{"id":"https://openalex.org/W2772944837","doi":"https://doi.org/10.1109/mfi.2017.8170435","title":"A survey of performance measures to evaluate ego-lane estimation and a novel sensor-independent measure along with its applications","display_name":"A survey of performance measures to evaluate ego-lane estimation and a novel sensor-independent measure along with its applications","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2772944837","doi":"https://doi.org/10.1109/mfi.2017.8170435","mag":"2772944837"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2017.8170435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5030699969","display_name":"Tran Tuan Nguyen","orcid":"https://orcid.org/0000-0002-2522-2414"},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tran Tuan Nguyen","raw_affiliation_strings":["Volkswagen Group, Wolfsburg, Germany"],"affiliations":[{"raw_affiliation_string":"Volkswagen Group, Wolfsburg, Germany","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008622599","display_name":"Jens Spehr","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Spehr","raw_affiliation_strings":["Volkswagen Group, Wolfsburg, Germany"],"affiliations":[{"raw_affiliation_string":"Volkswagen Group, Wolfsburg, Germany","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101686187","display_name":"Jian Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I1319473763","display_name":"Volkswagen Group (Germany)","ror":"https://ror.org/01f3bhg26","country_code":"DE","type":"company","lineage":["https://openalex.org/I1319473763"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jian Xiong","raw_affiliation_strings":["Volkswagen Group, Wolfsburg, Germany"],"affiliations":[{"raw_affiliation_string":"Volkswagen Group, Wolfsburg, Germany","institution_ids":["https://openalex.org/I1319473763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053963755","display_name":"Marcus Baum","orcid":"https://orcid.org/0000-0002-0953-9032"},"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":"Marcus Baum","raw_affiliation_strings":["University of G\u00f6ttingen, G\u00f6ttingen, Germany"],"affiliations":[{"raw_affiliation_string":"University of G\u00f6ttingen, G\u00f6ttingen, Germany","institution_ids":["https://openalex.org/I74656192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019536517","display_name":"Sebastian Zug","orcid":"https://orcid.org/0000-0001-9949-6963"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke University Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Zug","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082293980","display_name":"Rudolf Kruse","orcid":"https://orcid.org/0000-0003-4981-2758"},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke University Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rudolf Kruse","raw_affiliation_strings":["Otto-von-Guericke University, Magdeburg, Germany"],"affiliations":[{"raw_affiliation_string":"Otto-von-Guericke University, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5030699969"],"corresponding_institution_ids":["https://openalex.org/I1319473763"],"apc_list":null,"apc_paid":null,"fwci":1.2285,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82959024,"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":"239","last_page":"246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980000257492065,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7367364168167114},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.63799649477005},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5679794549942017},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5396646857261658},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5249692797660828},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.48491746187210083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45529675483703613},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.45202940702438354},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.45157590508461},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.44248923659324646},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4395589232444763},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42130371928215027},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37428581714630127},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1263504922389984},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09660559892654419}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7367364168167114},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.63799649477005},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5679794549942017},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5396646857261658},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5249692797660828},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.48491746187210083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45529675483703613},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.45202940702438354},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.45157590508461},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.44248923659324646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4395589232444763},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42130371928215027},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37428581714630127},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1263504922389984},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09660559892654419},{"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi.2017.8170435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W33116912","https://openalex.org/W335176846","https://openalex.org/W595289004","https://openalex.org/W1898022672","https://openalex.org/W1904741086","https://openalex.org/W1939911110","https://openalex.org/W1965406246","https://openalex.org/W1983812652","https://openalex.org/W1990004830","https://openalex.org/W2010212339","https://openalex.org/W2029551042","https://openalex.org/W2038091120","https://openalex.org/W2058619411","https://openalex.org/W2061352600","https://openalex.org/W2065436291","https://openalex.org/W2067026624","https://openalex.org/W2070494544","https://openalex.org/W2073438269","https://openalex.org/W2101704004","https://openalex.org/W2105934661","https://openalex.org/W2116455382","https://openalex.org/W2119112357","https://openalex.org/W2125656467","https://openalex.org/W2131076267","https://openalex.org/W2132529495","https://openalex.org/W2134160453","https://openalex.org/W2134214630","https://openalex.org/W2138817862","https://openalex.org/W2151823166","https://openalex.org/W2158233573","https://openalex.org/W2159132531","https://openalex.org/W2159163626","https://openalex.org/W2163436257","https://openalex.org/W2165445293","https://openalex.org/W2167222293","https://openalex.org/W2170736835","https://openalex.org/W2172108060","https://openalex.org/W2342840547","https://openalex.org/W2493603909","https://openalex.org/W2499555401","https://openalex.org/W2511969587","https://openalex.org/W2588654400","https://openalex.org/W2588793231","https://openalex.org/W2771646352","https://openalex.org/W2912268514","https://openalex.org/W2963522331","https://openalex.org/W4231896139","https://openalex.org/W4244440284","https://openalex.org/W6601344910","https://openalex.org/W6680525522","https://openalex.org/W6704559304","https://openalex.org/W6734153576"],"related_works":["https://openalex.org/W2091018038","https://openalex.org/W2225378543","https://openalex.org/W4287122200","https://openalex.org/W3162200841","https://openalex.org/W2593280956","https://openalex.org/W2004312940","https://openalex.org/W1909961747","https://openalex.org/W1938318326","https://openalex.org/W1969479488","https://openalex.org/W2915633022"],"abstract_inverted_index":{"Lane":[0],"estimation":[1,94,102],"plays":[2],"a":[3,32,50,117],"central":[4],"role":[5],"for":[6,90,185],"Driver":[7],"Assistance":[8],"Systems,":[9],"therefore":[10],"many":[11],"approaches":[12],"have":[13],"been":[14],"proposed":[15],"to":[16,62,141,156,192],"measure":[17],"its":[18],"performance.":[19],"However,":[20],"no":[21],"commonly":[22],"agreed":[23],"metric":[24,113,231],"exists.":[25],"In":[26],"this":[27,186,215],"work,":[28],"we":[29,76,228],"first":[30],"present":[31],"detailed":[33,170],"survey":[34],"of":[35,40,213],"the":[36,68,91,105,131,158,160,164,180,200,211,221],"current":[37],"measures.":[38],"Most":[39],"them":[41],"apply":[42],"pixel-level":[43],"benchmarks":[44],"on":[45],"camera":[46],"images":[47],"and":[48,52,80,87,104,121,127,169,177,188,205],"require":[49,116],"time-consuming":[51],"fault-prone":[53],"labeling":[54,119],"process.":[55],"Moreover,":[56],"these":[57],"metrics":[58,235],"cannot":[59],"be":[60,123,139],"used":[61,124,209],"assess":[63],"other":[64,73,233],"sources":[65],"such":[66],"as":[67],"detected":[69],"guardrails,":[70],"curbs":[71],"or":[72,163],"vehicles.":[74],"Therefore,":[75],"introduce":[77],"an":[78,85],"efficient":[79],"sensor-independent":[81],"metric,":[82],"which":[83],"provides":[84],"objective":[86],"intuitive":[88],"self-assessment":[89],"entire":[92],"road":[93,143],"process":[95],"at":[96],"multiple":[97],"levels:":[98],"individual":[99],"detectors,":[100],"lane":[101,109],"itself,":[103],"target":[106],"applications":[107],"(e.g.,":[108],"keeping":[110],"system).":[111],"Our":[112],"does":[114],"not":[115],"high":[118],"effort":[120],"can":[122,138],"both":[125,175],"online":[126],"offline.":[128],"By":[129,146],"selecting":[130],"evaluated":[132],"points":[133],"in":[134,148,210],"specific":[135],"distances,":[136],"it":[137,189],"applied":[140],"any":[142],"model":[144],"representation.":[145],"comparing":[147],"2D":[149],"vehicle":[150],"coordinate":[151],"system,":[152],"two":[153],"possibilities":[154],"exist":[155],"generate":[157],"ground-truth:":[159],"human-driven":[161,181],"path":[162,182],"expensive":[165],"alternative":[166],"with":[167,232],"DGPS":[168],"maps.":[171],"This":[172],"paper":[173,216],"applies":[174],"methods":[176],"reveals":[178],"that":[179,218],"also":[183],"qualifies":[184],"task":[187],"is":[190,207,224],"applicable":[191],"scenarios":[193],"without":[194],"GPS":[195],"signal,":[196],"e.g.,":[197],"tunnel.":[198],"Although":[199],"lateral":[201],"offset":[202],"between":[203],"reference":[204],"detection":[206],"widely":[208],"majority":[212],"works,":[214],"shows":[217],"another":[219],"criterion,":[220],"angle":[222],"deviation,":[223],"more":[225],"appropriate.":[226],"Finally,":[227],"compare":[229],"our":[230],"state-of-the-art":[234],"using":[236],"real":[237],"data":[238],"recordings":[239],"from":[240],"different":[241],"scenarios.":[242]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
