{"id":"https://openalex.org/W4402125467","doi":"https://doi.org/10.1109/tvt.2024.3453170","title":"Data-Driven Hierarchical Model Predictive Control for Automated Overtaking Maneuver via Gaussian Process Regression","display_name":"Data-Driven Hierarchical Model Predictive Control for Automated Overtaking Maneuver via Gaussian Process Regression","publication_year":2024,"publication_date":"2024-09-02","ids":{"openalex":"https://openalex.org/W4402125467","doi":"https://doi.org/10.1109/tvt.2024.3453170"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2024.3453170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3453170","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/A5100604274","display_name":"Yiqun Li","orcid":"https://orcid.org/0000-0002-9259-7355"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiqun Li","raw_affiliation_strings":["State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029453515","display_name":"Zong Chen","orcid":"https://orcid.org/0000-0002-4080-7736"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zong Chen","raw_affiliation_strings":["State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115596282","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0003-3322-7554"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083555259","display_name":"Xiangrui Zeng","orcid":"https://orcid.org/0000-0001-5425-9219"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrui Zeng","raw_affiliation_strings":["State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053892414","display_name":"Zhouping Yin","orcid":"https://orcid.org/0000-0001-5766-2337"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouping Yin","raw_affiliation_strings":["State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100604274"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":1.937,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86275841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"74","issue":"1","first_page":"263","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9945999979972839,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9584000110626221,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9581000208854675,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overtaking","display_name":"Overtaking","score":0.8133922815322876},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.729865312576294},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.605191707611084},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5156737565994263},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4929628372192383},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.46467170119285583},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46314215660095215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45500633120536804},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.45073994994163513},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3895758092403412},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37254244089126587},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.36812901496887207},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.3419332802295685},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.315473735332489},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.279689759016037},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22245708107948303},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21809783577919006},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09912168979644775}],"concepts":[{"id":"https://openalex.org/C2778448659","wikidata":"https://www.wikidata.org/wiki/Q1931051","display_name":"Overtaking","level":2,"score":0.8133922815322876},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.729865312576294},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.605191707611084},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5156737565994263},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4929628372192383},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.46467170119285583},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46314215660095215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45500633120536804},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.45073994994163513},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3895758092403412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37254244089126587},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.36812901496887207},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3419332802295685},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.315473735332489},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.279689759016037},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22245708107948303},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21809783577919006},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09912168979644775},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2024.3453170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3453170","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":[{"display_name":"Climate action","score":0.5,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G51933792","display_name":null,"funder_award_id":"51905185","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5300105078","display_name":null,"funder_award_id":"BX20180109","funder_id":"https://openalex.org/F4320335768","funder_display_name":"National Postdoctoral Program for Innovative Talents"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335768","display_name":"National Postdoctoral Program for Innovative Talents","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1497695555","https://openalex.org/W1523116185","https://openalex.org/W1578293866","https://openalex.org/W1822858039","https://openalex.org/W1904799423","https://openalex.org/W1969483458","https://openalex.org/W1971086298","https://openalex.org/W1977085960","https://openalex.org/W1981723834","https://openalex.org/W2000194319","https://openalex.org/W2047166686","https://openalex.org/W2055201760","https://openalex.org/W2148361676","https://openalex.org/W2155858901","https://openalex.org/W2169528473","https://openalex.org/W2343568200","https://openalex.org/W2396317032","https://openalex.org/W2480035973","https://openalex.org/W2557055507","https://openalex.org/W2560612192","https://openalex.org/W2586838877","https://openalex.org/W2729776805","https://openalex.org/W2737297115","https://openalex.org/W2769646558","https://openalex.org/W2787876816","https://openalex.org/W2790176947","https://openalex.org/W2803445028","https://openalex.org/W2892521964","https://openalex.org/W2901618432","https://openalex.org/W2923554444","https://openalex.org/W2952762354","https://openalex.org/W2954115742","https://openalex.org/W2990303017","https://openalex.org/W2992833799","https://openalex.org/W3007585794","https://openalex.org/W3027865947","https://openalex.org/W3097634115","https://openalex.org/W3123229529","https://openalex.org/W3142005321","https://openalex.org/W4206978265","https://openalex.org/W4313010601","https://openalex.org/W4386702779","https://openalex.org/W6704559304","https://openalex.org/W6753596642"],"related_works":["https://openalex.org/W3084163143","https://openalex.org/W3198453306","https://openalex.org/W3081587374","https://openalex.org/W591161629","https://openalex.org/W2294880310","https://openalex.org/W3208192858","https://openalex.org/W2618142536","https://openalex.org/W2102544652","https://openalex.org/W1998625354","https://openalex.org/W2115519811"],"abstract_inverted_index":{"The":[0],"effectiveness":[1,186],"of":[2,19,28,53,97,117,132,187],"model-driven":[3,83],"trajectory":[4,44,70,159,190],"generation":[5,45,71,160,191],"and":[6,22,33,46,51,68,72,85,108,141,161,192],"control":[7,47,73,151,162,193],"methods":[8],"for":[9,75,156],"an":[10,113],"automated":[11,76,99,168],"vehicle":[12,20,30,95,100,144],"is":[13,31,79,123,154],"closely":[14],"related":[15],"to":[16,105,125,183],"the":[17,25,41,49,54,82,89,93,98,127,134,137,142,164,185,188],"accuracy":[18],"kinematics":[21],"dynamics.":[23,145],"However,":[24],"dynamic":[26,139],"behavior":[27],"a":[29,65],"time-varying":[32],"uncertain,":[34],"especially":[35],"during":[36],"high":[37],"mobility":[38],"driving.":[39],"For":[40],"data-driven":[42],"end-to-end":[43,86],"approach,":[48,88],"transferability":[50],"robustness":[52],"trained":[55],"neural":[56],"network":[57],"cannot":[58],"easily":[59],"be":[60],"guaranteed.":[61],"In":[62],"this":[63],"paper,":[64],"combined":[66],"model-":[67],"learning-based":[69],"framework":[74,91],"overtaking":[77,110,165,169],"maneuver":[78],"presented.":[80],"Unlike":[81],"approach":[84],"learning":[87],"proposed":[90,189],"blends":[92],"single-track":[94,138],"model":[96,140,149],"with":[101,152,179],"time-series":[102],"driving":[103],"data":[104],"generate":[106],"safe":[107],"high-quality":[109],"motions.":[111],"Specifically,":[112],"efficient":[114],"vectorized":[115],"implementation":[116],"multivariate":[118],"Gaussian":[119],"process":[120],"regression":[121],"(MGPR)":[122],"applied":[124],"learn":[126],"unmodeled":[128],"dynamics":[129],"in":[130,163],"hopes":[131],"shortening":[133],"deviation":[135],"between":[136],"true":[143],"A":[146],"hierarchical":[147],"nonlinear":[148],"predictive":[150],"MGPR":[153],"designed":[155],"realizing":[157],"local":[158],"maneuvers.":[166],"Multi-phases":[167],"maneuvers":[170],"at":[171],"different":[172,180],"speed":[173],"ranges":[174],"are":[175],"conducted":[176],"on":[177],"roads":[178],"friction":[181],"coefficients":[182],"illustrate":[184],"framework.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}