{"id":"https://openalex.org/W4380607149","doi":"https://doi.org/10.1109/tits.2023.3265007","title":"Fuel Rate Prediction for Heavy-Duty Trucks","display_name":"Fuel Rate Prediction for Heavy-Duty Trucks","publication_year":2023,"publication_date":"2023-06-14","ids":{"openalex":"https://openalex.org/W4380607149","doi":"https://doi.org/10.1109/tits.2023.3265007"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3265007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3265007","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":["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/A5039156669","display_name":"Liangkai Liu","orcid":"https://orcid.org/0000-0002-6149-9859"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liangkai Liu","raw_affiliation_strings":["Department of Computer Science, Wayne State University, Detroit, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-6149-9859","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347664","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-3654-0335"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Inceptio, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inceptio, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019585260","display_name":"Dawei Wang","orcid":"https://orcid.org/0000-0003-2440-220X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Dawei Wang","raw_affiliation_strings":["Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-2440-220X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021066503","display_name":"Yi Wu","orcid":"https://orcid.org/0000-0002-2322-6825"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wu","raw_affiliation_strings":["College of Automation and the College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Automation and the College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076524203","display_name":"Ruigang Yang","orcid":"https://orcid.org/0000-0001-5296-6307"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruigang Yang","raw_affiliation_strings":["Inceptio, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inceptio, Shanghai, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100651611","display_name":"Weisong Shi","orcid":"https://orcid.org/0000-0001-5864-4675"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weisong Shi","raw_affiliation_strings":["Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA"],"raw_orcid":"https://orcid.org/0000-0001-5864-4675","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA","institution_ids":["https://openalex.org/I86501945"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5039156669"],"corresponding_institution_ids":["https://openalex.org/I185443292"],"apc_list":null,"apc_paid":null,"fwci":1.0857,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.75904124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"24","issue":"8","first_page":"8222","last_page":"8235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9998000264167786,"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":0.9998000264167786,"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/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9943000078201294,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.8871294260025024},{"id":"https://openalex.org/keywords/heavy-duty","display_name":"Heavy duty","score":0.7098454236984253},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5311732888221741},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.4638156294822693},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2853163480758667}],"concepts":[{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.8871294260025024},{"id":"https://openalex.org/C2993573757","wikidata":"https://www.wikidata.org/wiki/Q3784054","display_name":"Heavy duty","level":2,"score":0.7098454236984253},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5311732888221741},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.4638156294822693},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2853163480758667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3265007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3265007","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1589221021","https://openalex.org/W1591801644","https://openalex.org/W1979719437","https://openalex.org/W2002102776","https://openalex.org/W2048113012","https://openalex.org/W2074639699","https://openalex.org/W2089177739","https://openalex.org/W2102605133","https://openalex.org/W2145680191","https://openalex.org/W2151477633","https://openalex.org/W2151635408","https://openalex.org/W2157525649","https://openalex.org/W2171928131","https://openalex.org/W2180642879","https://openalex.org/W2298180549","https://openalex.org/W2525739395","https://openalex.org/W2726123582","https://openalex.org/W2765811365","https://openalex.org/W2775283290","https://openalex.org/W2919700208","https://openalex.org/W2948594009","https://openalex.org/W2963684088","https://openalex.org/W2964024268","https://openalex.org/W2977248525","https://openalex.org/W2987078782","https://openalex.org/W3016163932","https://openalex.org/W3030488317","https://openalex.org/W3045940927","https://openalex.org/W3087669446","https://openalex.org/W3096831136","https://openalex.org/W3157889433","https://openalex.org/W3159736609","https://openalex.org/W4213308398","https://openalex.org/W4230523054","https://openalex.org/W4255421341","https://openalex.org/W4302308043","https://openalex.org/W6635446068","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6685961532","https://openalex.org/W6773884966","https://openalex.org/W6800495581"],"related_works":["https://openalex.org/W2362148937","https://openalex.org/W627398415","https://openalex.org/W4252019847","https://openalex.org/W4254204236","https://openalex.org/W829935278","https://openalex.org/W4210551371","https://openalex.org/W2392119071","https://openalex.org/W2350722454","https://openalex.org/W2087328555","https://openalex.org/W754166688"],"abstract_inverted_index":{"Fuel":[0,64],"cost":[1,8],"contributes":[2],"significantly":[3],"to":[4,35,67,78,99,115,127,138],"the":[5,18,36,56,73,109,117,134,144],"high":[6],"operation":[7],"of":[9,20,75,119,121,136,147],"heavy-duty":[10,26],"trucks.":[11,27],"Developing":[12],"fuel":[13,21,38,102,148],"rate":[14,149],"prediction":[15,82,150],"models":[16,41,124],"is":[17],"cornerstone":[19],"consumption":[22],"optimization":[23],"approaches":[24],"for":[25,157],"However,":[28],"limited":[29],"by":[30],"accurate":[31],"features":[32],"directly":[33],"related":[34],"truck\u2019s":[37,57],"consumption,":[39],"state-of-the-art":[40],"show":[42,107],"poor":[43],"performance":[44],"and":[45,62,93,97,111,154],"are":[46,95],"rarely":[47],"deployed":[48],"in":[49],"practice.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,142],"use":[55],"engine":[58],"management":[59],"system":[60],"(EMS)":[61],"Instant":[63],"Meter":[65],"(IFM)":[66],"collect":[68],"a":[69],"three-month":[70],"dataset":[71,113],"during":[72],"period":[74],"December":[76],"2019":[77],"June":[79],"2020.":[80],"Seven":[81],"models,":[83],"including":[84],"linear":[85],"regression,":[86,88],"polynomial":[87],"MLP,":[89],"CNN,":[90],"LSTM,":[91],"CNN-LSTM,":[92],"AutoML,":[94],"investigated":[96],"evaluated":[98],"predict":[100],"real-time":[101],"rate.":[103],"The":[104],"evaluation":[105],"results":[106],"that":[108],"EMS":[110],"IFM":[112],"help":[114],"improve":[116],"coefficient":[118,135],"determination":[120,137],"traditional":[122],"linear/polynomial":[123],"from":[125],"0.87":[126],"0.96,":[128],"while":[129],"learning-based":[130],"approach":[131],"AutoML":[132],"improves":[133],"attain":[139],"0.99.":[140],"Besides,":[141],"explore":[143],"actual":[145],"deployment":[146],"with":[151],"transfer":[152],"learning":[153],"path":[155],"planning":[156],"autonomous":[158],"driving.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}