{"id":"https://openalex.org/W2117000198","doi":"https://doi.org/10.1109/ivs.2014.6856513","title":"Road geometry classification using ANN","display_name":"Road geometry classification using ANN","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2117000198","doi":"https://doi.org/10.1109/ivs.2014.6856513","mag":"2117000198"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2014.6856513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","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/A5016562532","display_name":"Alberto Hata","orcid":"https://orcid.org/0000-0002-6968-7387"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Alberto Y. Hata","raw_affiliation_strings":["Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060922062","display_name":"Danilo Habermann","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Danilo Habermann","raw_affiliation_strings":["Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030595758","display_name":"Fernando Santos Os\u00f3rio","orcid":"https://orcid.org/0000-0002-6620-2794"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando S. Osorio","raw_affiliation_strings":["Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047424364","display_name":"Denis F. Wolf","orcid":"https://orcid.org/0000-0003-1485-5686"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Denis F. Wolf","raw_affiliation_strings":["Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade de Sao Paulo, Sao Paulo, S\u00c3\u00a3o Paulo, BR","institution_ids":["https://openalex.org/I17974374"]},{"raw_affiliation_string":"Mobile Robot. Lab., Univ. of Sao Paulo, Sao Carlos, Brazil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016562532"],"corresponding_institution_ids":["https://openalex.org/I17974374"],"apc_list":null,"apc_paid":null,"fwci":2.0001,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.87227041,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1319","last_page":"1324"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13282","display_name":"Automated Road and Building Extraction","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7521594166755676},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7504993677139282},{"id":"https://openalex.org/keywords/road-surface","display_name":"Road surface","score":0.7127504348754883},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6387397646903992},{"id":"https://openalex.org/keywords/identifier","display_name":"Identifier","score":0.6366033554077148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5748663544654846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.555831253528595},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5216365456581116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4667157530784607},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4268408715724945},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.4139302968978882},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3212445378303528},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2148546278476715}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7521594166755676},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7504993677139282},{"id":"https://openalex.org/C2780042925","wikidata":"https://www.wikidata.org/wiki/Q1049667","display_name":"Road surface","level":2,"score":0.7127504348754883},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6387397646903992},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.6366033554077148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5748663544654846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.555831253528595},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5216365456581116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4667157530784607},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4268408715724945},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4139302968978882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3212445378303528},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2148546278476715},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2014.6856513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W126258430","https://openalex.org/W1985462666","https://openalex.org/W1989620441","https://openalex.org/W1998241363","https://openalex.org/W2036007814","https://openalex.org/W2051610568","https://openalex.org/W2065651455","https://openalex.org/W2089112725","https://openalex.org/W2136849599","https://openalex.org/W2138534490","https://openalex.org/W2159132531","https://openalex.org/W4293682399","https://openalex.org/W6647571858"],"related_works":["https://openalex.org/W4378651134","https://openalex.org/W4252684102","https://openalex.org/W2352307597","https://openalex.org/W1979633005","https://openalex.org/W2163724607","https://openalex.org/W3135403405","https://openalex.org/W1980092392","https://openalex.org/W2608983118","https://openalex.org/W37347591","https://openalex.org/W4283588223"],"abstract_inverted_index":{"An":[0,15],"autonomous":[1],"car":[2],"must":[3],"have":[4],"a":[5,62,89,100,236,242],"robust":[6],"perception":[7,20],"system":[8],"to":[9,41,47,69,79,149,164,169],"navigate":[10],"safely":[11],"in":[12,157,207,230],"urban":[13,232],"streets.":[14],"important":[16],"issue":[17],"of":[18,30,65,72,143,160,210,223,244,258],"environment":[19],"is":[21,146],"the":[22,28,31,43,48,70,158,165,175,208,211],"road":[23,32,35,56,90,106,120,172,259],"(navigable":[24],"area)":[25],"detection":[26],"and":[27,50,83,95,116,138,195,201,217],"identification":[29],"geometry.":[33],"The":[34,105,140,225],"geometry":[36,57],"information":[37,98,173],"can":[38],"be":[39],"used":[40],"determine":[42,170],"vehicle":[44],"control":[45],"according":[46],"street":[49],"also":[51],"for":[52,152,178],"topological":[53],"localization.":[54],"Existing":[55],"identifiers":[58],"only":[59],"work":[60],"with":[61,81,110,187,192,198,214,220],"limited":[63],"number":[64,257],"classes":[66],"and,":[67,234],"due":[68],"use":[71],"cameras,":[73],"some":[74],"solutions":[75],"depend":[76],"on":[77],"filters":[78],"deal":[80],"shadows":[82],"light":[84,150],"variations.":[85],"This":[86],"paper":[87],"presents":[88],"detector":[91],"that":[92,254],"extracts":[93],"curb":[94,188,200,216],"navigable":[96],"surface":[97,193,202,218],"from":[99],"multilayer":[101],"laser":[102],"sensor":[103],"data.":[104,203],"data":[107,162,194],"was":[108,228],"trained":[109,186,191,197,213,226],"an":[111,221],"artificial":[112],"neural":[113],"network":[114,212],"(ANN)":[115],"classified":[117],"into":[118],"eight":[119],"geometries:":[121],"straight":[122],"road,":[123,130,133],"left":[124,128],"turn,":[125,127],"right":[126,131],"side":[129,132],"T":[134],"intersection,":[135],"Y":[136],"intersection":[137],"crossroad.":[139],"main":[141],"advantage":[142],"our":[144],"method":[145],"its":[147],"robustness":[148],"variations":[151],"detecting":[153],"distinct":[154],"roads":[155],"even":[156],"presence":[159],"noisy":[161],"thanks":[163],"ANN.":[166],"In":[167],"order":[168],"which":[171],"has":[174],"best":[176],"features":[177],"ANN":[179,185,190,196,227],"training,":[180],"three":[181],"approaches":[182],"were":[183],"explored:":[184],"data,":[189,219],"both":[199,215],"Performed":[204],"experiments":[205],"resulted":[206],"superiority":[209],"accuracy":[222],"0.91799.":[224],"validated":[229],"different":[231],"scenarios":[233],"evaluating":[235],"1":[237],"Km":[238],"track,":[239],"we":[240],"obtained":[241],"94.48%":[243],"correct":[245],"classifications.":[246],"These":[247],"results":[248],"are":[249],"superior":[250],"than":[251],"other":[252],"works":[253],"detect":[255],"fewer":[256],"shapes.":[260]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}