{"id":"https://openalex.org/W2289501472","doi":"https://doi.org/10.1109/pccc.2015.7410307","title":"Traffic condition estimation using vehicular crowdsensing data","display_name":"Traffic condition estimation using vehicular crowdsensing data","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2289501472","doi":"https://doi.org/10.1109/pccc.2015.7410307","mag":"2289501472"},"language":"en","primary_location":{"id":"doi:10.1109/pccc.2015.7410307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pccc.2015.7410307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC)","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/A5013045071","display_name":"Lu Shao","orcid":"https://orcid.org/0009-0004-2150-9938"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lu Shao","raw_affiliation_strings":["Department of Computer Science, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101606331","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0001-7404-8785"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Department of Computer Science, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101729044","display_name":"Li Zhong","orcid":"https://orcid.org/0000-0002-7043-0239"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Li","raw_affiliation_strings":["Department of Communication Engineering, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Communication Engineering, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066099338","display_name":"Changjun Jiang","orcid":"https://orcid.org/0000-0003-0637-9317"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjun Jiang","raw_affiliation_strings":["Department of Computer Science, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013045071"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":2.514,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91480708,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9976000189781189,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/upload","display_name":"Upload","score":0.7765499353408813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7105827927589417},{"id":"https://openalex.org/keywords/crowdsensing","display_name":"Crowdsensing","score":0.5304158329963684},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.503356397151947},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4843974709510803},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4687654674053192},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.44244828820228577},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.4137706756591797},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.34025630354881287},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2783131003379822},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.2187769114971161},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13508033752441406},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13245579600334167}],"concepts":[{"id":"https://openalex.org/C71901391","wikidata":"https://www.wikidata.org/wiki/Q7126699","display_name":"Upload","level":2,"score":0.7765499353408813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7105827927589417},{"id":"https://openalex.org/C2780821482","wikidata":"https://www.wikidata.org/wiki/Q25381721","display_name":"Crowdsensing","level":2,"score":0.5304158329963684},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.503356397151947},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4843974709510803},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4687654674053192},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.44244828820228577},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.4137706756591797},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.34025630354881287},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2783131003379822},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.2187769114971161},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13508033752441406},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13245579600334167},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pccc.2015.7410307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pccc.2015.7410307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1947768731","https://openalex.org/W1966296731","https://openalex.org/W1972346388","https://openalex.org/W1973145806","https://openalex.org/W1975091065","https://openalex.org/W1977647505","https://openalex.org/W1982857754","https://openalex.org/W1986492449","https://openalex.org/W1992864126","https://openalex.org/W2008675681","https://openalex.org/W2016143382","https://openalex.org/W2027843963","https://openalex.org/W2042881845","https://openalex.org/W2042956327","https://openalex.org/W2049130312","https://openalex.org/W2050134713","https://openalex.org/W2052753508","https://openalex.org/W2058201718","https://openalex.org/W2067926144","https://openalex.org/W2071007744","https://openalex.org/W2079838248","https://openalex.org/W2082017338","https://openalex.org/W2098150889","https://openalex.org/W2106229734","https://openalex.org/W2114483011","https://openalex.org/W2116568543","https://openalex.org/W2121816615","https://openalex.org/W2125826911","https://openalex.org/W2126025422","https://openalex.org/W2126687488","https://openalex.org/W2128076129","https://openalex.org/W2128309854","https://openalex.org/W2135409936","https://openalex.org/W2155064397","https://openalex.org/W2166663528","https://openalex.org/W2171959453","https://openalex.org/W6643553314","https://openalex.org/W6646007771","https://openalex.org/W6680021088"],"related_works":["https://openalex.org/W2563347706","https://openalex.org/W2608033733","https://openalex.org/W4287604253","https://openalex.org/W1894261276","https://openalex.org/W2944823289","https://openalex.org/W2295662171","https://openalex.org/W2168877220","https://openalex.org/W4312620436","https://openalex.org/W3093800067","https://openalex.org/W2565481591"],"abstract_inverted_index":{"Urban":[0],"traffic":[1,48,149,163,192,234],"condition":[2,49,150,164,193,235],"usually":[3],"serves":[4],"as":[5,34],"a":[6,106,127,140,177,202],"basic":[7],"information":[8,23],"for":[9,47,194],"some":[10],"intelligent":[11,15],"urban":[12],"applications,":[13],"e.g.,":[14],"transportation":[16],"system.":[17],"But":[18],"the":[19,29,61,83,86,91,121,148,153,156,159,162,166,173,181,186,224,231],"acquisition":[20],"of":[21,53,63,85,155,161,226],"such":[22,33],"is":[24,56,134],"often":[25],"costly":[26],"due":[27],"to":[28,43,176],"dependency":[30],"on":[31,101,210],"equipments":[32],"cameras":[35],"and":[36,67,97,110,137,158,190,228],"loop":[37],"detectors.":[38],"Crowdsensing":[39],"can":[40,221],"be":[41],"utilized":[42],"gather":[44],"vehicle-sensed":[45],"data":[46,54,64,68,108,130,175,189,200],"estimation.":[50],"This":[51,143],"way":[52],"collection":[55,109],"economic.":[57],"However,":[58],"it":[59],"has":[60],"problems":[62,225],"uploading":[65],"efficiency":[66,227],"usage":[69],"effectiveness.":[70],"To":[71],"deal":[72],"with":[73],"these":[74],"problems,":[75],"in":[76,201,230],"this":[77,102],"paper,":[78],"we":[79,104],"take":[80],"into":[81,94],"account":[82],"topology":[84],"road":[87,92,167,195],"net.":[88],"We":[89,205],"divide":[90],"net":[93],"Road":[95],"Sections":[96],"Junction":[98],"Areas.":[99],"Based":[100],"division,":[103],"introduce":[105],"two-phased":[107],"processing":[111],"scheme":[112],"named":[113],"RTS":[114],"(Road":[115],"Topology":[116],"based":[117,209,233],"Scheme).":[118],"It":[119],"leverages":[120],"correlations":[122],"among":[123,184],"adjacent":[124],"roads.":[125],"In":[126],"junction":[128],"area,":[129],"collected":[131],"by":[132,139,198],"vehicles":[133],"first":[135],"processed":[136],"integrated":[138],"sponsor":[141,144,157,170],"vehicle.":[142],"vehicle":[145,212],"will":[146],"calculate":[147],"locally.":[151],"Both":[152],"selection":[154],"calculation":[160],"utilize":[165],"correlation.":[168],"The":[169,215],"then":[171],"uploads":[172],"local":[174],"server.":[178],"By":[179],"employing":[180],"inherent":[182],"relations":[183],"roads,":[185],"server":[187],"processes":[188],"estimates":[191],"sections":[196],"unreached":[197],"vehicular":[199],"global":[203],"vision.":[204],"conduct":[206],"extensive":[207],"experiments":[208],"real":[211],"trace":[213],"data.":[214],"results":[216],"indicate":[217],"that,":[218],"our":[219],"design":[220],"commendably":[222],"handle":[223],"effectiveness":[229],"vehicular-crowdsensing-data":[232],"evaluation.":[236]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
