{"id":"https://openalex.org/W2149660853","doi":"https://doi.org/10.1109/ivs.2011.5940397","title":"Traffic density estimation under heterogeneous traffic conditions using data fusion","display_name":"Traffic density estimation under heterogeneous traffic conditions using data fusion","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2149660853","doi":"https://doi.org/10.1109/ivs.2011.5940397","mag":"2149660853"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2011.5940397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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/A5007568253","display_name":"Anand Ramkumar","orcid":"https://orcid.org/0000-0002-7505-6397"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"R. Asha Anand","raw_affiliation_strings":["Department of Civil Engineering, Indian Institute of Technology Chennai, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Indian Institute of Technology Chennai, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070390385","display_name":"Lelitha Vanajakshi","orcid":"https://orcid.org/0000-0002-1137-9656"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lelitha Vanajakshi","raw_affiliation_strings":["Department of Civil Engineering, Indian Institute of Technology Chennai, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Indian Institute of Technology Chennai, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039918256","display_name":"Shankar C. Subramanian","orcid":"https://orcid.org/0000-0001-6710-2202"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shankar C. Subramanian","raw_affiliation_strings":["Department of Engineering Design, Indian Institute of Technology Chennai, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Design, Indian Institute of Technology Chennai, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007568253"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":6.6333,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.96140781,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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/T10524","display_name":"Traffic control and management","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10698","display_name":"Transportation Planning and Optimization","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7698692083358765},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.7233690023422241},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6443743705749512},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5928749442100525},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.531897783279419},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.4983382225036621},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37367647886276245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2531692385673523},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22588902711868286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16972953081130981},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.11052653193473816}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7698692083358765},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.7233690023422241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6443743705749512},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5928749442100525},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.531897783279419},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.4983382225036621},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37367647886276245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2531692385673523},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22588902711868286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16972953081130981},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.11052653193473816},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2011.5940397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W32452329","https://openalex.org/W612685003","https://openalex.org/W1513927654","https://openalex.org/W1531358901","https://openalex.org/W1601640479","https://openalex.org/W1968616299","https://openalex.org/W1984328578","https://openalex.org/W1985986451","https://openalex.org/W2009395135","https://openalex.org/W2023601590","https://openalex.org/W2072400991","https://openalex.org/W2075249328","https://openalex.org/W2145438115","https://openalex.org/W2152196380","https://openalex.org/W2488454393","https://openalex.org/W2491009754","https://openalex.org/W3022404379","https://openalex.org/W3125192562","https://openalex.org/W6619062350","https://openalex.org/W6635749825","https://openalex.org/W6681222055","https://openalex.org/W6789950532"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2103761320","https://openalex.org/W2358167375","https://openalex.org/W2031992971","https://openalex.org/W116564642","https://openalex.org/W1983380679","https://openalex.org/W1981649169","https://openalex.org/W2357354286","https://openalex.org/W2388705266","https://openalex.org/W2113617130"],"abstract_inverted_index":{"Data":[0],"fusion":[1,186],"is":[2,78,83,100],"one":[3,33],"of":[4,17,49,73,117],"the":[5,12,23,28,47,66,71,126,133,169,182],"recent":[6],"approaches":[7],"in":[8],"traffic":[9,18,51,74],"analysis":[10],"for":[11,35,70],"accurate":[13],"estimation":[14,72,149],"and":[15,56,90,132,152,181],"prediction":[16],"parameters.":[19,119],"In":[20],"this":[21],"approach,":[22],"parameters":[24,48,107],"are":[25,176],"estimated":[26,102],"using":[27,52,59,95,125,150,168,178],"data":[29,55,58,60,161,185],"from":[30,88,103,114,130,137,158],"more":[31],"than":[32],"source":[34],"better":[36,188],"accuracy.":[37],"This":[38],"paper":[39],"discusses":[40],"a":[41,79,115],"model":[42],"based":[43,160],"approach":[44],"to":[45,85],"estimate":[46],"heterogeneous":[50],"both":[53],"location":[54,159],"spatial":[57,80,166],"fusion.":[61],"The":[62,120,144,174],"proposed":[63],"method":[64],"uses":[65],"Kalman":[67,171],"filtering":[68],"technique":[69],"density.":[75,191],"Traffic":[76],"density":[77,124,148],"parameter":[81],"which":[82],"difficult":[84],"measure":[86],"directly":[87],"field":[89],"can":[91],"be":[92],"measured":[93,129],"only":[94],"aerial":[96],"photography.":[97],"Hence,":[98],"it":[99],"usually":[101],"other":[104],"easily":[105],"measurable":[106],"such":[108,118],"as":[109],"speed,":[110],"flow,":[111],"etc.,":[112],"or":[113],"combination":[116],"present":[121],"study":[122,145],"estimates":[123,175],"flow":[127,151],"values":[128,180],"video":[131],"travel":[134],"time":[135],"obtained":[136,157],"Global":[138],"Positioning":[139],"System":[140],"(GPS)":[141],"equipped":[142],"vehicles.":[143],"also":[146],"reports":[147],"Space":[153],"Mean":[154],"Speed":[155],"(SMS)":[156],"alone":[162],"without":[163],"fusing":[164],"with":[165],"data,":[167],"Extended":[170],"filter":[172],"technique.":[173],"corroborated":[177],"actual":[179],"results":[183],"show":[184],"performing":[187],"while":[189],"estimating":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}