{"id":"https://openalex.org/W4383899715","doi":"https://doi.org/10.1109/tiv.2023.3293954","title":"BEV-V2X: Cooperative Birds-Eye-View Fusion and Grid Occupancy Prediction via V2X-Based Data Sharing","display_name":"BEV-V2X: Cooperative Birds-Eye-View Fusion and Grid Occupancy Prediction via V2X-Based Data Sharing","publication_year":2023,"publication_date":"2023-07-11","ids":{"openalex":"https://openalex.org/W4383899715","doi":"https://doi.org/10.1109/tiv.2023.3293954"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2023.3293954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3293954","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Transactions on Intelligent Vehicles","raw_type":"journal-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/A5002066189","display_name":"Cheng Chang","orcid":"https://orcid.org/0000-0003-2768-5866"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Chang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2768-5866","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100462845","display_name":"Jiawei Zhang","orcid":"https://orcid.org/0000-0002-8634-1687"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawei Zhang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8634-1687","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449447","display_name":"Kunpeng Zhang","orcid":"https://orcid.org/0000-0003-1979-4261"},"institutions":[{"id":"https://openalex.org/I36152291","display_name":"Henan University of Technology","ror":"https://ror.org/05sbgwt55","country_code":"CN","type":"education","lineage":["https://openalex.org/I36152291"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunpeng Zhang","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China","College of Electrical Engineering, Henan University of Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"College of Electrical Engineering, Henan University of Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I36152291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011097997","display_name":"Wenqin Zhong","orcid":"https://orcid.org/0000-0001-6239-2909"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqin Zhong","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027536715","display_name":"Xinyu Peng","orcid":"https://orcid.org/0000-0002-7181-2159"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Peng","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7181-2159","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107117626","display_name":"Shen Li","orcid":"https://orcid.org/0000-0002-7111-8861"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shen Li","raw_affiliation_strings":["Department of Civil Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7111-8861","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114911316","display_name":"Li Li","orcid":"https://orcid.org/0000-0002-9428-1960"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["Department of Automation, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9428-1960","affiliations":[{"raw_affiliation_string":"Department of Automation, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3504,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.95813142,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":"11","first_page":"4498","last_page":"4514"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/computer-science","display_name":"Computer science","score":0.7138650417327881},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6146793365478516},{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.5795711874961853},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5653561353683472},{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.5132062435150146},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5023980140686035},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.44595175981521606},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4402518570423126},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4319641590118408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4144384562969208},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3605259954929352},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.127358078956604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138650417327881},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6146793365478516},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.5795711874961853},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5653561353683472},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.5132062435150146},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5023980140686035},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.44595175981521606},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4402518570423126},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4319641590118408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4144384562969208},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3605259954929352},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.127358078956604},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"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/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2023.3293954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3293954","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Transactions on Intelligent Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G298791016","display_name":null,"funder_award_id":"52272420","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W2071571922","https://openalex.org/W2081438358","https://openalex.org/W2105617589","https://openalex.org/W2115579991","https://openalex.org/W2135825595","https://openalex.org/W2142887887","https://openalex.org/W2142895728","https://openalex.org/W2144357069","https://openalex.org/W2149649818","https://openalex.org/W2194775991","https://openalex.org/W2290903295","https://openalex.org/W2340897893","https://openalex.org/W2476721060","https://openalex.org/W2519091744","https://openalex.org/W2521921275","https://openalex.org/W2743840443","https://openalex.org/W2766585573","https://openalex.org/W2896642734","https://openalex.org/W2923088732","https://openalex.org/W2944851425","https://openalex.org/W2947439027","https://openalex.org/W2948515602","https://openalex.org/W2953303875","https://openalex.org/W2955189650","https://openalex.org/W2963853051","https://openalex.org/W2980087597","https://openalex.org/W2982681137","https://openalex.org/W3008052774","https://openalex.org/W3028320132","https://openalex.org/W3034669477","https://openalex.org/W3035054225","https://openalex.org/W3035574168","https://openalex.org/W3081125129","https://openalex.org/W3098774053","https://openalex.org/W3101475896","https://openalex.org/W3102343027","https://openalex.org/W3109991383","https://openalex.org/W3128155778","https://openalex.org/W3155776565","https://openalex.org/W3160112148","https://openalex.org/W3164817606","https://openalex.org/W3170672542","https://openalex.org/W3172477795","https://openalex.org/W3174850769","https://openalex.org/W3184466352","https://openalex.org/W3201193904","https://openalex.org/W3203158837","https://openalex.org/W4200086871","https://openalex.org/W4211176245","https://openalex.org/W4214895168","https://openalex.org/W4226078411","https://openalex.org/W4226239849","https://openalex.org/W4226345352","https://openalex.org/W4226436200","https://openalex.org/W4281685999","https://openalex.org/W4283028672","https://openalex.org/W4283392354","https://openalex.org/W4284701604","https://openalex.org/W4285121103","https://openalex.org/W4285266601","https://openalex.org/W4288712624","https://openalex.org/W4295832484","https://openalex.org/W4296079511","https://openalex.org/W4296425724","https://openalex.org/W4308068359","https://openalex.org/W4311243060","https://openalex.org/W4312604822","https://openalex.org/W4312857200","https://openalex.org/W4312894406","https://openalex.org/W4312939270","https://openalex.org/W4323647389","https://openalex.org/W4366957398","https://openalex.org/W6739901393","https://openalex.org/W6767619714","https://openalex.org/W6768870957","https://openalex.org/W6790534506","https://openalex.org/W6802966573","https://openalex.org/W6839180059"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W2162255319","https://openalex.org/W3033776171","https://openalex.org/W1999050017","https://openalex.org/W5037887","https://openalex.org/W4229444815","https://openalex.org/W4293877624","https://openalex.org/W1992005931","https://openalex.org/W1538887534"],"abstract_inverted_index":{"Birds-Eye-View":[0],"(BEV)":[1],"perception":[2,46,203],"can":[3,183],"naturally":[4],"represent":[5],"natural":[6],"scenes,":[7,28],"which":[8,29],"is":[9],"conducive":[10],"to":[11,37,63],"multimodal":[12],"data":[13,18,95],"processing":[14],"and":[15,22,54,57,66,99,109,132,144,187,205,211],"fusion.":[16],"BEV":[17,41,94,114,142],"contain":[19],"rich":[20],"semantics":[21],"integrate":[23],"the":[24,72,104,111,152,181,195,198,209],"information":[25],"of":[26,154,158,197],"driving":[27,67,123,127],"play":[30],"an":[31,139],"important":[32],"role":[33],"in":[34,173],"researches":[35],"related":[36],"autonomous":[38],"driving.":[39],"However,":[40],"constructed":[42],"by":[43],"single":[44,159,201],"vehicle":[45,160,202],"encounter":[47],"certain":[48],"issues,":[49],"such":[50],"as":[51],"low":[52],"accuracy":[53],"insufficient":[55],"range,":[56],"thus":[58],"cannot":[59],"be":[60],"well":[61],"applied":[62],"scenario":[64],"understanding":[65],"situation":[68],"prediction.":[69,161],"To":[70],"address":[71],"challenges,":[73],"this":[74],"article":[75],"proposes":[76],"a":[77],"novel":[78],"data-driven":[79],"approach":[80],"based":[81],"on":[82,208],"vehicle-to-everything":[83],"(V2X)":[84],"communication.":[85],"The":[86],"roadside":[87],"unit":[88],"or":[89],"cloud":[90],"center":[91],"collects":[92],"local":[93],"from":[96],"all":[97,177],"connected":[98],"automated":[100],"vehicles":[101,178],"(CAVs)":[102],"within":[103],"control":[105,131],"area,":[106],"then":[107],"fuses":[108],"predicts":[110],"future":[112],"global":[113,189],"occupancy":[115],"grid":[116,206],"map.":[117],"It":[118],"provides":[119],"powerful":[120],"support":[121],"for":[122],"safety":[124],"warning,":[125],"cooperative":[126,129,141],"planning,":[128],"traffic":[130],"other":[133],"applications.":[134],"More":[135],"precisely,":[136],"we":[137],"develop":[138],"attention-based":[140],"fusion":[143,210],"prediction":[145,212],"model":[146,182],"called":[147],"BEV-V2X.":[148],"We":[149,192],"also":[150,193],"compare":[151],"performance":[153],"BEV-V2X":[155],"with":[156],"that":[157,165],"Experimental":[162],"results":[163],"demonstrate":[164],"our":[166],"proposed":[167],"method":[168],"achieves":[169],"higher":[170],"accuracy.":[171],"Even":[172],"cases":[174],"where":[175],"not":[176],"are":[179],"CAVs,":[180],"still":[184],"comprehensively":[185],"estimate":[186],"predict":[188],"spatiotemporal":[190],"changes.":[191],"discuss":[194],"impact":[196],"CAV":[199],"rate,":[200],"ability,":[204],"size":[207],"results.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}