{"id":"https://openalex.org/W2897876743","doi":"https://doi.org/10.1109/ivs.2018.8500543","title":"A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?","display_name":"A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2897876743","doi":"https://doi.org/10.1109/ivs.2018.8500543","mag":"2897876743"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2018.8500543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.03251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mario Bijelic","orcid":null},"institutions":[{"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":"Mario Bijelic","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tobias Gruber","orcid":null},"institutions":[{"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":"Tobias Gruber","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":null,"display_name":"Werner Ritter","orcid":null},"institutions":[{"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":"Werner Ritter","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I891521709"],"apc_list":null,"apc_paid":null,"fwci":23.623,"has_fulltext":false,"cited_by_count":170,"citation_normalized_percentile":{"value":0.99833055,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"760","last_page":"767"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9979000091552734,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.9185000061988831},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.8009999990463257},{"id":"https://openalex.org/keywords/adverse-weather","display_name":"Adverse weather","score":0.7415000200271606},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.641700029373169},{"id":"https://openalex.org/keywords/snow","display_name":"Snow","score":0.4165000021457672}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.9185000061988831},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.8009999990463257},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.7415000200271606},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.641700029373169},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6298999786376953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49480000138282776},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.474700003862381},{"id":"https://openalex.org/C197046000","wikidata":"https://www.wikidata.org/wiki/Q7561","display_name":"Snow","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C2777601987","wikidata":"https://www.wikidata.org/wiki/Q5283581","display_name":"Disturbance (geology)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3077000081539154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2888999879360199}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ivs.2018.8500543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.03251","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03251","pdf_url":"https://arxiv.org/pdf/1912.03251","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.03251","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03251","pdf_url":"https://arxiv.org/pdf/1912.03251","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1973444879","https://openalex.org/W1978564507","https://openalex.org/W1981491492","https://openalex.org/W1992967753","https://openalex.org/W2051484573","https://openalex.org/W2085857887","https://openalex.org/W2087019298","https://openalex.org/W2094658656","https://openalex.org/W2113551198","https://openalex.org/W2121880036","https://openalex.org/W2123253832","https://openalex.org/W2132476535","https://openalex.org/W2166323392","https://openalex.org/W2386963785","https://openalex.org/W2555618208","https://openalex.org/W2741964872","https://openalex.org/W6677392417","https://openalex.org/W6784807522"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1],"at":[2],"level":[3],"five":[4],"does":[5],"not":[6],"only":[7],"means":[8],"self-driving":[9],"in":[10,45,48,79],"the":[11,24,27,35,64,92],"sunshine.":[12],"Adverse":[13],"weather":[14,81],"is":[15,84],"especially":[16],"critical":[17],"because":[18,88],"fog,":[19],"rain,":[20],"and":[21,39,56],"snow":[22],"degrade":[23],"perception":[25],"of":[26,34,63,85,91],"environment.":[28],"In":[29],"this":[30],"work,":[31],"current":[32,54],"state":[33,62,90],"art":[36,65,93],"light":[37],"detection":[38,94],"ranging":[40],"(lidar)":[41],"sensors":[42],"are":[43,96],"tested":[44],"controlled":[46],"conditions":[47],"a":[49],"fog":[50],"chamber.":[51],"We":[52],"present":[53],"problems":[55],"disturbance":[57],"patterns":[58],"for":[59],"four":[60],"different":[61],"lidar":[66,100],"systems.":[67],"Moreover,":[68],"we":[69],"investigate":[70],"how":[71],"tuning":[72],"internal":[73],"parameters":[74],"can":[75],"improve":[76],"their":[77],"performance":[78],"bad":[80],"situations.":[82],"This":[83],"great":[86],"importance":[87],"most":[89],"algorithms":[95],"based":[97],"on":[98],"undisturbed":[99],"data.":[101]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2018-10-26T00:00:00"}
