{"id":"https://openalex.org/W2772972874","doi":"https://doi.org/10.1109/thms.2017.2776605","title":"Risky Driver Recognition Based on Vehicle Speed Time Series","display_name":"Risky Driver Recognition Based on Vehicle Speed Time Series","publication_year":2017,"publication_date":"2017-12-13","ids":{"openalex":"https://openalex.org/W2772972874","doi":"https://doi.org/10.1109/thms.2017.2776605","mag":"2772972874"},"language":"en","primary_location":{"id":"doi:10.1109/thms.2017.2776605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2017.2776605","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine 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/A5074752977","display_name":"Dajun Wang","orcid":"https://orcid.org/0000-0003-0372-8999"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dajun Wang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0372-8999","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636075","display_name":"Xin Pei","orcid":"https://orcid.org/0000-0003-3807-2264"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Pei","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114911316","display_name":"Li Li","orcid":"https://orcid.org/0000-0002-9428-1960"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["Department of Automation, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9428-1960","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081663090","display_name":"Danya Yao","orcid":"https://orcid.org/0000-0001-5032-6322"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danya Yao","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.4282,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.84774296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"48","issue":"1","first_page":"63","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9977999925613403,"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":0.9977999925613403,"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":0.996999979019165,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9961000084877014,"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/computer-science","display_name":"Computer science","score":0.6422074437141418},{"id":"https://openalex.org/keywords/traffic-speed","display_name":"Traffic speed","score":0.5946659445762634},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5596534013748169},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.4834538400173187},{"id":"https://openalex.org/keywords/speed-measurement","display_name":"Speed measurement","score":0.4591995179653168},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.456196129322052},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4412078857421875},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3581300675868988},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2604151964187622},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2173328399658203},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1941392719745636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13034680485725403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6422074437141418},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.5946659445762634},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5596534013748169},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.4834538400173187},{"id":"https://openalex.org/C2987320957","wikidata":"https://www.wikidata.org/wiki/Q2041172","display_name":"Speed measurement","level":2,"score":0.4591995179653168},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.456196129322052},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4412078857421875},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3581300675868988},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2604151964187622},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2173328399658203},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1941392719745636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13034680485725403},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/thms.2017.2776605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2017.2776605","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6853452163","display_name":null,"funder_award_id":"91520301","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W74920699","https://openalex.org/W1503398984","https://openalex.org/W1842501785","https://openalex.org/W1970436864","https://openalex.org/W1997236834","https://openalex.org/W2006820723","https://openalex.org/W2011430131","https://openalex.org/W2012232229","https://openalex.org/W2015463731","https://openalex.org/W2019836660","https://openalex.org/W2024501962","https://openalex.org/W2036563674","https://openalex.org/W2038962921","https://openalex.org/W2044080979","https://openalex.org/W2052770734","https://openalex.org/W2056570754","https://openalex.org/W2102847084","https://openalex.org/W2126288068","https://openalex.org/W2139367509","https://openalex.org/W2151221872","https://openalex.org/W2174602916","https://openalex.org/W2324869184","https://openalex.org/W2333777777","https://openalex.org/W2345312465","https://openalex.org/W2574613120","https://openalex.org/W2799061466","https://openalex.org/W2799148064","https://openalex.org/W3023819769","https://openalex.org/W6603060881"],"related_works":["https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W629430645","https://openalex.org/W648495037","https://openalex.org/W560153893","https://openalex.org/W567114884","https://openalex.org/W2371966573","https://openalex.org/W1528244218"],"abstract_inverted_index":{"Risky":[0],"driving":[1,20],"is":[2,76,95],"a":[3,14],"major":[4],"cause":[5],"of":[6,37,63,69,80],"traffic":[7,99],"accidents.":[8],"In":[9],"this":[10,85],"paper,":[11],"we":[12],"propose":[13],"new":[15],"method":[16,30,86],"that":[17],"recognizes":[18],"risky":[19,57],"behaviors":[21],"purely":[22],"based":[23,59],"on":[24,60,78],"vehicle":[25],"speed":[26,51,74],"time":[27],"series.":[28],"This":[29],"first":[31],"retrieves":[32],"the":[33,38,56,67,70,81],"important":[34],"distribution":[35],"pattern":[36],"sampled":[39],"positive":[40],"speed-change":[41],"(value":[42],"and":[43,91,104],"duration)":[44],"tuples":[45],"for":[46],"individual":[47],"drivers":[48,58],"within":[49],"different":[50,61],"ranges.":[52],"Then,":[53],"it":[54],"identifies":[55],"patterns":[62],"drivers.":[64],"Tests":[65],"show":[66],"effectiveness":[68],"proposed":[71],"method.":[72],"Since":[73],"measurement":[75],"available":[77],"most":[79],"newly":[82],"build":[83],"vehicles,":[84],"can":[87],"be":[88],"easily":[89],"implemented":[90],"used.":[92],"The":[93],"conclusion":[94],"useful":[96],"to":[97],"many":[98],"applications,":[100],"e.g.,":[101],"driver":[102],"training":[103],"insurance":[105],"pricing.":[106]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
