{"id":"https://openalex.org/W3117165346","doi":"https://doi.org/10.1109/itsc45102.2020.9294222","title":"Efficient Occupancy Grid Mapping and Camera-LiDAR Fusion for Conditional Imitation Learning Driving","display_name":"Efficient Occupancy Grid Mapping and Camera-LiDAR Fusion for Conditional Imitation Learning Driving","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3117165346","doi":"https://doi.org/10.1109/itsc45102.2020.9294222","mag":"3117165346"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5083360810","display_name":"Hesham M. Eraqi","orcid":"https://orcid.org/0000-0001-9430-7553"},"institutions":[{"id":"https://openalex.org/I80693520","display_name":"American University in Cairo","ror":"https://ror.org/0176yqn58","country_code":"EG","type":"education","lineage":["https://openalex.org/I80693520"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Hesham M. Eraqi","raw_affiliation_strings":["The American University in Cairo,Computer Science & Engineering department,Egypt","The American University in Cairo, Egypt; Valeo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The American University in Cairo,Computer Science & Engineering department,Egypt","institution_ids":["https://openalex.org/I80693520"]},{"raw_affiliation_string":"The American University in Cairo, Egypt; Valeo","institution_ids":["https://openalex.org/I80693520"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mohamed N. Moustafa","orcid":null},"institutions":[{"id":"https://openalex.org/I80693520","display_name":"American University in Cairo","ror":"https://ror.org/0176yqn58","country_code":"EG","type":"education","lineage":["https://openalex.org/I80693520"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed N. Moustafa","raw_affiliation_strings":["The American University in Cairo,Computer Science & Engineering department,Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The American University in Cairo,Computer Science & Engineering department,Egypt","institution_ids":["https://openalex.org/I80693520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003616544","display_name":"Jens Honer","orcid":null},"institutions":[{"id":"https://openalex.org/I220619192","display_name":"Valeo (France)","ror":"https://ror.org/04ryqpf83","country_code":"FR","type":"company","lineage":["https://openalex.org/I220619192"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jens Honer","raw_affiliation_strings":["Valeo.,Driving Assistance department"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo.,Driving Assistance department","institution_ids":["https://openalex.org/I220619192"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7947,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.80030776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10531","display_name":"Advanced Vision and Imaging","score":0.9988999962806702,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.9032607078552246},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7591727375984192},{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.7505080699920654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.679449200630188},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6501076817512512},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.5726991891860962},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5505743026733398},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5353641510009766},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5120030045509338},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4815557301044464},{"id":"https://openalex.org/keywords/grid-cell","display_name":"Grid cell","score":0.41094672679901123},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.2029227912425995},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12445086240768433},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.11958345770835876},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10541412234306335},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06757965683937073}],"concepts":[{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.9032607078552246},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7591727375984192},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.7505080699920654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.679449200630188},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6501076817512512},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5726991891860962},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5505743026733398},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5353641510009766},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5120030045509338},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4815557301044464},{"id":"https://openalex.org/C2983008078","wikidata":"https://www.wikidata.org/wiki/Q863495","display_name":"Grid cell","level":3,"score":0.41094672679901123},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2029227912425995},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12445086240768433},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.11958345770835876},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10541412234306335},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06757965683937073},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W80201019","https://openalex.org/W1999050017","https://openalex.org/W2006890787","https://openalex.org/W2055207897","https://openalex.org/W2086356840","https://openalex.org/W2095705004","https://openalex.org/W2115579991","https://openalex.org/W2119112357","https://openalex.org/W2125420246","https://openalex.org/W2163605009","https://openalex.org/W2167224731","https://openalex.org/W2168137830","https://openalex.org/W2336416123","https://openalex.org/W2342840547","https://openalex.org/W2529646329","https://openalex.org/W2559767995","https://openalex.org/W2761595090","https://openalex.org/W2901316471","https://openalex.org/W2905173465","https://openalex.org/W2912346386","https://openalex.org/W2937814560","https://openalex.org/W2955181123","https://openalex.org/W2955189650","https://openalex.org/W2962867954","https://openalex.org/W2962894046","https://openalex.org/W2963439114","https://openalex.org/W2963579094","https://openalex.org/W2963647876","https://openalex.org/W2963881378","https://openalex.org/W2964193755","https://openalex.org/W2989878538","https://openalex.org/W3040318838","https://openalex.org/W4293580146","https://openalex.org/W4293682399","https://openalex.org/W4295719664","https://openalex.org/W4300124531","https://openalex.org/W6674330103","https://openalex.org/W6678097026","https://openalex.org/W6684191040","https://openalex.org/W6704559304","https://openalex.org/W6728300634","https://openalex.org/W6737309142","https://openalex.org/W6744454805","https://openalex.org/W6745935785","https://openalex.org/W6756871163"],"related_works":["https://openalex.org/W1999050017","https://openalex.org/W5037887","https://openalex.org/W4229444815","https://openalex.org/W4293877624","https://openalex.org/W1992005931","https://openalex.org/W3033776171","https://openalex.org/W3121103700","https://openalex.org/W2162255319","https://openalex.org/W2004240842","https://openalex.org/W2016986216"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"trained":[3,133],"end-to-end":[4],"on":[5,39,124,134],"demonstrations":[6],"of":[7,86],"human":[8],"driving":[9,108,115,126,139],"have":[10],"learned":[11],"to":[12,23,34,50,67,94,99],"follow":[13],"roads,":[14],"avoid":[15],"obstacles,":[16],"and":[17,53,92,118,128,146],"take":[18],"specific":[19],"turns":[20],"in":[21],"intersections":[22],"reach":[24],"a":[25,63,82],"destination.":[26],"Such":[27],"conditional":[28],"imitation":[29],"learning":[30],"approach":[31],"is":[32,54,90],"demonstrated":[33],"drive":[35],"efficiently":[36],"when":[37,48],"deployed":[38,49],"the":[40,79,96,102,110],"same":[41],"training":[42],"environments,":[43],"but":[44],"performance":[45],"dramatically":[46],"decreases":[47],"new":[51,83],"environments":[52,129],"not":[55],"consistent":[56],"against":[57],"varying":[58],"weathers.":[59],"In":[60],"this":[61],"work,":[62],"proposed":[64,111],"model":[65,97],"aims":[66],"cope":[68],"with":[69,78],"such":[70],"two":[71],"challenges":[72],"by":[73,144,150],"fusing":[74],"laser":[75],"scanner":[76],"input":[77],"camera.":[80],"Additionally,":[81],"efficient":[84],"method":[85],"Occupancy":[87],"Grid":[88],"Mapping":[89],"introduced":[91],"used":[93],"rectify":[95],"output":[98],"further":[100],"improve":[101],"performance.":[103],"On":[104],"CARLA":[105],"simulator":[106],"urban":[107],"benchmark,":[109],"system":[112],"improves":[113,143],"autonomous":[114],"success":[116,140],"rate":[117,141],"average":[119],"distance":[120],"traveled":[121],"towards":[122],"destination":[123],"all":[125],"tasks":[127],"combinations,":[130],"while":[131],"it\u2019s":[132],"automatically":[135],"recorded":[136],"traces.":[137],"Autonomous":[138],"generalization":[142],"57%":[145],"weather":[147],"consistency":[148],"improved":[149],"around":[151],"four":[152],"times.":[153]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}