{"id":"https://openalex.org/W4396506123","doi":"https://doi.org/10.1109/tits.2024.3390792","title":"Improving Urban Travel Time Estimation Using Gaussian Mixture Models","display_name":"Improving Urban Travel Time Estimation Using Gaussian Mixture Models","publication_year":2024,"publication_date":"2024-04-30","ids":{"openalex":"https://openalex.org/W4396506123","doi":"https://doi.org/10.1109/tits.2024.3390792"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3390792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3390792","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/A5022911422","display_name":"Andrea Gemma","orcid":"https://orcid.org/0000-0002-6177-382X"},"institutions":[{"id":"https://openalex.org/I119003972","display_name":"Roma Tre University","ror":"https://ror.org/05vf0dg29","country_code":"IT","type":"education","lineage":["https://openalex.org/I119003972"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Andrea Gemma","raw_affiliation_strings":["Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6177-382X","affiliations":[{"raw_affiliation_string":"Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy","institution_ids":["https://openalex.org/I119003972"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002518807","display_name":"Livia Mannini","orcid":"https://orcid.org/0000-0002-5021-7094"},"institutions":[{"id":"https://openalex.org/I119003972","display_name":"Roma Tre University","ror":"https://ror.org/05vf0dg29","country_code":"IT","type":"education","lineage":["https://openalex.org/I119003972"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Livia Mannini","raw_affiliation_strings":["Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-5021-7094","affiliations":[{"raw_affiliation_string":"Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy","institution_ids":["https://openalex.org/I119003972"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002864424","display_name":"Umberto Crisalli","orcid":"https://orcid.org/0000-0002-2672-8054"},"institutions":[{"id":"https://openalex.org/I116067653","display_name":"University of Rome Tor Vergata","ror":"https://ror.org/02p77k626","country_code":"IT","type":"education","lineage":["https://openalex.org/I116067653"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Umberto Crisalli","raw_affiliation_strings":["Department of Enterprise Engineering, Tor Vergata University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-2672-8054","affiliations":[{"raw_affiliation_string":"Department of Enterprise Engineering, Tor Vergata University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I116067653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007521351","display_name":"Ernesto Cipriani","orcid":null},"institutions":[{"id":"https://openalex.org/I119003972","display_name":"Roma Tre University","ror":"https://ror.org/05vf0dg29","country_code":"IT","type":"education","lineage":["https://openalex.org/I119003972"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Ernesto Cipriani","raw_affiliation_strings":["Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-5073-9378","affiliations":[{"raw_affiliation_string":"Department of Civil, Computer Science and Aeronautical Technologies Engineering, University of Roma Tre, Rome, Italy","institution_ids":["https://openalex.org/I119003972"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022911422"],"corresponding_institution_ids":["https://openalex.org/I119003972"],"apc_list":null,"apc_paid":null,"fwci":1.7761,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82686137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"25","issue":"10","first_page":"14154","last_page":"14163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9966999888420105,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9965000152587891,"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/mixture-model","display_name":"Mixture model","score":0.6130614876747131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5901655554771423},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5505644083023071},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5052102208137512},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5043014287948608},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.47821304202079773},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4690720736980438},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4298490881919861},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42752042412757874},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4125468134880066},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37341850996017456},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3694228231906891},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2066769301891327},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20298528671264648},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1872146725654602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17541468143463135},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13502845168113708}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6130614876747131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5901655554771423},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5505644083023071},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5052102208137512},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5043014287948608},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.47821304202079773},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4690720736980438},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4298490881919861},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42752042412757874},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4125468134880066},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37341850996017456},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3694228231906891},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2066769301891327},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20298528671264648},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1872146725654602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17541468143463135},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13502845168113708},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2024.3390792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3390792","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"},{"id":"pmh:oai:art.torvergata.it:2108/454509","is_oa":false,"landing_page_url":"https://hdl.handle.net/2108/454509","pdf_url":null,"source":{"id":"https://openalex.org/S4306400993","display_name":"Cineca Institutional Research Information System (Tor Vergata University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I116067653","host_organization_name":"University of Rome Tor Vergata","host_organization_lineage":["https://openalex.org/I116067653"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6499999761581421,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1561128958","https://openalex.org/W1602211094","https://openalex.org/W1852328876","https://openalex.org/W1970574049","https://openalex.org/W1975086685","https://openalex.org/W1976333578","https://openalex.org/W1976495514","https://openalex.org/W1989491491","https://openalex.org/W2001355817","https://openalex.org/W2011504567","https://openalex.org/W2027665506","https://openalex.org/W2056145546","https://openalex.org/W2074108366","https://openalex.org/W2076246037","https://openalex.org/W2089079865","https://openalex.org/W2100366979","https://openalex.org/W2127012233","https://openalex.org/W2133177820","https://openalex.org/W2157409281","https://openalex.org/W2165327689","https://openalex.org/W2169560049","https://openalex.org/W2217607432","https://openalex.org/W2239838331","https://openalex.org/W2302719757","https://openalex.org/W2319145018","https://openalex.org/W2346039921","https://openalex.org/W2543610789","https://openalex.org/W2556487516","https://openalex.org/W2593149854","https://openalex.org/W2736186863","https://openalex.org/W2779684064","https://openalex.org/W2781864963","https://openalex.org/W2807691880","https://openalex.org/W2883345462","https://openalex.org/W2884860764","https://openalex.org/W2905108066","https://openalex.org/W3012477623","https://openalex.org/W3102428570","https://openalex.org/W3129093284","https://openalex.org/W3187749162","https://openalex.org/W3197872836","https://openalex.org/W3198046024","https://openalex.org/W4205453809","https://openalex.org/W4244532478","https://openalex.org/W4283580362","https://openalex.org/W4283733329","https://openalex.org/W4376616386","https://openalex.org/W4386498049","https://openalex.org/W4386933541","https://openalex.org/W6618457977","https://openalex.org/W6683788084","https://openalex.org/W6687168902","https://openalex.org/W6693705418","https://openalex.org/W6704922485","https://openalex.org/W6750374569"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W3130349901","https://openalex.org/W1579833936"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"a":[3,72,96,107,120,159],"methodology":[4,91],"to":[5,52,71,101,203,214],"improve":[6],"the":[7,10,77,102,125,195,204],"accuracy":[8],"of":[9,12,39,76,106,122,179,194,198],"estimation":[11],"path":[13],"travel":[14,32,226],"times":[15],"in":[16,27,95,109,119,135],"urban":[17],"areas":[18],"is":[19],"proposed,":[20],"as":[21,149],"they":[22],"play":[23],"an":[24],"important":[25],"role":[26],"advanced":[28],"management":[29],"applications.":[30],"Heterogeneous":[31],"time":[33,138,155,227],"measurements":[34,201],"provided":[35],"by":[36,84,116,158],"different":[37,171,177,210],"types":[38],"monitoring":[40],"technologies":[41,180],"(e.g.":[42],"Floating":[43],"Car":[44],"and":[45,55,67,187,190],"Bluetooth":[46],"Antennas)":[47],"have":[48,140,173,218],"been":[49,81,93,141,147,174,219],"first":[50],"used":[51],"derive":[53],"current":[54,200],"historical":[56,205],"information":[57,145],"on":[58,62,164],"traffic":[59,113,131,196],"states":[60],"based":[61,163],"Gaussian":[63],"Mixture":[64],"Model":[65],"(GMM)":[66],"then":[68,82],"fused":[69],"according":[70,202],"Bayesian":[73],"approach.":[74],"Accuracy":[75],"resulting":[78],"estimate":[79],"has":[80,92,146,207],"evaluated":[83],"comparison":[85],"with":[86,225],"ground":[87],"truth.":[88],"The":[89,143],"proposed":[90],"implemented":[94],"full":[97],"laboratory":[98],"test":[99],"relative":[100],"real":[103],"size":[104],"network":[105],"district":[108],"Rome:":[110],"starting":[111],"from":[112,170],"counts":[114],"collected":[115],"fixed":[117],"detectors":[118],"period":[121],"40":[123],"days,":[124],"960":[126],"hourly":[127],"Origin":[128],"\u2013":[129],"Destination":[130],"demand":[132],"matrices,":[133],"split":[134],"20":[136],"minutes":[137],"slices,":[139],"estimated.":[142],"ground-truth":[144],"assumed":[148],"vehicles":[150],"trajectories":[151],"for":[152],"any":[153],"considered":[154],"slice":[156],"obtained":[157],"Dynameq":[160],"microscopic":[161],"simulation":[162],"within-day":[165],"user":[166],"equilibrium":[167],"principles.":[168],"Measurements":[169],"sensors":[172],"simulated":[175,199],"adopting":[176],"values":[178],"penetration":[181],"rates,":[182],"errors":[183],"bias":[184],"(mean":[185],"value)":[186],"dispersion":[188],"(variance":[189],"distribution).":[191],"Then,":[192],"identification":[193],"state":[197],"GMM":[206],"allowed":[208],"fusing":[209],"heterogeneous":[211],"data.":[212],"According":[213],"promising":[215],"results":[216],"that":[217],"obtained,":[220],"future":[221],"research":[222],"will":[223],"deal":[224],"forecasts.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}