{"id":"https://openalex.org/W2768434802","doi":"https://doi.org/10.1145/3132340.3132356","title":"Tracking Vehicles Equipped with Dedicated Short-Range Communication at Traffic Intersections","display_name":"Tracking Vehicles Equipped with Dedicated Short-Range Communication at Traffic Intersections","publication_year":2017,"publication_date":"2017-11-15","ids":{"openalex":"https://openalex.org/W2768434802","doi":"https://doi.org/10.1145/3132340.3132356","mag":"2768434802"},"language":"en","primary_location":{"id":"doi:10.1145/3132340.3132356","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132340.3132356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications","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/A5074789327","display_name":"Patrick Emami","orcid":"https://orcid.org/0000-0001-7846-5578"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Patrick Emami","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057923918","display_name":"Lily Elefteriadou","orcid":"https://orcid.org/0000-0003-4045-3365"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lily Elefteriadou","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077570468","display_name":"Sanjay Ranka","orcid":"https://orcid.org/0000-0003-4886-1988"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjay Ranka","raw_affiliation_strings":["University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074789327"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.8315,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81305745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9975000023841858,"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":0.6567476987838745},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5500137805938721},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5135079026222229},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.41175079345703125},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3572413921356201},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.33471813797950745},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22041112184524536},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.10605460405349731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6567476987838745},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5500137805938721},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5135079026222229},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.41175079345703125},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3572413921356201},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.33471813797950745},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22041112184524536},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.10605460405349731},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3132340.3132356","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132340.3132356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2117550922","display_name":null,"funder_award_id":"BDV31, TWO 977-45","funder_id":"https://openalex.org/F4320309978","funder_display_name":"Florida Department of Transportation"},{"id":"https://openalex.org/G3662242608","display_name":null,"funder_award_id":"1446813","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309978","display_name":"Florida Department of Transportation","ror":"https://ror.org/01v2vzt58"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1500961935","https://openalex.org/W1514095306","https://openalex.org/W1568122762","https://openalex.org/W1894033869","https://openalex.org/W1973293707","https://openalex.org/W1976877689","https://openalex.org/W1982770030","https://openalex.org/W2103323962","https://openalex.org/W2131390079","https://openalex.org/W2160337655","https://openalex.org/W2336416123","https://openalex.org/W2427105973","https://openalex.org/W2527545631","https://openalex.org/W2563429800","https://openalex.org/W2563658259","https://openalex.org/W2730504761","https://openalex.org/W2769601620","https://openalex.org/W2963298573","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2130966263","https://openalex.org/W2153913439","https://openalex.org/W2363207358","https://openalex.org/W1967523843","https://openalex.org/W1519398290","https://openalex.org/W2056851291","https://openalex.org/W2348770236","https://openalex.org/W2363789696","https://openalex.org/W2889205661","https://openalex.org/W1995995628"],"abstract_inverted_index":{"In":[0,82,113],"the":[1,4,32,59,77,93,99,105,126,171,195,211,214],"near":[2],"future,":[3],"traffic":[5,35,55,78,94,133],"stream":[6],"will":[7,27],"contain":[8],"both":[9],"connected":[10],"and":[11,44,54,73,157,181],"autonomous":[12],"vehicles":[13,68],"with":[14,71,145,149,185],"Dedicated":[15],"Short-Range":[16],"Communication":[17],"(DSRC)":[18],"vehicle-to-infrastructure":[19],"(V2I)":[20],"capabilities.":[21],"With":[22],"these":[23],"new":[24],"technologies,":[25],"it":[26,110],"become":[28],"possible":[29],"to":[30,69,84,97,124,162],"optimize":[31],"performance":[33,172,212],"of":[34,76,104,107,128,170,173,191,213],"intersections":[36],"so":[37],"that":[38,206],"wasted":[39],"time":[40],"at":[41,62,92],"red":[42],"lights":[43],"carbon":[45],"emissions":[46],"are":[47],"minimized.":[48],"Sensors,":[49],"such":[50],"as":[51],"Doppler":[52],"radar":[53],"cameras,":[56],"can":[57],"use":[58],"data":[60,138,197],"received":[61,139],"Road-Side":[63],"Units":[64],"(RSUs)":[65],"from":[66],"DSRC-equipped":[67],"assist":[70],"tracking":[72,119],"classifying":[74],"all":[75],"approaching":[79,131],"an":[80],"intersection.":[81],"order":[83],"fuse":[85],"information":[86],"between":[87],"multiple":[88],"sensors,":[89],"each":[90],"sensor":[91,161],"intersection":[95,134],"needs":[96],"compute":[98],"uncertainty":[100],"about":[101],"its":[102],"estimate":[103,125],"state":[106,127],"every":[108],"vehicle":[109,130,147],"is":[111,201],"tracking.":[112],"this":[114],"work,":[115],"we":[116,204],"evaluate":[117],"different":[118,186],"filters":[120,216],"for":[121],"their":[122],"ability":[123],"a":[129,132,146,150,158,168,174],"based":[135],"on":[136],"GPS":[137,160,196],"over":[140],"DSRC.":[141],"We":[142,166],"ran":[143],"experiments":[144],"equipped":[148],"Cohda":[151],"Wireless":[152],"Mk5":[153],"On-Board":[154],"Unit":[155],"(OBU)":[156],"high-precision":[159],"generate":[163],"ground-truth":[164],"data.":[165],"present":[167],"comparison":[169],"linear":[175],"Kalman":[176,179],"filter,":[177,180],"extended":[178],"particle":[182],"filter":[183],"configured":[184],"kinematics":[187],"models.":[188],"The":[189],"effects":[190],"measurement":[192],"bias":[193,209],"in":[194,198],"DSRC":[199],"messages":[200],"also":[202],"explored;":[203],"observe":[205],"without":[207],"any":[208],"estimation,":[210],"track":[215],"degrades":[217],"significantly.":[218]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}