{"id":"https://openalex.org/W2955043693","doi":"https://doi.org/10.3390/ijgi8070295","title":"Predicting the Upcoming Services of Vacant Taxis near Fixed Locations Using Taxi Trajectories","display_name":"Predicting the Upcoming Services of Vacant Taxis near Fixed Locations Using Taxi Trajectories","publication_year":2019,"publication_date":"2019-06-27","ids":{"openalex":"https://openalex.org/W2955043693","doi":"https://doi.org/10.3390/ijgi8070295","mag":"2955043693"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi8070295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8070295","pdf_url":"https://www.mdpi.com/2220-9964/8/7/295/pdf?version=1561627058","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/8/7/295/pdf?version=1561627058","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007683510","display_name":"Chunchun Hu","orcid":"https://orcid.org/0009-0002-3908-7548"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunchun Hu","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000206320","display_name":"Jean\u2010Claude Thill","orcid":"https://orcid.org/0000-0002-6651-8123"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jean-Claude Thill","raw_affiliation_strings":["Department of Geography &amp; Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA"],"raw_orcid":"https://orcid.org/0000-0002-6651-8123","affiliations":[{"raw_affiliation_string":"Department of Geography &amp; Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA","institution_ids":["https://openalex.org/I102149020"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007683510"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1700,"currency":"CHF","value_usd":1893},"apc_paid":{"value":1700,"currency":"CHF","value_usd":1893},"fwci":0.2999,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61029746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8","issue":"7","first_page":"295","last_page":"295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9998999834060669,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9991999864578247,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9990000128746033,"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/taxis","display_name":"Taxis","score":0.9676964282989502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7431885600090027},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.4793844223022461},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.45889735221862793},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3638879060745239},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33514320850372314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26130151748657227},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13776376843452454},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1352444589138031}],"concepts":[{"id":"https://openalex.org/C183373512","wikidata":"https://www.wikidata.org/wiki/Q949618","display_name":"Taxis","level":2,"score":0.9676964282989502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7431885600090027},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.4793844223022461},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.45889735221862793},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3638879060745239},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33514320850372314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26130151748657227},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13776376843452454},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1352444589138031},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/ijgi8070295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8070295","pdf_url":"https://www.mdpi.com/2220-9964/8/7/295/pdf?version=1561627058","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5fe125e8bad744698dea14c53b1d8634","is_oa":true,"landing_page_url":"https://doaj.org/article/5fe125e8bad744698dea14c53b1d8634","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information, Vol 8, Iss 7, p 295 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2220-9964/8/7/295/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/ijgi8070295","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/ijgi8070295","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8070295","pdf_url":"https://www.mdpi.com/2220-9964/8/7/295/pdf?version=1561627058","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2955043693.pdf","grobid_xml":"https://content.openalex.org/works/W2955043693.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W262913824","https://openalex.org/W800432607","https://openalex.org/W991541073","https://openalex.org/W1717467887","https://openalex.org/W1969454839","https://openalex.org/W1988580225","https://openalex.org/W2009076082","https://openalex.org/W2060207543","https://openalex.org/W2062363204","https://openalex.org/W2065696385","https://openalex.org/W2067261106","https://openalex.org/W2069677470","https://openalex.org/W2093776599","https://openalex.org/W2099533879","https://openalex.org/W2104841477","https://openalex.org/W2113076747","https://openalex.org/W2118154549","https://openalex.org/W2126140499","https://openalex.org/W2161581167","https://openalex.org/W2176629631","https://openalex.org/W2232898627","https://openalex.org/W2337281148","https://openalex.org/W2484357102","https://openalex.org/W2505396488","https://openalex.org/W2762724025","https://openalex.org/W2783981215","https://openalex.org/W2821470430","https://openalex.org/W6626031305","https://openalex.org/W6675644723","https://openalex.org/W6724686424"],"related_works":["https://openalex.org/W2731640799","https://openalex.org/W3145095895","https://openalex.org/W1946755446","https://openalex.org/W2978498151","https://openalex.org/W2782837293","https://openalex.org/W2388377527","https://openalex.org/W565532978","https://openalex.org/W2376563300","https://openalex.org/W2372614270","https://openalex.org/W2216673692"],"abstract_inverted_index":{"Emerging":[0],"on-line":[1],"reservation":[2],"services":[3,7,48,146],"and":[4,58,69,81,100,164,189],"special":[5],"car":[6],"have":[8],"greatly":[9],"affected":[10],"the":[11,14,40,46,75,87,117,135,139,144,153,156,177,184,193],"development":[12],"of":[13,49,77,79,103,124,138,147,170,179,187,195],"taxi":[15,20,125,180],"industry.":[16],"Surprisingly,":[17],"taking":[18],"a":[19,23,65,70,109,121,160],"is":[21,93,106],"still":[22],"significant":[24],"problem":[25],"in":[26,127,142],"many":[27],"large":[28],"cities.":[29],"In":[30,84,129],"this":[31,130,171],"paper,":[32],"we":[33],"present":[34],"an":[35],"effective":[36],"solution":[37],"based":[38],"on":[39,120],"Hidden":[41],"Markov":[42],"Model":[43],"to":[44,182,191],"predict":[45],"upcoming":[47,145],"vacant":[50,148],"taxis":[51,188],"that":[52],"appear":[53],"at":[54,59],"some":[55],"fixed":[56],"locations":[57],"specific":[60],"times.":[61],"The":[62,168],"model":[63,119],"introduces":[64],"weighted":[66],"confusion":[67],"matrix":[68],"modified":[71],"Viterbi":[72],"algorithm,":[73],"combining":[74],"factors":[76,154],"time":[78],"day":[80],"traffic":[82,104],"conditions.":[83],"our":[85],"framework,":[86],"hotspot":[88],"or":[89],"hidden":[90],"states":[91],"extraction":[92],"implemented":[94],"through":[95],"kernel":[96],"density":[97],"estimation":[98],"(KDE)":[99],"fuzzy":[101],"partitioning":[102],"zones":[105],"done":[107],"via":[108,159],"Fuzzy":[110],"C":[111],"Means":[112],"(FCM)":[113],"algorithm.":[114],"We":[115,150],"implement":[116],"proposed":[118],"large-scale":[122],"dataset":[123],"trajectories":[126],"Beijing.":[128],"use":[131],"case,":[132],"tests":[133],"demonstrate":[134],"high":[136],"accuracy":[137,158,162],"modeling":[140],"framework":[141],"predicting":[143],"taxis.":[149,198],"further":[151],"analyze":[152],"affecting":[155],"predictive":[157],"prediction":[161,165],"analysis":[163],"location":[166],"evaluation.":[167],"findings":[169],"paper":[172],"can":[173],"provide":[174],"intelligence":[175],"for":[176],"improvement":[178],"services,":[181],"increase":[183],"passenger":[185],"capacity":[186],"also":[190],"improve":[192],"probability":[194],"passengers":[196],"finding":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
