{"id":"https://openalex.org/W4391768929","doi":"https://doi.org/10.1109/itsc57777.2023.10422413","title":"Inverse Reinforcement Learning and Gaussian Process Regression-based Real-Time Framework for Personalized Adaptive Cruise Control","display_name":"Inverse Reinforcement Learning and Gaussian Process Regression-based Real-Time Framework for Personalized Adaptive Cruise Control","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4391768929","doi":"https://doi.org/10.1109/itsc57777.2023.10422413"},"language":"en","primary_location":{"id":"doi:10.1109/itsc57777.2023.10422413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422413","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-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/A5066621781","display_name":"Zhouqiao Zhao","orcid":"https://orcid.org/0000-0002-5286-3807"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhouqiao Zhao","raw_affiliation_strings":["College of Engineering, University of California, Riverside,Riverside,CA,92507"],"affiliations":[{"raw_affiliation_string":"College of Engineering, University of California, Riverside,Riverside,CA,92507","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050822564","display_name":"Xishun Liao","orcid":"https://orcid.org/0000-0002-7219-8971"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xishun Liao","raw_affiliation_strings":["College of Engineering, University of California, Riverside,Riverside,CA,92507"],"affiliations":[{"raw_affiliation_string":"College of Engineering, University of California, Riverside,Riverside,CA,92507","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070231367","display_name":"Amr Abdelraouf","orcid":"https://orcid.org/0000-0001-9068-6664"},"institutions":[{"id":"https://openalex.org/I4210093665","display_name":"Toyota Motor Corporation (United States)","ror":"https://ror.org/0076knn86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093665","https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amr Abdelraouf","raw_affiliation_strings":["Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043"],"affiliations":[{"raw_affiliation_string":"Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043","institution_ids":["https://openalex.org/I4210093665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009775690","display_name":"Kyungtae Han","orcid":"https://orcid.org/0000-0001-8291-5025"},"institutions":[{"id":"https://openalex.org/I4210093665","display_name":"Toyota Motor Corporation (United States)","ror":"https://ror.org/0076knn86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093665","https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyungtae Han","raw_affiliation_strings":["Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043"],"affiliations":[{"raw_affiliation_string":"Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043","institution_ids":["https://openalex.org/I4210093665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038831216","display_name":"Rohit Kumar Gupta","orcid":"https://orcid.org/0000-0002-1080-2651"},"institutions":[{"id":"https://openalex.org/I4210093665","display_name":"Toyota Motor Corporation (United States)","ror":"https://ror.org/0076knn86","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093665","https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rohit Gupta","raw_affiliation_strings":["Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043"],"affiliations":[{"raw_affiliation_string":"Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,94043","institution_ids":["https://openalex.org/I4210093665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077257353","display_name":"Matthew Barth","orcid":"https://orcid.org/0000-0002-4735-5859"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew J. Barth","raw_affiliation_strings":["College of Engineering, University of California, Riverside,Riverside,CA,92507"],"affiliations":[{"raw_affiliation_string":"College of Engineering, University of California, Riverside,Riverside,CA,92507","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006183071","display_name":"Guoyuan Wu","orcid":"https://orcid.org/0000-0001-6707-6366"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoyuan Wu","raw_affiliation_strings":["College of Engineering, University of California, Riverside,Riverside,CA,92507"],"affiliations":[{"raw_affiliation_string":"College of Engineering, University of California, Riverside,Riverside,CA,92507","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5066621781"],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":0.2542,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.4547599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4428","last_page":"4435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9819999933242798,"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"}},"topics":[{"id":"https://openalex.org/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.9819999933242798,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9388999938964844,"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/T10524","display_name":"Traffic control and management","score":0.9297999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cruise-control","display_name":"Cruise control","score":0.7109395861625671},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6842782497406006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.661649227142334},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6218044757843018},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5381304621696472},{"id":"https://openalex.org/keywords/inverse-gaussian-distribution","display_name":"Inverse Gaussian distribution","score":0.47133851051330566},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4707779586315155},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4578056335449219},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.456871896982193},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.4307790994644165},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3521643877029419},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.2906842827796936},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17528176307678223},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14434826374053955}],"concepts":[{"id":"https://openalex.org/C113168747","wikidata":"https://www.wikidata.org/wiki/Q507295","display_name":"Cruise control","level":3,"score":0.7109395861625671},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6842782497406006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.661649227142334},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6218044757843018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5381304621696472},{"id":"https://openalex.org/C132878287","wikidata":"https://www.wikidata.org/wiki/Q1671727","display_name":"Inverse Gaussian distribution","level":3,"score":0.47133851051330566},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4707779586315155},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4578056335449219},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.456871896982193},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.4307790994644165},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3521643877029419},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2906842827796936},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17528176307678223},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14434826374053955},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc57777.2023.10422413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc57777.2023.10422413","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1502922572","https://openalex.org/W2054210802","https://openalex.org/W2089080831","https://openalex.org/W2124609748","https://openalex.org/W2152374007","https://openalex.org/W2170908920","https://openalex.org/W2170973929","https://openalex.org/W2768408353","https://openalex.org/W2886622679","https://openalex.org/W2904814783","https://openalex.org/W2913367279","https://openalex.org/W2991431362","https://openalex.org/W3083713718","https://openalex.org/W3090797051","https://openalex.org/W3158597572","https://openalex.org/W3163197578","https://openalex.org/W3210643912","https://openalex.org/W3210655259","https://openalex.org/W4213052444","https://openalex.org/W4285047693","https://openalex.org/W4308079974","https://openalex.org/W4360995340","https://openalex.org/W4391768406","https://openalex.org/W4391770362","https://openalex.org/W6852194634","https://openalex.org/W6856178415"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W4293503520","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655","https://openalex.org/W2947916784"],"abstract_inverted_index":{"Adaptive":[0],"Cruise":[1],"Control":[2],"(ACC)":[3],"has":[4,45],"become":[5],"increasingly":[6],"popular":[7],"in":[8,131,170,177],"modern":[9],"vehicles,":[10],"providing":[11],"enhanced":[12],"driving":[13,57,128],"safety,":[14],"comfort,":[15],"and":[16,34,92,104],"fuel":[17],"efficiency.":[18],"However,":[19,50],"predefined":[20],"ACC":[21,43],"settings":[22],"may":[23],"not":[24],"always":[25],"align":[26],"with":[27,145],"a":[28,76,171],"driver's":[29,100,122,147,159],"preferences,":[30],"leading":[31],"to":[32,59,110,125,155,182],"discomfort":[33],"possible":[35],"safety":[36],"hazards.":[37],"To":[38,70],"address":[39],"this":[40,72],"issue,":[41],"Personalized":[42],"(P-ACC)":[44],"been":[46],"studied":[47],"by":[48],"scholars.":[49],"existing":[51],"research":[52],"mostly":[53],"relies":[54],"on":[55,114,142],"historical":[56],"data":[58],"imitate":[60],"driver":[61,84,175],"styles,":[62],"which":[63,81],"ignores":[64],"real-time":[65,83,123,132],"feedback":[66,85,124],"from":[67],"the":[68,99,112,115,121,127,140,143,146,158,166],"driver.":[69],"overcome":[71],"limitation,":[73],"we":[74],"propose":[75],"cloud-vehicle":[77],"collaborative":[78],"P-ACC":[79],"framework,":[80],"integrates":[82],"adaptation.":[86],"This":[87],"framework":[88,168],"consists":[89],"of":[90,174],"offline":[91,96],"online":[93,118],"modules.":[94],"The":[95,117],"module":[97,119],"records":[98],"naturalistic":[101],"car-following":[102],"trajectory":[103],"uses":[105],"inverse":[106],"reinforcement":[107],"learning":[108,154],"(IRL)":[109],"train":[111],"model":[113,141],"cloud.":[116],"utilizes":[120],"update":[126],"gap":[129],"preference":[130],"using":[133],"Gaussian":[134],"process":[135],"regression":[136],"(GPR).":[137],"By":[138],"retraining":[139],"cloud":[144],"takeover":[148],"trajectories,":[149],"our":[150],"approach":[151],"achieves":[152],"incremental":[153],"better":[156],"match":[157],"preference.":[160],"In":[161],"human-in-the-loop":[162],"(HuiL)":[163],"simulation":[164],"experiments,":[165],"proposed":[167],"results":[169],"significant":[172],"reduction":[173],"intervention":[176],"automatic":[178],"control":[179],"systems,":[180],"up":[181],"70.9%.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
