{"id":"https://openalex.org/W2910440362","doi":"https://doi.org/10.1109/lra.2019.2893446","title":"Deep Metadata Fusion for Traffic Light to Lane Assignment","display_name":"Deep Metadata Fusion for Traffic Light to Lane Assignment","publication_year":2019,"publication_date":"2019-01-16","ids":{"openalex":"https://openalex.org/W2910440362","doi":"https://doi.org/10.1109/lra.2019.2893446","mag":"2910440362"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2019.2893446","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2019.2893446","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/8581687/08613841.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/7083369/8581687/08613841.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034003527","display_name":"Tristan Langenberg","orcid":"https://orcid.org/0000-0002-0143-9416"},"institutions":[{"id":"https://openalex.org/I1332474105","display_name":"Mercedes-Benz (Germany)","ror":"https://ror.org/055rn2a38","country_code":"DE","type":"company","lineage":["https://openalex.org/I1332474105"]},{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tristan Langenberg","raw_affiliation_strings":["Daimler AG, Mercedes-Benz Cars, Research and Development, Sindelfingen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-0143-9416","affiliations":[{"raw_affiliation_string":"Daimler AG, Mercedes-Benz Cars, Research and Development, Sindelfingen, Germany","institution_ids":["https://openalex.org/I1332474105","https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053943963","display_name":"Timo L\u00fcddecke","orcid":"https://orcid.org/0000-0002-1643-7827"},"institutions":[{"id":"https://openalex.org/I74656192","display_name":"University of G\u00f6ttingen","ror":"https://ror.org/01y9bpm73","country_code":"DE","type":"education","lineage":["https://openalex.org/I74656192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Timo Luddecke","raw_affiliation_strings":["Third Physical Institute, Georg-August University G\u00f6ttingen, G\u00f6ttingen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-1643-7827","affiliations":[{"raw_affiliation_string":"Third Physical Institute, Georg-August University G\u00f6ttingen, G\u00f6ttingen, Germany","institution_ids":["https://openalex.org/I74656192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023811677","display_name":"Florentin W\u00f6rg\u00f6tter","orcid":null},"institutions":[{"id":"https://openalex.org/I74656192","display_name":"University of G\u00f6ttingen","ror":"https://ror.org/01y9bpm73","country_code":"DE","type":"education","lineage":["https://openalex.org/I74656192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florentin Worgotter","raw_affiliation_strings":["Third Physical Institute, Georg-August University G\u00f6ttingen, G\u00f6ttingen, Germany"],"raw_orcid":"https://orcid.org/0000-0001-8206-9738","affiliations":[{"raw_affiliation_string":"Third Physical Institute, Georg-August University G\u00f6ttingen, G\u00f6ttingen, Germany","institution_ids":["https://openalex.org/I74656192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5685,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.66719404,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"4","issue":"2","first_page":"973","last_page":"980"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/metadata","display_name":"Metadata","score":0.9355788826942444},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8205353021621704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.763962984085083},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.752532958984375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5877118110656738},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5427605509757996},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.518601655960083},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48242267966270447},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4561942219734192},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44915029406547546},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4339636564254761},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32484501600265503},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07227957248687744}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.9355788826942444},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8205353021621704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.763962984085083},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.752532958984375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5877118110656738},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5427605509757996},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.518601655960083},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48242267966270447},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4561942219734192},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44915029406547546},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4339636564254761},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32484501600265503},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07227957248687744},{"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2019.2893446","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2019.2893446","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/8581687/08613841.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:publications.goettingen-research-online.de:2/135618","is_oa":true,"landing_page_url":"https://resolver.sub.uni-goettingen.de/purl?gro-2/135618","pdf_url":null,"source":{"id":"https://openalex.org/S4306401634","display_name":"GoeScholar  The Publication Server of the Georg-August-Universit\u00e4t G\u00f6ttingen (Georg-August-Universit\u00e4t G\u00f6ttingen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210122495","host_organization_name":"Asklepios Klinik St. Georg","host_organization_lineage":["https://openalex.org/I4210122495"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/lra.2019.2893446","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2019.2893446","pdf_url":"https://ieeexplore.ieee.org/ielx7/7083369/8581687/08613841.pdf","source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338339","display_name":"H2020 Leadership in Enabling and Industrial Technologies","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2910440362.pdf","grobid_xml":"https://content.openalex.org/works/W2910440362.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1562810981","https://openalex.org/W1577575150","https://openalex.org/W1927391347","https://openalex.org/W1960560098","https://openalex.org/W2073769893","https://openalex.org/W2076945774","https://openalex.org/W2097117768","https://openalex.org/W2101938307","https://openalex.org/W2136891917","https://openalex.org/W2188028980","https://openalex.org/W2194775991","https://openalex.org/W2239589426","https://openalex.org/W2291942460","https://openalex.org/W2294873883","https://openalex.org/W2420642263","https://openalex.org/W2508688281","https://openalex.org/W2520640394","https://openalex.org/W2592903734","https://openalex.org/W2737202447","https://openalex.org/W2739574231","https://openalex.org/W2741046124","https://openalex.org/W2741637292","https://openalex.org/W2762219805","https://openalex.org/W2773412982","https://openalex.org/W2782021532","https://openalex.org/W2792492025","https://openalex.org/W2806886077","https://openalex.org/W2890748873","https://openalex.org/W2903889928","https://openalex.org/W2962949934","https://openalex.org/W3099871687","https://openalex.org/W4250482878","https://openalex.org/W6686815432","https://openalex.org/W6687567705","https://openalex.org/W6717247507"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2912737833","https://openalex.org/W2999805992","https://openalex.org/W2910440362","https://openalex.org/W3208266890"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,15,37,91,121,138,142,167],"deep":[3],"metadata":[4,13],"fusion":[5],"approach":[6,21,126,155],"that":[7,67],"connects":[8],"image":[9],"data":[10],"and":[11,45,77,102],"heterogeneous":[12],"inside":[14],"Convolutional":[16],"Neural":[17],"Network":[18],"(CNN).":[19],"This":[20],"enables":[22],"us":[23],"to":[24,30,49,99,113,162,172],"assign":[25],"all":[26,62,128],"relevant":[27,64],"traffic":[28,65,111],"lights":[29,66],"their":[31],"associated":[32,69],"lanes.":[33,71],"To":[34],"achieve":[35],"this,":[36],"common":[38],"CNN":[39],"topology":[40],"is":[41,149],"trained":[42],"by":[43,120],"down-sampled":[44],"transformed":[46],"input":[47,89],"images":[48],"predict":[50],"an":[51],"indication":[52,55],"vector.":[53],"The":[54,95,124],"vector":[56],"contains":[57],"the":[58,63,85,110,153],"column":[59],"positions":[60],"of":[61,90,109],"are":[68,97],"with":[70,84,160],"In":[72,105,141,151],"parallel,":[73],"we":[74],"fuse":[75],"prepared":[76],"adaptively":[78],"weighted":[79],"Metadata":[80],"Feature":[81],"Maps":[82],"(MFM)":[83],"convolutional":[86,93],"feature":[87],"map":[88],"selected":[92],"layer.":[94],"results":[96,159],"compared":[98],"rule-based,":[100],"only-metadata,":[101],"only-vision":[103],"approaches.":[104,130],"addition,":[106],"human":[107,174],"performance":[108],"light":[112],"ego-vehicle":[114],"lane":[115],"assignment":[116],"has":[117],"been":[118],"measured":[119],"subjective":[122],"test.":[123],"proposed":[125],"outperforms":[127],"other":[129],"It":[131],"achieves":[132],"about":[133],"93.0%":[134],"average":[135,147,164],"precision":[136,148],"for":[137,166],"real-world":[139,168],"dataset.":[140],"more":[143],"complex":[144],"dataset,":[145],"87.1%":[146],"achieved.":[150],"particular,":[152],"new":[154],"reaches":[156],"significantly":[157],"higher":[158],"93.7%":[161],"91.0%":[163],"accuracy":[165],"dataset":[169],"in":[170],"contrast":[171],"lower":[173],"performance.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
