{"id":"https://openalex.org/W2126687488","doi":"https://doi.org/10.1109/tits.2012.2218237","title":"Efficient Traffic State Estimation for Large-Scale Urban Road Networks","display_name":"Efficient Traffic State Estimation for Large-Scale Urban Road Networks","publication_year":2012,"publication_date":"2012-11-21","ids":{"openalex":"https://openalex.org/W2126687488","doi":"https://doi.org/10.1109/tits.2012.2218237","mag":"2126687488"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2012.2218237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2012.2218237","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","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/A5101735181","display_name":"Qing\u2010Jie Kong","orcid":"https://orcid.org/0000-0002-3788-305X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing-Jie Kong","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China","State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103179555","display_name":"Qiankun Zhao","orcid":"https://orcid.org/0000-0002-2635-3328"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiankun Zhao","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China","IBM China Research Laboratory, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"IBM China Research Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023730987","display_name":"Chao Wei","orcid":"https://orcid.org/0000-0003-1581-8377"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wei","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061110835","display_name":"Yuncai Liu","orcid":"https://orcid.org/0000-0002-4040-4478"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuncai Liu","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101735181"],"corresponding_institution_ids":["https://openalex.org/I183067930","https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":8.7622,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.97624577,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"14","issue":"1","first_page":"398","last_page":"407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","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"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/global-positioning-system","display_name":"Global Positioning System","score":0.8476415276527405},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.663668692111969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5522834062576294},{"id":"https://openalex.org/keywords/digital-mapping","display_name":"Digital mapping","score":0.5285431742668152},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5214309692382812},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5053694844245911},{"id":"https://openalex.org/keywords/downtown","display_name":"Downtown","score":0.46511557698249817},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.444631427526474},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.41237741708755493},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.28403618931770325},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.25439536571502686},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24625977873802185},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.24603432416915894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20777693390846252},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.18838858604431152},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.18283382058143616},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11896052956581116},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09894850850105286}],"concepts":[{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.8476415276527405},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.663668692111969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5522834062576294},{"id":"https://openalex.org/C181672929","wikidata":"https://www.wikidata.org/wiki/Q4115141","display_name":"Digital mapping","level":2,"score":0.5285431742668152},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5214309692382812},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5053694844245911},{"id":"https://openalex.org/C2776556313","wikidata":"https://www.wikidata.org/wiki/Q1050303","display_name":"Downtown","level":2,"score":0.46511557698249817},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.444631427526474},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.41237741708755493},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.28403618931770325},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.25439536571502686},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24625977873802185},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.24603432416915894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20777693390846252},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.18838858604431152},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.18283382058143616},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11896052956581116},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09894850850105286},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2012.2218237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2012.2218237","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1490699950","https://openalex.org/W1617152041","https://openalex.org/W1974926843","https://openalex.org/W1988466776","https://openalex.org/W1989608371","https://openalex.org/W1990834404","https://openalex.org/W2000854095","https://openalex.org/W2031346385","https://openalex.org/W2058200155","https://openalex.org/W2071510389","https://openalex.org/W2085234095","https://openalex.org/W2100378013","https://openalex.org/W2101022200","https://openalex.org/W2105901624","https://openalex.org/W2125371460","https://openalex.org/W2134336255","https://openalex.org/W2138296406","https://openalex.org/W2145438115","https://openalex.org/W2156828505","https://openalex.org/W2157428127","https://openalex.org/W2158054751","https://openalex.org/W2167079720","https://openalex.org/W2168802877","https://openalex.org/W6629233169"],"related_works":["https://openalex.org/W4205268161","https://openalex.org/W2185134528","https://openalex.org/W2891070750","https://openalex.org/W2516160486","https://openalex.org/W1861932442","https://openalex.org/W2047022258","https://openalex.org/W1880567472","https://openalex.org/W1606048439","https://openalex.org/W2465912761","https://openalex.org/W2389441598"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,88],"systematic":[4],"solution":[5,86],"to":[6,23],"efficiently":[7],"estimate":[8],"the":[9,20,25,36,40,45,57,68,73,78,84,99,107,118,128,139,142,150,156,162,165,172,189,198],"traffic":[10,41,69,199],"state":[11,42,70,200],"of":[12,91,103,112,127,141,201],"large-scale":[13,151,202],"urban":[14,152,203],"road":[15,153,179,204],"networks.":[16,205],"We":[17],"first":[18],"propose":[19],"new":[21],"approach":[22],"construct":[24],"exact":[26,31],"GIS-T":[27],"digital":[28,32,101],"map.":[29],"The":[30,121,184],"map":[33,102],"can":[34],"lay":[35],"solid":[37],"foundation":[38],"for":[39,67,149],"estimation":[43,122],"with":[44,87],"data":[46,93,109],"from":[47,94,110],"Global":[48],"Positioning":[49],"System":[50],"(GPS)":[51],"probe":[52,65,96,119],"vehicles.":[53,120],"Then,":[54],"we":[55,82],"present":[56],"following":[58],"two":[59,129],"effective":[60,193],"methods":[61,131,191],"based":[62],"on":[63,177],"GPS":[64,95,143],"vehicles":[66,97],"estimation:":[71],"(1)":[72],"curve-fitting-based":[74],"method":[75],"and":[76,98,124,135,158,194],"(2)":[77],"vehicle-tracking-based":[79],"method.":[80],"Finally,":[81],"test":[83],"proposed":[85,190],"large":[89],"number":[90],"real":[92],"standard":[100],"Shanghai,":[104],"China.":[105],"In":[106,137],"experiments,":[108],"thousands":[111],"GPS-equipped":[113],"taxies":[114],"were":[115,132,146,175],"taken":[116],"as":[117],"accuracy":[123,163],"operation":[125],"speed":[126],"different":[130],"systematically":[133],"measured":[134],"compared.":[136],"addition,":[138],"coverages":[140],"sampling":[144],"points":[145],"also":[147],"investigated":[148],"network":[154],"in":[155,181,196],"spatial":[157],"temporal":[159],"domains.":[160],"For":[161],"experiment,":[164],"ground":[166],"truth":[167],"was":[168],"obtained":[169],"by":[170],"repeating":[171],"videos":[173],"that":[174,188],"recorded":[176],"24":[178],"sections":[180],"downtown":[182],"Shanghai.":[183],"experimental":[185],"results":[186],"illustrate":[187],"are":[192],"efficient":[195],"monitoring":[197]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
