{"id":"https://openalex.org/W2517945972","doi":"https://doi.org/10.1109/tits.2016.2584388","title":"Modal Activity-Based Stochastic Model for Estimating Vehicle Trajectories from Sparse Mobile Sensor Data","display_name":"Modal Activity-Based Stochastic Model for Estimating Vehicle Trajectories from Sparse Mobile Sensor Data","publication_year":2016,"publication_date":"2016-08-15","ids":{"openalex":"https://openalex.org/W2517945972","doi":"https://doi.org/10.1109/tits.2016.2584388","mag":"2517945972"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2016.2584388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2016.2584388","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/A5088116668","display_name":"Peng Hao","orcid":"https://orcid.org/0000-0001-5864-7358"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Hao","raw_affiliation_strings":["Center for Environmental Research and Technology, University of California, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Environmental Research and Technology, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026317556","display_name":"Kanok Boriboonsomsin","orcid":"https://orcid.org/0000-0003-2558-5343"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kanok Boriboonsomsin","raw_affiliation_strings":["Center for Environmental Research and Technology, University of California, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Environmental Research and Technology, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006183071","display_name":"Guoyuan Wu","orcid":"https://orcid.org/0000-0001-6707-6366"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoyuan Wu","raw_affiliation_strings":["Center for Environmental Research and Technology, University of California, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Environmental Research and Technology, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077257353","display_name":"Matthew Barth","orcid":"https://orcid.org/0000-0002-4735-5859"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew J. Barth","raw_affiliation_strings":["Center for Environmental Research and Technology, University of California, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Environmental Research and Technology, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":4.2192,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.93174552,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"18","issue":"3","first_page":"701","last_page":"711"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10524","display_name":"Traffic control and management","score":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5617891550064087},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.524939775466919},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.517551839351654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5047470331192017},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4693789482116699},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44928574562072754},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.4491257667541504},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.43352869153022766},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.43018078804016113},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.41330209374427795},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3507440686225891},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.325336754322052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20768499374389648},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20095983147621155},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.10565510392189026},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09805876016616821}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5617891550064087},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.524939775466919},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.517551839351654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5047470331192017},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4693789482116699},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44928574562072754},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.4491257667541504},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.43352869153022766},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.43018078804016113},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.41330209374427795},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3507440686225891},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.325336754322052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20768499374389648},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20095983147621155},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.10565510392189026},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09805876016616821},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2016.2584388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2016.2584388","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W61548216","https://openalex.org/W1958866086","https://openalex.org/W1963875011","https://openalex.org/W1968198841","https://openalex.org/W1968765912","https://openalex.org/W1970574049","https://openalex.org/W1980258017","https://openalex.org/W1992477951","https://openalex.org/W1994413287","https://openalex.org/W2000854095","https://openalex.org/W2020893175","https://openalex.org/W2031346385","https://openalex.org/W2063890507","https://openalex.org/W2065964232","https://openalex.org/W2082492304","https://openalex.org/W2097833556","https://openalex.org/W2115868680","https://openalex.org/W2122169437","https://openalex.org/W2130482380","https://openalex.org/W2136383351","https://openalex.org/W2142382652","https://openalex.org/W2145401763","https://openalex.org/W2152857550","https://openalex.org/W2189139187","https://openalex.org/W2796377487","https://openalex.org/W2962917186","https://openalex.org/W3049751339","https://openalex.org/W3110683067","https://openalex.org/W6602509845","https://openalex.org/W6687341440","https://openalex.org/W6782184084","https://openalex.org/W6786768871"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W2349383066","https://openalex.org/W1969901537","https://openalex.org/W4328132048","https://openalex.org/W4308259661","https://openalex.org/W1639545646","https://openalex.org/W2376202349"],"abstract_inverted_index":{"Probe":[0],"vehicles":[1],"that":[2],"measure":[3],"position":[4,106],"and":[5,17,42,62,98,107,167],"speed":[6,84,108,147],"have":[7],"emerged":[8],"as":[9,134],"a":[10,74,123,144,189,202],"promising":[11],"tool":[12],"for":[13,139],"traffic":[14,213],"data":[15,29,44,102],"collection":[16],"performance":[18],"measurement,":[19],"but":[20],"the":[21,43,55,81,135,153,160,170,177,181,209],"sampling":[22],"rates":[23],"of":[24,91,112,114,137,183,211],"most":[25],"probe":[26],"vehicle":[27,56,83,127,146,185,204],"sensor":[28,69],"available":[30],"today":[31],"are":[32],"low":[33],"(ranging":[34],"from":[35,104],"10":[36],"to":[37,52,79,201,207],"60":[38],"s":[39],"per":[40],"sample),":[41],"coverage":[45],"is":[46,50,77,118,131,165,199],"limited.":[47],"Therefore,":[48,143],"it":[49],"challenging":[51],"accurately":[53],"estimate":[54,80],"dynamic":[57,128],"states":[58],"in":[59],"both":[60],"space":[61],"time":[63],"based":[64,192],"on":[65,180,193],"these":[66],"sparse":[67,105],"mobile":[68],"data.":[70],"In":[71],"this":[72],"paper,":[73],"stochastic":[75],"model":[76,164,198],"proposed":[78,163,197],"second-by-second":[82],"trajectories":[85,186],"by":[86,121],"examining":[87],"all":[88],"possible":[89],"sequences":[90],"modal":[92,155],"activities":[93],"(i.e.,":[94],"acceleration,":[95],"deceleration,":[96],"cruising,":[97],"idling)":[99],"between":[100],"consecutive":[101],"points":[103],"measurements.":[109],"The":[110,126,162,174,196],"likelihood":[111],"occurrence":[113],"each":[115],"sequential":[116],"pattern":[117],"first":[119],"quantified":[120],"mode-specific":[122],"priori":[124],"distributions.":[125],"state":[129],"probability":[130],"then":[132],"formulated":[133],"product":[136],"probabilities":[138],"multiple":[140],"independent":[141],"events.":[142],"detailed":[145],"trajectory":[148],"can":[149],"be":[150],"reconstructed":[151],"using":[152,169],"optimal":[154],"activity":[156,205],"sequence,":[157],"which":[158],"maximizes":[159],"likelihood.":[161],"calibrated":[166],"validated":[168],"Next-Generation":[171],"SIMulation":[172],"dataset.":[173],"results":[175],"show":[176],"substantial":[178],"improvements":[179],"accuracy":[182],"estimated":[184],"compared":[187],"with":[188],"baseline":[190],"method":[191],"linear":[194],"interpolation.":[195],"applied":[200],"large-scale":[203],"dataset":[206],"demonstrate":[208],"estimation":[210],"hourly":[212],"delay":[214],"variation.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
