{"id":"https://openalex.org/W3031381725","doi":"https://doi.org/10.1109/tvt.2020.2997914","title":"Low-Cost Reconstruction of Typical Driving Cycles Based on Empirical Information and Low-Frequency Speed Data","display_name":"Low-Cost Reconstruction of Typical Driving Cycles Based on Empirical Information and Low-Frequency Speed Data","publication_year":2020,"publication_date":"2020-05-27","ids":{"openalex":"https://openalex.org/W3031381725","doi":"https://doi.org/10.1109/tvt.2020.2997914","mag":"3031381725"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.2997914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2997914","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5087920747","display_name":"Shuming Shi","orcid":"https://orcid.org/0000-0001-7018-0682"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuming Shi","raw_affiliation_strings":["School of Transportation, Jilin University, Chang Chun, China"],"affiliations":[{"raw_affiliation_string":"School of Transportation, Jilin University, Chang Chun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353064","display_name":"Man Zhang","orcid":"https://orcid.org/0000-0001-8648-9895"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210110558","display_name":"Xi'an Technological University","ror":"https://ror.org/01t8prc81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Man Zhang","raw_affiliation_strings":["School of Mechatronic Engineering, Xi'an Technological University, Xi'an","School of Transportation, Jilin University, Changchun, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Xi'an Technological University, Xi'an","institution_ids":["https://openalex.org/I4210110558"]},{"raw_affiliation_string":"School of Transportation, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085632247","display_name":"Nan Lin","orcid":"https://orcid.org/0000-0002-8331-6988"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Lin","raw_affiliation_strings":["School of Transportation, Jilin University, Chang Chun, China"],"affiliations":[{"raw_affiliation_string":"School of Transportation, Jilin University, Chang Chun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043943506","display_name":"Bingjian Yue","orcid":"https://orcid.org/0000-0003-1877-2167"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingjian Yue","raw_affiliation_strings":["School of Transportation, Jilin University, Chang Chun, China"],"affiliations":[{"raw_affiliation_string":"School of Transportation, Jilin University, Chang Chun, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087920747"],"corresponding_institution_ids":["https://openalex.org/I194450716"],"apc_list":null,"apc_paid":null,"fwci":0.6101,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.69334744,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"69","issue":"8","first_page":"8221","last_page":"8231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":1.0,"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/T12095","display_name":"Vehicle emissions and performance","score":1.0,"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/T10190","display_name":"Air Quality and Health Impacts","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/driving-cycle","display_name":"Driving cycle","score":0.666641354560852},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5520402789115906},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5485284924507141},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5237593650817871},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4973764717578888},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.48825696110725403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.481972873210907},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4498266279697418},{"id":"https://openalex.org/keywords/driving-range","display_name":"Driving range","score":0.411307156085968},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3698292672634125},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3517675995826721},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3084579110145569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15347641706466675},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.14771321415901184},{"id":"https://openalex.org/keywords/electric-vehicle","display_name":"Electric vehicle","score":0.14020085334777832}],"concepts":[{"id":"https://openalex.org/C169042556","wikidata":"https://www.wikidata.org/wiki/Q16246150","display_name":"Driving cycle","level":4,"score":0.666641354560852},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5520402789115906},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5485284924507141},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5237593650817871},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4973764717578888},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.48825696110725403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.481972873210907},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4498266279697418},{"id":"https://openalex.org/C2780847881","wikidata":"https://www.wikidata.org/wiki/Q3177122","display_name":"Driving range","level":4,"score":0.411307156085968},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3698292672634125},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3517675995826721},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3084579110145569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15347641706466675},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.14771321415901184},{"id":"https://openalex.org/C2776422217","wikidata":"https://www.wikidata.org/wiki/Q13629441","display_name":"Electric vehicle","level":3,"score":0.14020085334777832},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","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},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2020.2997914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.2997914","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G2732296003","display_name":null,"funder_award_id":"NSFCU1964202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6776333102","display_name":null,"funder_award_id":"NSFC51975242","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/W756271089","https://openalex.org/W1978662634","https://openalex.org/W1992341169","https://openalex.org/W2020143195","https://openalex.org/W2025707819","https://openalex.org/W2061740008","https://openalex.org/W2062235423","https://openalex.org/W2067279931","https://openalex.org/W2072284544","https://openalex.org/W2084708815","https://openalex.org/W2108386305","https://openalex.org/W2121373027","https://openalex.org/W2125118005","https://openalex.org/W2128553717","https://openalex.org/W2138987855","https://openalex.org/W2171275074","https://openalex.org/W2216448532","https://openalex.org/W2290076963","https://openalex.org/W2410777413","https://openalex.org/W2472191079","https://openalex.org/W2793915192","https://openalex.org/W2905470808","https://openalex.org/W2943131220","https://openalex.org/W2943565918","https://openalex.org/W3140461181","https://openalex.org/W4302391531","https://openalex.org/W6656883186","https://openalex.org/W6666015909","https://openalex.org/W6676399402"],"related_works":["https://openalex.org/W1739651088","https://openalex.org/W2964627364","https://openalex.org/W4210323698","https://openalex.org/W4312801853","https://openalex.org/W4280559757","https://openalex.org/W2789281155","https://openalex.org/W4365150880","https://openalex.org/W2997232532","https://openalex.org/W3016216301","https://openalex.org/W4327545682"],"abstract_inverted_index":{"A":[0],"representative":[1],"driving":[2,50,64,92,102,128,144,156,173,178,204,221],"cycle":[3,93],"is":[4,19,37,245],"crucial":[5],"to":[6,21,52,171],"estimating":[7],"emissions":[8],"and":[9,25,44,54,82,100,118,135,228,232,260],"energy":[10,252],"consumptions":[11],"of":[12,62,113,122,152,183,191,225,239,254],"vehicles.":[13,57],"However,":[14],"their":[15,56,226],"traditional":[16,79],"data":[17,51,182],"acquisition":[18],"subject":[20],"large":[22,60],"sampling":[23,185,209],"requirements":[24],"high":[26,216],"costs,":[27],"whether":[28],"a":[29,59,91,114,159,196,207,215,258],"chase-car":[30],"method":[31,36,81,95,117,163,176,249],"or":[32],"an":[33,119],"on-board":[34],"measurement":[35],"adopted.":[38],"Presently,":[39],"the":[40,70,78,111,123,141,153,166,188,192,202,211,219],"public":[41],"transportation":[42],"department":[43],"many":[45],"private":[46],"companies":[47],"collect":[48],"low-frequency":[49,101,124,181],"track":[53],"monitor":[55],"And":[58],"number":[61],"typical":[63,143],"cycles":[65,129,179,205,213,222],"have":[66,74,83],"been":[67,75,85],"generated":[68],"in":[69,223,257],"automobile":[71],"field,":[72],"which":[73],"limited":[76],"by":[77,132],"designed":[80],"not":[84],"fully":[86],"utilized.":[87],"Herein,":[88],"we":[89],"investigate":[90],"reconstruction":[94],"based":[96,109,139,164],"on":[97,110,140,165],"empirical":[98,150,167],"information":[99,151,168],"data.":[103,125],"First,":[104],"characteristic":[105,193],"parameters":[106,194],"were":[107,130,147],"selected,":[108],"ergodicity":[112],"Markov":[115,160],"Chain":[116,161],"interpolation":[120],"analysis":[121],"Second,":[126],"similar":[127],"grouped":[131],"K-means":[133],"clustering":[134],"principal":[136],"component":[137],"analysis,":[138],"existing":[142],"cycles.":[145,157,174],"These":[146],"considered":[148],"as":[149],"original":[154,203,220],"transient":[155],"Ultimately,":[158],"evolution":[162],"was":[169],"used":[170],"reconstruct":[172],"The":[175],"reconstructs":[177],"using":[180],"different":[184],"intervals,":[186],"keeping":[187],"relative":[189],"deviations":[190],"within":[195],"threshold":[197],"range.":[198],"In":[199],"comparison":[200],"with":[201,218],"having":[206],"1-s":[208],"interval,":[210],"reconstructed":[212],"exhibit":[214],"similarity":[217],"terms":[224],"velocity":[227],"acceleration":[229],"probability":[230],"distribution":[231],"power":[233],"spectral":[234],"density.":[235],"Additionally,":[236],"calculation":[237],"deviation":[238],"fuel":[240],"consumption":[241,253],"per":[242],"100":[243],"km":[244],"small.":[246],"Therefore,":[247],"this":[248],"can":[250],"estimate":[251],"urban":[255],"vehicles":[256],"timely":[259],"effective":[261],"manner.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
