_index":{"Characterizing":[0],"human":[1],"driver's":[2],"driving":[3,27,39,45,81,92,163,243],"behaviors":[4],"from":[5,110,123,166],"GPS":[6,22,54,112,168,222],"trajectories":[7,55],"is":[8,158],"an":[9,90],"important":[10],"yet":[11],"challenging":[12],"trajectory":[13,169,223],"mining":[14],"task.":[15],"Previous":[16],"works":[17,63],"heavily":[18],"rely":[19],"on":[20,204],"high-quality":[21],"data":[23,49,77,187,191,200],"to":[24,78,106,142,160],"learn":[25,79,162],"such":[26],"style":[28,82,93,164,244],"representations":[29,165],"through":[30],"deep":[31],"neural":[32],"networks.":[33],"However,":[34],"they":[35],"have":[36,75],"overlooked":[37],"the":[38,48,65,70,136,155,234],"contexts":[40],"that":[41,226],"greatly":[42],"govern":[43],"drivers'":[44],"activities":[46],"and":[47,131,152,194,214,241],"sparsity":[50],"issue":[51],"of":[52,126],"practical":[53,167],"collected":[56],"at":[57],"a":[58,195,219],"low-sampling":[59],"rate.":[60],"Besides,":[61],"existing":[62],"omit":[64],"cold":[66],"start":[67],"problem,":[68],"where":[69],"newly":[71],"joined":[72],"drivers":[73,183],"usually":[74],"insufficient":[76],"accurate":[80,242],"representations.":[83,245],"To":[84],"address":[85],"these":[86],"limitations,":[87],"we":[88,172],"present":[89],"adversarial":[91,140],"representation":[94,180],"learning":[95,145,181,238],"approach,":[96],"named":[97],"<inline-formula":[98,114,174,227],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[99,115,175,209,228],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[100,116,176,229],"notation=\"LaTeX\">$\\mathtt":[101,117,177,230],"{Radar}$</tex-math></inline-formula>":[102,118,178,231],".":[103],"In":[104],"addition":[105],"summarizing":[107],"statistic":[108,150],"features":[109,122,151],"raw":[111],"data,":[113],"also":[119],"extracts":[120],"contextual":[121,153],"three":[124],"aspects":[125],"road":[127],"condition,":[128],"geographic":[129],"semantic,":[130],"traffic":[132],"condition.":[133],"We":[134],"exploit":[135],"advanced":[137],"semi-supervised":[138],"generative":[139],"networks":[141],"construct":[143],"our":[144],"model.":[146],"By":[147],"jointly":[148],"considering":[149],"features,":[154],"trained":[156],"model":[157],"able":[159],"efficiently":[161],"data.":[170],"Furthermore,":[171],"enhance":[173],"'s":[179],"for":[182],"owning":[184],"limited":[185],"training":[186],"with":[188,218],"some":[189],"basic":[190],"augmentation":[192,201],"strategies":[193],"novel":[196],"auxiliary":[197],"driver":[198,212,215],"based":[199],"method.":[202],"Experiments":[203],"two":[205],"benchmark":[206],"applications,":[207],"<italic":[208],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e.</i>":[210],",":[211],"identification":[213],"number":[216],"estimation,":[217],"large":[220],"real-world":[221],"dataset":[224],"demonstrate":[225],"can":[232],"outperform":[233],"state-of-the-art":[235],"approaches":[236],"by":[237],"more":[239],"effective":[240]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2022-09-21T00:00:00"}
