{"id":"https://openalex.org/W7162405547","doi":"https://doi.org/10.48550/arxiv.2605.25029","title":"ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation","display_name":"ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation","publication_year":2026,"publication_date":"2026-05-24","ids":{"openalex":"https://openalex.org/W7162405547","doi":"https://doi.org/10.48550/arxiv.2605.25029"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25029","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25029","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.25029","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137049254","display_name":"Zhengcheng Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Zhengcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052605358","display_name":"Changze Li","orcid":"https://orcid.org/0000-0003-3004-1818"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Changze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136994078","display_name":"Haoran Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137071762","display_name":"Tong Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.3255999982357025,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12546","display_name":"Smart Parking Systems Research","score":0.3255999982357025,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.22949999570846558,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.17589999735355377,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7857000231742859},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4081000089645386},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.38909998536109924},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.36090001463890076},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.34529998898506165},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.30309998989105225}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7857000231742859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.756600022315979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43130001425743103},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2955999970436096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2797999978065491},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25029","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25029","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.25029","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25029","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5940813422203064,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"parking":[1,74,108,195,218],"demands":[2],"precise":[3],"low-speed":[4],"maneuvering":[5],"within":[6],"narrow,":[7],"cluttered,":[8],"and":[9,23,45,68,138,149,162,179,200,209],"highly":[10],"constrained":[11],"environments,":[12],"where":[13],"vehicles":[14],"must":[15],"navigate":[16],"tight":[17],"spaces":[18],"while":[19],"avoiding":[20],"static":[21],"obstacles":[22],"complex":[24],"geometric":[25],"boundaries.":[26],"Unlike":[27],"imitation":[28],"learning,":[29],"which":[30,97],"typically":[31],"requires":[32],"massive":[33],"volumes":[34],"of":[35,115,212],"high-quality":[36],"expert":[37],"demonstrations":[38],"to":[39,41,51,71],"converge":[40],"a":[42,86,102,128,180],"stable":[43],"policy":[44],"often":[46],"suffers":[47],"from":[48],"limited":[49],"generalization":[50],"unseen":[52],"scenarios,":[53,205],"traditional":[54],"reinforcement":[55,89],"learning":[56,90,124,164],"(RL)":[57],"methods":[58],"face":[59],"persistent":[60],"challenges":[61],"including":[62],"excessive":[63],"training":[64],"overhead,":[65],"inefficient":[66],"exploration,":[67],"even":[69],"failure":[70],"learn":[72],"viable":[73],"strategies":[75],"in":[76,101,123,153,173,194],"challenging":[77],"settings.":[78],"To":[79],"address":[80],"these":[81],"limitations,":[82],"this":[83],"paper":[84],"presents":[85],"correction-in-the-loop":[87],"sample-efficient":[88],"(CIL-SERL)":[91],"framework":[92,169],"for":[93],"end-to-end":[94,216],"autonomous":[95,217],"parking,":[96],"is":[98,170],"entirely":[99],"trained":[100],"photorealistic":[103],"3D":[104],"Gaussian":[105],"Splatting":[106],"(3DGS)":[107],"simulator":[109],"that":[110,188],"enables":[111],"high-fidelity":[112],"digital":[113],"reconstruction":[114],"real-world":[116],"scenes.":[117],"Inspired":[118],"by":[119],"error-correction":[120],"notebooks":[121],"used":[122],"practice,":[125],"we":[126],"design":[127],"novel":[129],"multi-level":[130],"replay":[131],"buffer":[132],"mechanism.":[133],"These":[134],"buffers":[135],"hierarchically":[136],"organize":[137],"store":[139],"standard":[140],"RL":[141],"rollouts,":[142],"human":[143],"corrective":[144],"interventions,":[145],"failed":[146],"exploration":[147],"trajectories,":[148],"rollback-based":[150],"correction":[151],"segments":[152],"separate":[154],"yet":[155],"interconnected":[156],"memory":[157],"regions,":[158],"facilitating":[159],"structured":[160],"sampling":[161],"targeted":[163],"during":[165],"training.":[166],"The":[167],"proposed":[168,214],"systematically":[171],"evaluated":[172],"both":[174],"the":[175,207,213],"3DGS":[176],"simulation":[177],"environment":[178],"physical":[181],"vehicle":[182],"platform.":[183],"Extensive":[184],"experimental":[185],"results":[186],"demonstrate":[187],"our":[189],"method":[190],"achieves":[191],"substantial":[192],"improvements":[193],"success":[196],"rate,":[197],"operational":[198],"efficiency,":[199],"safety":[201],"performance":[202],"across":[203],"diverse":[204],"validating":[206],"effectiveness":[208],"practical":[210],"applicability":[211],"CIL-SERL-based":[215],"solution.":[219]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-27T00:00:00"}
