{"id":"https://openalex.org/W2983192835","doi":"https://doi.org/10.1109/tits.2020.2970295","title":"Real-Time Sensor Anomaly Detection and Recovery in Connected Automated Vehicle Sensors","display_name":"Real-Time Sensor Anomaly Detection and Recovery in Connected Automated Vehicle Sensors","publication_year":2020,"publication_date":"2020-02-05","ids":{"openalex":"https://openalex.org/W2983192835","doi":"https://doi.org/10.1109/tits.2020.2970295","mag":"2983192835"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2020.2970295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2970295","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.01531","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100775829","display_name":"Yiyang Wang","orcid":"https://orcid.org/0000-0002-6478-7282"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yiyang Wang","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","University of Tennessee at Knoxville, TN 37996, USA","are with the University of Michigan, Ann Arbor, MI 48109, USA"],"raw_orcid":"https://orcid.org/0000-0002-6478-7282","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Tennessee at Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I75027704"]},{"raw_affiliation_string":"are with the University of Michigan, Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083290583","display_name":"Neda Masoud","orcid":"https://orcid.org/0000-0002-6526-3317"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neda Masoud","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA","are with the University of Michigan, Ann Arbor, MI 48109, USA","University of Tennessee at Knoxville, TN 37996, USA"],"raw_orcid":"https://orcid.org/0000-0002-6526-3317","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"are with the University of Michigan, Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Tennessee at Knoxville, TN 37996, USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005681030","display_name":"Anahita Khojandi","orcid":"https://orcid.org/0000-0001-6818-2048"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anahita Khojandi","raw_affiliation_strings":["University of Tennessee, Knoxville, TN, USA","are with the University of Michigan, Ann Arbor, MI 48109, USA"],"raw_orcid":"https://orcid.org/0000-0001-6818-2048","affiliations":[{"raw_affiliation_string":"University of Tennessee, Knoxville, TN, USA","institution_ids":["https://openalex.org/I75027704"]},{"raw_affiliation_string":"are with the University of Michigan, Ann Arbor, MI 48109, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100775829"],"corresponding_institution_ids":["https://openalex.org/I27837315","https://openalex.org/I75027704"],"apc_list":null,"apc_paid":null,"fwci":11.1433,"has_fulltext":false,"cited_by_count":167,"citation_normalized_percentile":{"value":0.98728399,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"22","issue":"3","first_page":"1411","last_page":"1421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9973000288009644,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/anomaly-detection","display_name":"Anomaly detection","score":0.6513797640800476},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5972613096237183},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5823574066162109},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5262869000434875},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4827975034713745},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4746594727039337},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.45122236013412476},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.43347272276878357},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4297511577606201},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4291931390762329},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.42432835698127747},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.421394407749176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35979944467544556},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3431662917137146},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.32973814010620117},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17838388681411743},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.08625787496566772}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6513797640800476},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5972613096237183},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5823574066162109},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5262869000434875},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4827975034713745},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4746594727039337},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.45122236013412476},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.43347272276878357},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4297511577606201},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4291931390762329},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.42432835698127747},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.421394407749176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35979944467544556},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3431662917137146},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.32973814010620117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17838388681411743},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.08625787496566772},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"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":2,"locations":[{"id":"doi:10.1109/tits.2020.2970295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2970295","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"},{"id":"pmh:oai:arXiv.org:1911.01531","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.01531","pdf_url":"https://arxiv.org/pdf/1911.01531","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.01531","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.01531","pdf_url":"https://arxiv.org/pdf/1911.01531","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W87635799","https://openalex.org/W159748277","https://openalex.org/W1521507142","https://openalex.org/W1965455100","https://openalex.org/W1965606617","https://openalex.org/W1969729144","https://openalex.org/W1971918058","https://openalex.org/W1973581271","https://openalex.org/W1993470778","https://openalex.org/W2003827925","https://openalex.org/W2010922160","https://openalex.org/W2014297741","https://openalex.org/W2019837559","https://openalex.org/W2023835067","https://openalex.org/W2038505590","https://openalex.org/W2039491987","https://openalex.org/W2048312361","https://openalex.org/W2097876126","https://openalex.org/W2099005886","https://openalex.org/W2102832680","https://openalex.org/W2111184007","https://openalex.org/W2116520617","https://openalex.org/W2129078811","https://openalex.org/W2132870739","https://openalex.org/W2133854595","https://openalex.org/W2139638562","https://openalex.org/W2150015649","https://openalex.org/W2160452173","https://openalex.org/W2163573608","https://openalex.org/W2295628043","https://openalex.org/W2537364430","https://openalex.org/W2549079146","https://openalex.org/W2553151007","https://openalex.org/W2578404781","https://openalex.org/W2591996318","https://openalex.org/W2617994934","https://openalex.org/W2725499676","https://openalex.org/W2740214584","https://openalex.org/W2765859232","https://openalex.org/W2941511030","https://openalex.org/W2945434604","https://openalex.org/W2969995408","https://openalex.org/W3124885228","https://openalex.org/W4297938851","https://openalex.org/W6603557143","https://openalex.org/W6606535463","https://openalex.org/W6641713732","https://openalex.org/W6674615465"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,34],"propose":[4],"a":[5,46,50,94,145,156,165,171],"novel":[6],"observer-based":[7],"method":[8,24,154],"to":[9,41,70,89,128],"improve":[10],"the":[11,55,58,62,66,87,91,100,111,114,125,142,175],"safety":[12],"and":[13,17,29,103],"security":[14],"of":[15,45,93,113],"connected":[16],"automated":[18],"vehicle":[19,60,95],"(CAV)":[20],"transportation.":[21],"The":[22],"proposed":[23,153],"combines":[25],"model-based":[26],"signal":[27],"filtering":[28],"anomaly":[30,158],"detection":[31,159,177],"methods.":[32],"Specifically,":[33],"use":[35],"adaptive":[36],"extended":[37],"Kalman":[38],"filter":[39],"(AEKF)":[40],"smooth":[42],"sensor":[43,72],"readings":[44],"CAV":[47],"based":[48,98],"on":[49,99,174],"nonlinear":[51],"car-following":[52,56,126],"model.":[53],"Using":[54],"model":[57,127],"subject":[59],"(i.e.,":[61],"following":[63],"vehicle)":[64],"utilizes":[65],"leading":[67],"vehicle's":[68,101],"information":[69],"detect":[71],"anomalies":[73],"by":[74,107],"employing":[75],"previously-trained":[76],"One":[77],"Class":[78],"Support":[79],"Vector":[80],"Machine":[81],"(OCSVM)":[82],"models.":[83],"This":[84],"approach":[85],"allows":[86],"AEKF":[88,143],"estimate":[90],"state":[92,112],"not":[96],"only":[97],"location":[102],"speed,":[104],"but":[105],"also":[106,162],"taking":[108],"into":[109],"account":[110],"surrounding":[115],"traffic.":[116],"A":[117],"communication":[118],"time":[119,167],"delay":[120,168],"factor":[121,169],"is":[122],"considered":[123],"in":[124],"make":[129],"it":[130],"more":[131],"suitable":[132],"for":[133],"real-world":[134],"applications.":[135],"Our":[136],"experiments":[137],"show":[138],"that":[139,164],"compared":[140],"with":[141,144],"traditional":[146],"x":[147],"<sup":[148],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[149],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[150],"-detector,":[151],"our":[152],"achieves":[155],"better":[157],"performance.":[160,178],"We":[161],"demonstrate":[163],"larger":[166],"has":[170],"negative":[172],"impact":[173],"overall":[176]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":43},{"year":2023,"cited_by_count":36},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":9}],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2019-11-22T00:00:00"}
