{"id":"https://openalex.org/W2205029267","doi":"https://doi.org/10.1109/bigdata.2015.7363837","title":"A scalable approach for data-driven taxi ride-sharing simulation","display_name":"A scalable approach for data-driven taxi ride-sharing simulation","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2205029267","doi":"https://doi.org/10.1109/bigdata.2015.7363837","mag":"2205029267"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2015.7363837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7363837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","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/A5039398331","display_name":"Masayo Ota","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Masayo Ota","raw_affiliation_strings":["Department of Computer Science and Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064720873","display_name":"Huy T. Vo","orcid":"https://orcid.org/0000-0002-5963-6615"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]},{"id":"https://openalex.org/I174216632","display_name":"City University of New York","ror":"https://ror.org/00453a208","country_code":"US","type":"education","lineage":["https://openalex.org/I174216632"]},{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huy Vo","raw_affiliation_strings":["Department of Computer Science and Engineering, New York University","Department of Computer Science, The City College of the City University of New York"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Department of Computer Science, The City College of the City University of New York","institution_ids":["https://openalex.org/I174216632","https://openalex.org/I125687163"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101757990","display_name":"Claudio Silva","orcid":"https://orcid.org/0000-0003-4331-3755"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Claudio Silva","raw_affiliation_strings":["Department of Computer Science and Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006773757","display_name":"Juliana Freire","orcid":"https://orcid.org/0000-0003-3915-7075"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juliana Freire","raw_affiliation_strings":["Department of Computer Science and Engineering, New York University"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039398331"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":6.5935,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.96621891,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"888","last_page":"897"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":1.0,"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":1.0,"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/T12546","display_name":"Smart Parking Systems Research","score":0.9975000023841858,"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/taxis","display_name":"Taxis","score":0.8458160161972046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7692712545394897},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6859759092330933},{"id":"https://openalex.org/keywords/trips-architecture","display_name":"TRIPS architecture","score":0.6809453368186951},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4651082158088684},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.45952779054641724},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4386503994464874},{"id":"https://openalex.org/keywords/urban-computing","display_name":"Urban computing","score":0.42075207829475403},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.4107482135295868},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3891676664352417},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.3471570611000061},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2520771920681},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17522099614143372},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13928186893463135},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12647968530654907}],"concepts":[{"id":"https://openalex.org/C183373512","wikidata":"https://www.wikidata.org/wiki/Q949618","display_name":"Taxis","level":2,"score":0.8458160161972046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7692712545394897},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6859759092330933},{"id":"https://openalex.org/C157085824","wikidata":"https://www.wikidata.org/wiki/Q2384809","display_name":"TRIPS architecture","level":2,"score":0.6809453368186951},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4651082158088684},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.45952779054641724},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4386503994464874},{"id":"https://openalex.org/C2778459138","wikidata":"https://www.wikidata.org/wiki/Q7900107","display_name":"Urban computing","level":2,"score":0.42075207829475403},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.4107482135295868},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3891676664352417},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3471570611000061},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2520771920681},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17522099614143372},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13928186893463135},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12647968530654907},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2015.7363837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7363837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310874","display_name":"Center for Urban Science and Progress","ror":"https://ror.org/0190ak572"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W560531075","https://openalex.org/W1492747100","https://openalex.org/W1492821746","https://openalex.org/W1539300019","https://openalex.org/W1554727768","https://openalex.org/W1923372423","https://openalex.org/W1963504979","https://openalex.org/W1976993400","https://openalex.org/W2031318626","https://openalex.org/W2044891321","https://openalex.org/W2077715727","https://openalex.org/W2093189937","https://openalex.org/W2098978591","https://openalex.org/W2137045485","https://openalex.org/W2156767060","https://openalex.org/W2164674071","https://openalex.org/W2295595685","https://openalex.org/W2331651998","https://openalex.org/W2971301549","https://openalex.org/W3123416802","https://openalex.org/W4239562980","https://openalex.org/W4252071611","https://openalex.org/W4285719527","https://openalex.org/W6629483879","https://openalex.org/W6632512199","https://openalex.org/W6644702372","https://openalex.org/W6697368715","https://openalex.org/W6821309870"],"related_works":["https://openalex.org/W2731640799","https://openalex.org/W3145095895","https://openalex.org/W2594548639","https://openalex.org/W4387544810","https://openalex.org/W2978498151","https://openalex.org/W4327733581","https://openalex.org/W3090765184","https://openalex.org/W2989156809","https://openalex.org/W3207093644","https://openalex.org/W2973580673"],"abstract_inverted_index":{"As":[0],"urban":[1],"population":[2],"grows,":[3],"cities":[4],"face":[5],"many":[6],"challenges":[7],"related":[8],"to":[9,25,43,63,101,123],"transportation,":[10],"resource":[11],"consumption,":[12,30],"and":[13,31,37,46,92,136,160,180,199,209],"the":[14,64,82,110,125,140,144,156,222,225,234],"environment.":[15],"Ride":[16],"sharing":[17],"has":[18],"been":[19],"proposed":[20],"as":[21,94,227,229],"an":[22,164],"effective":[23,208],"approach":[24,174],"reduce":[26],"traffic":[27],"congestion,":[28],"gasoline":[29],"pollution.":[32],"Despite":[33],"great":[34],"promise,":[35],"researchers":[36],"policy":[38],"makers":[39],"lack":[40],"adequate":[41],"tools":[42],"assess":[44],"tradeoffs":[45],"benefits":[47],"of":[48,66,85,106,118,143,158,163,224,233],"various":[49],"ride-sharing":[50,127,218],"strategies.":[51],"Existing":[52],"approaches":[53],"either":[54],"make":[55],"unrealistic":[56],"modeling":[57,90],"assumptions":[58],"or":[59],"do":[60],"not":[61],"scale":[62],"sizes":[65],"existing":[67],"data":[68,184],"sets.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73,120,146],"propose":[74],"a":[75,103,115,148,230],"real-time,":[76],"data-driven":[77],"simulation":[78],"framework":[79,98,179,206],"that":[80,152,204],"supports":[81],"efficient":[83,165],"analysis":[84,232],"taxi":[86,126],"ride":[87],"sharing.":[88],"By":[89],"taxis":[91,192],"trips":[93,159,188],"distinct":[95],"entities,":[96],"our":[97,173,178,205],"is":[99,153,207],"able":[100,122],"simulate":[102],"rich":[104],"set":[105,117],"realistic":[107],"scenarios.":[108],"At":[109],"same":[111],"time,":[112],"by":[113,190],"providing":[114],"comprehensive":[116],"parameters,":[119],"are":[121],"study":[124,226],"problem":[128],"from":[129],"different":[130,133],"angles,":[131],"considering":[132],"stakeholders'":[134],"interests":[135],"constraints.":[137],"To":[138],"address":[139],"computational":[141],"complexity":[142],"model,":[145],"describe":[147,221],"new":[149],"optimization":[150],"algorithm":[151,181],"linear":[154],"in":[155,193],"number":[157],"makes":[161,172],"use":[162],"indexing":[166],"scheme,":[167],"which":[168],"combined":[169],"with":[170],"parallelization,":[171],"scalable.":[175],"We":[176,220],"evaluate":[177],"using":[182],"real":[183],"-":[185],"360":[186],"million":[187],"taken":[189],"13,000":[191],"New":[194],"York":[195],"City":[196],"during":[197],"2011":[198],"2012.":[200],"The":[201],"results":[202],"demonstrate":[203],"can":[210],"provide":[211],"insights":[212],"into":[213],"strategies":[214],"for":[215],"implementing":[216],"city-wide":[217],"solutions.":[219],"findings":[223],"well":[228],"performance":[231],"model.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}