{"id":"https://openalex.org/W4405429579","doi":"https://doi.org/10.1109/tits.2024.3509899","title":"Minimizing Emission for Timely Heavy-Duty Truck Transportation","display_name":"Minimizing Emission for Timely Heavy-Duty Truck Transportation","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405429579","doi":"https://doi.org/10.1109/tits.2024.3509899"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3509899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3509899","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/A5080531126","display_name":"Junyan Su","orcid":"https://orcid.org/0000-0002-6805-3833"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junyan Su","raw_affiliation_strings":["Department of Data Science, City University of Hong Kong, Kowloon, Hong Kong","Department of Data Science, City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6805-3833","affiliations":[{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079666403","display_name":"Runzhi Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Runzhi Zhou","raw_affiliation_strings":["Department of the School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of the School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669228","display_name":"Qingyu Liu","orcid":"https://orcid.org/0000-0003-1487-7682"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyu Liu","raw_affiliation_strings":["School of Electric and Computer Engineering, Shenzhen Graduate School, Peking University, Beijing, China","Shenzhen Graduate School, School of Electric and Computer Engineering, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1487-7682","affiliations":[{"raw_affiliation_string":"School of Electric and Computer Engineering, Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Shenzhen Graduate School, School of Electric and Computer Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005803135","display_name":"Wenjie Xu","orcid":"https://orcid.org/0000-0001-7475-0056"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Wenjie Xu","raw_affiliation_strings":["Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-7475-0056","affiliations":[{"raw_affiliation_string":"Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100602652","display_name":"Minghua Chen","orcid":"https://orcid.org/0000-0003-4763-0037"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Minghua Chen","raw_affiliation_strings":["Department of Data Science, City University of Hong Kong, Kowloon, Hong Kong","Department of Data Science, City University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-4763-0037","affiliations":[{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025405598","display_name":"Haibo Zeng","orcid":"https://orcid.org/0000-0003-1162-759X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibo Zeng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-1162-759X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3283,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5799543,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"26","issue":"2","first_page":"1454","last_page":"1469"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9997000098228455,"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":0.9997000098228455,"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/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9667999744415283,"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"}},{"id":"https://openalex.org/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.9555000066757202,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.8721754550933838},{"id":"https://openalex.org/keywords/heavy-duty","display_name":"Heavy duty","score":0.685189425945282},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.6331130266189575},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4280911982059479},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.35729920864105225},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3492403030395508},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3312980532646179},{"id":"https://openalex.org/keywords/aeronautics","display_name":"Aeronautics","score":0.32211750745773315}],"concepts":[{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.8721754550933838},{"id":"https://openalex.org/C2993573757","wikidata":"https://www.wikidata.org/wiki/Q3784054","display_name":"Heavy duty","level":2,"score":0.685189425945282},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.6331130266189575},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4280911982059479},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.35729920864105225},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3492403030395508},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3312980532646179},{"id":"https://openalex.org/C178802073","wikidata":"https://www.wikidata.org/wiki/Q8421","display_name":"Aeronautics","level":1,"score":0.32211750745773315}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3509899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3509899","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":[],"awards":[{"id":"https://openalex.org/G4507518585","display_name":null,"funder_award_id":"11206821","funder_id":"https://openalex.org/F4320321917","funder_display_name":"General Secretariat for Research and Technology"}],"funders":[{"id":"https://openalex.org/F4320321917","display_name":"General Secretariat for Research and Technology","ror":"https://ror.org/04yeh8h63"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W571614529","https://openalex.org/W1647519740","https://openalex.org/W1941866442","https://openalex.org/W1993074639","https://openalex.org/W1993939248","https://openalex.org/W1994644215","https://openalex.org/W2016339236","https://openalex.org/W2023071828","https://openalex.org/W2042872819","https://openalex.org/W2051054757","https://openalex.org/W2069197515","https://openalex.org/W2074117023","https://openalex.org/W2076370241","https://openalex.org/W2084744129","https://openalex.org/W2094311908","https://openalex.org/W2120575449","https://openalex.org/W2126043710","https://openalex.org/W2130626677","https://openalex.org/W2133990726","https://openalex.org/W2136181552","https://openalex.org/W2140556610","https://openalex.org/W2157009781","https://openalex.org/W2180642879","https://openalex.org/W2519221640","https://openalex.org/W2553233604","https://openalex.org/W2581545479","https://openalex.org/W2726123582","https://openalex.org/W2762828613","https://openalex.org/W2781474360","https://openalex.org/W2910908851","https://openalex.org/W2913740161","https://openalex.org/W2973272432","https://openalex.org/W2985559234","https://openalex.org/W2986766003","https://openalex.org/W3106612504","https://openalex.org/W3129782579","https://openalex.org/W4250589301","https://openalex.org/W4252476088","https://openalex.org/W4285502049","https://openalex.org/W4312732052","https://openalex.org/W4379162539","https://openalex.org/W6762732724","https://openalex.org/W6838743364","https://openalex.org/W6854837146"],"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":{"We":[0,146,180,199,256],"consider":[1],"the":[2,60,80,94,106,114,130,136,140,148,153,156,172,195,202,219,224,234,251],"problem":[3,131,175,187,222],"of":[4,7,105,117,139,226],"minimizing":[5],"emission":[6,53,61,83,95,220,247,268],"a":[8,18,27,31,120,124,161,166,177],"heavy-duty":[9,70],"truck":[10,23,157,283],"transporting":[11],"freight":[12],"between":[13],"two":[14,91],"locations":[15],"subject":[16],"to":[17,50,58,103,135,217,244,250,266,271,278],"hard":[19],"deadline":[20],"constraint.":[21],"The":[22],"is":[24,57,98,132],"equipped":[25],"with":[26,72],"multi-speed":[28,73],"transmission":[29,74],"and":[30,66,75,100,109,143,169,188,214],"modern":[32],"combustion":[33],"engine":[34,45],"that":[35,239,259],"intelligently":[36],"switches":[37],"among":[38],"multiple":[39,76],"fuel":[40,107],"injection":[41,77],"strategies":[42,78],"at":[43,119,160],"certain":[44],"speeds":[46],"(called":[47],"switching":[48,104],"speeds)":[49],"achieve":[51],"lower":[52],"profiles.":[54],"Our":[55,230],"objective":[56],"minimize":[59],"by":[62,151,205],"optimizing":[63,260],"both":[64,211],"path":[65,142,212,254],"speed":[67,122,144,163,173,197,215,262],"planning":[68,174,213,216],"for":[69,193,210],"trucks":[71],"in":[79,88,185,281],"engine.":[81],"This":[82],"minimization":[84,221],"problem,":[85],"while":[86],"pervasive":[87],"practice,":[89],"has":[90],"challenges:":[92],"i)":[93],"rate":[96],"function":[97],"discontinuous":[99],"non-convex":[101],"due":[102,134],"injections":[108],"gear":[110],"ratios,":[111],"which":[112],"makes":[113],"common":[115],"practice":[116],"driving":[118],"constant":[121],"on":[123,223,233],"road":[125,167],"segment":[126,168],"not":[127],"eco-friendly;":[128],"ii)":[129],"NP-hard":[133],"combinatorial":[137],"nature":[138],"simultaneous":[141],"planning.":[145],"tackle":[147,201],"first":[149],"challenge":[150,204],"considering":[152],"case":[154],"where":[155],"can":[158],"travel":[159],"heterogeneous":[162,261],"profile":[164],"over":[165],"then":[170,200],"formulate":[171],"as":[176,248,269],"convex":[178],"problem.":[179],"further":[181],"identify":[182],"special":[183],"structures":[184],"this":[186],"provide":[189],"an":[190,207],"efficient":[191,208],"method":[192],"computing":[194],"optimal":[196],"profile.":[198],"second":[203],"developing":[206],"heuristic":[209],"solve":[218],"scale":[225],"national":[227],"highway":[228,236],"systems.":[229],"extensive":[231],"simulations":[232],"US":[235],"system":[237],"show":[238],"our":[240],"solution":[241],"reduces":[242],"up":[243,265],"46%":[245],"NOx":[246],"compared":[249,270],"commonly-adopted":[252],"fastest":[253],"approach.":[255],"also":[257],"find":[258],"profiles":[263],"reduce":[264],"32%":[267],"their":[272],"homogeneous":[273],"counterpart,":[274],"thus":[275],"are":[276],"necessary":[277],"be":[279],"considered":[280],"eco-friendly":[282],"operations.":[284]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}