{"id":"https://openalex.org/W4400644846","doi":"https://doi.org/10.1109/iv55156.2024.10588861","title":"High-performance Racing on Unmapped Tracks using Local Maps","display_name":"High-performance Racing on Unmapped Tracks using Local Maps","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400644846","doi":"https://doi.org/10.1109/iv55156.2024.10588861"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5076940088","display_name":"Benjamin Evans","orcid":"https://orcid.org/0000-0001-6312-1203"},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Benjamin David Evans","raw_affiliation_strings":["Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065610954","display_name":"Hendrik Willem Jordaan","orcid":"https://orcid.org/0000-0002-6466-6456"},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Hendrik Willem Jordaan","raw_affiliation_strings":["Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091413322","display_name":"Herman A. Engelbrecht","orcid":"https://orcid.org/0000-0001-8753-8994"},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Herman Arnold Engelbrecht","raw_affiliation_strings":["Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Electrical and Electronic Engineering Department,Stellenbosch,South Africa,7600","institution_ids":["https://openalex.org/I26092322"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I26092322"],"apc_list":null,"apc_paid":null,"fwci":4.757,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94162914,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"851","last_page":"856"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9564999938011169,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9564999938011169,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.932200014591217,"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/T10157","display_name":"Sports Performance and Training","score":0.9233999848365784,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5246382355690002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4557395577430725},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.35447782278060913},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3399658501148224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5246382355690002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4557395577430725},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.35447782278060913},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3399658501148224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","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":25,"referenced_works":["https://openalex.org/W1578293866","https://openalex.org/W2041448245","https://openalex.org/W2910720822","https://openalex.org/W2951357333","https://openalex.org/W2961619538","https://openalex.org/W2963086870","https://openalex.org/W2977084332","https://openalex.org/W3046240082","https://openalex.org/W3091512219","https://openalex.org/W3093237585","https://openalex.org/W3132308129","https://openalex.org/W3188004887","https://openalex.org/W4211094662","https://openalex.org/W4225642194","https://openalex.org/W4281757468","https://openalex.org/W4285102517","https://openalex.org/W4285228542","https://openalex.org/W4309344373","https://openalex.org/W4366748330","https://openalex.org/W4383109279","https://openalex.org/W4385539610","https://openalex.org/W4389708898","https://openalex.org/W6678081342","https://openalex.org/W6859328159","https://openalex.org/W7047190309"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Map-based":[0],"methods":[1,19,36,169,201],"for":[2,107,113,184],"autonomous":[3,116,191],"racing":[4,117,192],"estimate":[5],"the":[6,31,63,78,83,94,140,152,178],"vehicle\u2019s":[7],"location,":[8],"which":[9],"is":[10,164],"used":[11,106,183],"to":[12,51,73,85,151,173,199],"follow":[13],"a":[14,28,100,119,126,156,204],"high-level":[15],"plan.":[16],"While":[17],"map-based":[18],"demonstrate":[20],"high-performance":[21],"results,":[22],"they":[23,43],"are":[24,136],"limited":[25],"by":[26],"requiring":[27,203],"map":[29,65,91,162,176],"of":[30,77,177],"environment.":[32],"In":[33,59],"contrast,":[34],"mapless":[35],"can":[37,181],"operate":[38],"in":[39,155],"unmapped":[40,194],"contexts":[41],"since":[42],"directly":[44],"process":[45],"raw":[46],"sensor":[47],"data":[48],"(often":[49],"LiDAR)":[50],"calculate":[52],"commands,":[53],"but":[54],"suffer":[55],"from":[56],"poor":[57],"performance.":[58],"response,":[60],"we":[61],"propose":[62],"local":[64,75,90,161],"framework":[66],"that":[67,81,135,170,180],"uses":[68],"easily":[69],"extractable,":[70],"low-level":[71],"features":[72],"build":[74],"maps":[76],"visible":[79,95],"region":[80],"form":[82],"input":[84],"optimisation-based":[86],"trajectory":[87,120],"planners.":[88],"Our":[89,130],"generation":[92],"extracts":[93],"racetrack":[96],"boundaries":[97],"and":[98,103,122,125,143],"calculates":[99],"centre":[101],"line":[102],"track":[104,179,205],"widths":[105],"planning.":[108,185],"We":[109],"evaluate":[110],"our":[111,187],"method":[112,131,142],"simulated":[114],"F1Tenth":[115],"using":[118],"optimisation":[121,153],"tracking":[123],"strategy":[124],"model":[127],"predictive":[128],"controller.":[129],"achieves":[132],"lap":[133],"times":[134],"8.8%":[137],"faster":[138,145,157],"than":[139,146,167],"Follow-The-Gap":[141],"3.22%":[144],"end-to-end":[147],"neural":[148],"networks":[149],"due":[150],"resulting":[154],"speed":[158],"profile.":[159],"The":[160],"planner":[163],"3.28%":[165],"slower":[166],"global":[168,200],"have":[171],"access":[172],"an":[174],"entire":[175],"be":[182],"Critically,":[186],"approach":[188],"enables":[189],"high-speed":[190],"on":[193],"tracks,":[195],"achieving":[196],"performance":[197],"similar":[198],"without":[202],"map.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}