{"id":"https://openalex.org/W4286580809","doi":"https://doi.org/10.1109/tvt.2022.3193220","title":"Inverse Reinforcement Learning Based: Segmented Lane-Change Trajectory Planning With Consideration of Interactive Driving Intention","display_name":"Inverse Reinforcement Learning Based: Segmented Lane-Change Trajectory Planning With Consideration of Interactive Driving Intention","publication_year":2022,"publication_date":"2022-07-22","ids":{"openalex":"https://openalex.org/W4286580809","doi":"https://doi.org/10.1109/tvt.2022.3193220"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2022.3193220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2022.3193220","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/A5069567021","display_name":"Yingbo Sun","orcid":"https://orcid.org/0000-0001-6681-1066"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingbo Sun","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112852836","display_name":"Yuan Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Chu","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036222171","display_name":"Tao Xu","orcid":"https://orcid.org/0000-0001-5889-3727"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367200","display_name":"Jingyuan Li","orcid":"https://orcid.org/0000-0003-0483-0944"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyuan Li","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024351828","display_name":"Xuewu Ji","orcid":"https://orcid.org/0000-0002-5242-8119"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewu Ji","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5069567021"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.479,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.88882906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"71","issue":"11","first_page":"11395","last_page":"11407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","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/T11099","display_name":"Autonomous Vehicle Technology and Safety","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/T10524","display_name":"Traffic control and management","score":0.9940999746322632,"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/T10370","display_name":"Traffic and Road Safety","score":0.9667999744415283,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/trajectory","display_name":"Trajectory","score":0.7374900579452515},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6683056950569153},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6677542924880981},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.632902979850769},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.46781063079833984},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4619396924972534},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.44691145420074463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4201474189758301},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.41251304745674133},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.14325395226478577}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7374900579452515},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6683056950569153},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6677542924880981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.632902979850769},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.46781063079833984},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4619396924972534},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.44691145420074463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4201474189758301},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.41251304745674133},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.14325395226478577},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2022.3193220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2022.3193220","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":"Sustainable cities and communities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8643382381","display_name":null,"funder_award_id":"51975311","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W131069610","https://openalex.org/W1516898087","https://openalex.org/W1527702126","https://openalex.org/W1533707276","https://openalex.org/W1989438871","https://openalex.org/W2056877664","https://openalex.org/W2098774185","https://openalex.org/W2127330529","https://openalex.org/W2741087535","https://openalex.org/W2795543364","https://openalex.org/W2801597796","https://openalex.org/W2891385160","https://openalex.org/W2896642734","https://openalex.org/W2901561173","https://openalex.org/W2942735643","https://openalex.org/W2952762354","https://openalex.org/W2963000651","https://openalex.org/W2963489164","https://openalex.org/W2963594110","https://openalex.org/W2990048843","https://openalex.org/W2992382489","https://openalex.org/W2995649812","https://openalex.org/W2996287921","https://openalex.org/W3023995140","https://openalex.org/W3037434189","https://openalex.org/W3097522998","https://openalex.org/W3101805180","https://openalex.org/W3103869897","https://openalex.org/W3104181348","https://openalex.org/W3115674057","https://openalex.org/W3176912151","https://openalex.org/W3211345831","https://openalex.org/W3217645262","https://openalex.org/W3217696802","https://openalex.org/W4226338449","https://openalex.org/W6605295560","https://openalex.org/W6647802820","https://openalex.org/W6674884181"],"related_works":["https://openalex.org/W4385832323","https://openalex.org/W4244391535","https://openalex.org/W2356996864","https://openalex.org/W2904060783","https://openalex.org/W2015393961","https://openalex.org/W2378339670","https://openalex.org/W2359353485","https://openalex.org/W2361427670","https://openalex.org/W2139910871","https://openalex.org/W2119925415"],"abstract_inverted_index":{"One":[0],"of":[1,130,148,216],"the":[2,28,42,98,128,149,183,196,213],"most":[3],"challenging":[4],"problems":[5],"in":[6,118],"autonomous":[7,80],"driving":[8,48,67,110,214],"is":[9,18,57,124,170],"trajectory":[10,16,76,141,168],"planning":[11,17,77,169],"for":[12,32,79,93,107],"lane":[13],"changes.":[14],"Conventional":[15],"generally":[19],"realized":[20],"by":[21,64],"optimizing":[22],"a":[23,73],"specific":[24],"cost":[25,43,146],"function.":[26,44],"However,":[27],"model":[29,106],"performance":[30],"required":[31],"different":[33,156,164],"scenarios":[34],"makes":[35],"it":[36,56],"repetitive":[37],"and":[38,97,102,186,205],"time-consuming":[39],"to":[40,46,59,126,138,155,163,172,212],"tune":[41],"Furthermore,":[45],"ensure":[47],"safety,":[49],"comfort":[50],"as":[51,53],"well":[52],"traffic":[54],"efficiency,":[55],"essential":[58],"interact":[60],"with":[61],"other":[62],"vehicles":[63,81,132],"predicting":[65],"their":[66],"intentions.":[68],"Therefore,":[69],"this":[70,119],"paper":[71],"proposes":[72],"segmented-updated":[74],"lane-change":[75,140,157,189,208],"method":[78,198],"on":[82,134],"closed":[83],"highways.":[84],"The":[85,122],"maximum":[86],"entropy":[87],"inverse":[88],"reinforcement":[89],"learning":[90,96],"(IRL)":[91],"algorithm":[92,151],"human":[94],"demonstration":[95],"long":[99],"short-term":[100],"memory":[101],"Bayesian":[103],"network":[104],"(LSTM-BN)-based":[105],"target":[108],"vehicles'":[109],"intentions":[111,129,215],"are":[112,116,152],"applied.":[113],"Three":[114],"contributions":[115],"made":[117],"work:":[120],"1)":[121],"LSTM-BN":[123],"used":[125,171],"judge":[127],"surrounding":[131,217],"based":[133],"its":[135,161],"historical":[136],"information":[137],"inform":[139],"planning.":[142],"2)":[143],"Different":[144],"feature-based":[145],"functions":[147],"IRL":[150],"designed":[153],"according":[154,211],"scenarios,":[158],"which":[159,181],"enhances":[160],"adaptability":[162],"scenarios.":[165],"3)":[166],"Segmented-updated":[167],"dynamically":[173],"optimize":[174],"trajectories":[175,209],"via":[176],"an":[177],"online":[178],"optimization":[179],"process,":[180],"reduces":[182],"model's":[184],"limitations":[185],"improves":[187],"overall":[188],"performance.":[190],"Finally,":[191],"simulation":[192],"experiments":[193],"demonstrate":[194],"that":[195],"proposed":[197],"has":[199],"strong":[200],"generalization":[201],"ability,":[202],"reliable":[203],"accuracy,":[204],"can":[206],"adjust":[207],"reasonably":[210],"vehicles.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}