{"id":"https://openalex.org/W4400232100","doi":"https://doi.org/10.1109/vnc61989.2024.10576012","title":"Poster: Risk and Redundancy-Based Object Selection Method for Collective Perception Messages in Cellular-V2x","display_name":"Poster: Risk and Redundancy-Based Object Selection Method for Collective Perception Messages in Cellular-V2x","publication_year":2024,"publication_date":"2024-05-29","ids":{"openalex":"https://openalex.org/W4400232100","doi":"https://doi.org/10.1109/vnc61989.2024.10576012"},"language":"en","primary_location":{"id":"doi:10.1109/vnc61989.2024.10576012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc61989.2024.10576012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Vehicular Networking Conference (VNC)","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/A5111246113","display_name":"Yuki Miyata","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuki Miyata","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080417719","display_name":"Yuuri Iwashina","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuuri Iwashina","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002392598","display_name":"Hiroshi Shigeno","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Shigeno","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University,Yokohama,Kanagawa,Japan,223-8522","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111246113"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.222,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50100943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"249","last_page":"250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9038000106811523,"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"}},"topics":[{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9038000106811523,"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/redundancy","display_name":"Redundancy (engineering)","score":0.8620760440826416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7602156400680542},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.663933277130127},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6442456245422363},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4240800440311432},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3549919128417969},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15320292115211487},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.054252684116363525}],"concepts":[{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.8620760440826416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602156400680542},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.663933277130127},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6442456245422363},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4240800440311432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3549919128417969},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15320292115211487},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.054252684116363525},{"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/vnc61989.2024.10576012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc61989.2024.10576012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Vehicular Networking Conference (VNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3386539412","display_name":null,"funder_award_id":"JP20H04180","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2979314428","https://openalex.org/W3039996319","https://openalex.org/W4376480782"],"related_works":["https://openalex.org/W1495042958","https://openalex.org/W2494338568","https://openalex.org/W2122678784","https://openalex.org/W2282510344","https://openalex.org/W139987158","https://openalex.org/W2183994405","https://openalex.org/W2628861693","https://openalex.org/W4205762803","https://openalex.org/W1875646599","https://openalex.org/W1976807322"],"abstract_inverted_index":{"Connected":[0],"and":[1,12,55,143,163,193,249],"Automated":[2],"Vehicles":[3],"(CAVs)":[4],"utilize":[5],"Vehicle-to-Everything":[6],"(V2X)":[7],"communication":[8,53,58],"to":[9,49,65,78,89,126],"exchange":[10,32],"messages":[11],"share":[13],"information":[14,24],"with":[15,33,245],"surrounding":[16,40,161,191],"vehicles.":[17],"Collective":[18],"Perception":[19],"Messages":[20],"(CPMs)":[21],"contain":[22],"object":[23,68,145],"detected":[25],"by":[26],"the":[27,31,39,80,91,104,110,116,157,164,184,194,200,205,221,241,250,253],"onboard":[28],"sensors.":[29],"Through":[30],"nearby":[34],"CAVs,":[35],"CAVs":[36,162,192],"can":[37,47],"perceive":[38],"objects.":[41,135],"Higher":[42],"vehicle":[43],"traffic":[44,81],"densities,":[45],"however,":[46,112],"lead":[48],"a":[50,62,66,127,141,179,189,214],"shortage":[51],"of":[52,57,83,94,106,109,118,130,166,183,196,207,217,252],"resources":[54],"degradation":[56],"quality.":[59],"This,":[60],"as":[61,180],"result,":[63],"leads":[64,125],"decreased":[67],"recognition":[69],"frequency.":[70],"To":[71],"mitigate":[72],"such":[73,134],"degradation,":[74],"it":[75,86,101],"is":[76,87],"necessary":[77],"reduce":[79],"volume":[82],"CPMs.":[84,95,107,210,224],"Therefore,":[85],"important":[88],"decrease":[90],"message":[92],"size":[93],"Various":[96],"existing":[97],"studies":[98],"aimed":[99],"at":[100],"have":[102],"reduced":[103],"redundancy":[105,165],"Most":[108],"studies,":[111],"do":[113],"not":[114],"prioritize":[115],"inclusion":[117],"high-accident":[119],"risk":[120,142],"objects":[121,152,208,218,244],"in":[122,168,231],"CPMs,":[123],"which":[124,150],"higher":[128],"Age":[129],"Information":[131],"(AoI)":[132],"for":[133,153,160,190,209,223,243],"In":[136,170],"this":[137,171],"paper,":[138],"we":[139,173],"propose":[140],"redundancy-based":[144],"selection":[146],"method,":[147],"called":[148],"RRS,":[149],"selects":[151],"CPMs":[154,167],"based":[155,219],"on":[156,188,220],"accident":[158,176,185,247],"risks":[159,248],"C-V2X.":[169],"proposal,":[172],"define":[174],"an":[175,181,232],"avoidance":[177],"acceleration":[178],"indicator":[182],"risks.":[186,255],"Based":[187],"number":[195,216,251],"CPM":[197],"receptions":[198],"indicating":[199],"redundancy,":[201],"CAV":[202,211],"s":[203,212],"calculate":[204],"priority":[206,222],"select":[213],"fixed":[215],"We":[225],"evaluate":[226],"RRS":[227,239],"through":[228],"simulation":[229],"experiments":[230],"intersection":[233],"scenario.":[234],"The":[235],"results":[236],"show":[237],"that":[238],"decreases":[240],"AoI":[242],"high":[246],"highest":[254]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}