{"id":"https://openalex.org/W4393948435","doi":"https://doi.org/10.1137/23m155699x","title":"Efficiency of ETA Prediction","display_name":"Efficiency of ETA Prediction","publication_year":2024,"publication_date":"2024-04-04","ids":{"openalex":"https://openalex.org/W4393948435","doi":"https://doi.org/10.1137/23m155699x"},"language":"eu","primary_location":{"id":"doi:10.1137/23m155699x","is_oa":true,"landing_page_url":"https://doi.org/10.1137/23m155699x","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1137/23m155699x","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009243454","display_name":"Chiwei Yan","orcid":"https://orcid.org/0000-0001-5770-2079"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chiwei Yan","raw_affiliation_strings":["Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720 USA"],"raw_orcid":"https://orcid.org/0000-0001-5770-2079","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720 USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029579758","display_name":"James E. Johndrow","orcid":"https://orcid.org/0000-0001-7919-364X"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Johndrow","raw_affiliation_strings":["Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-1686 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-1686 USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055858606","display_name":"Dawn B. Woodard","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawn Woodard","raw_affiliation_strings":["LinkedIn Corporation, Sunnyvale, CA 94085 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LinkedIn Corporation, Sunnyvale, CA 94085 USA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100597649","display_name":"Yanwei Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yanwei Sun","raw_affiliation_strings":["Department of Analytics & Operations, Imperial College Business School, London, SW7 2AZ, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Analytics & Operations, Imperial College Business School, London, SW7 2AZ, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009243454"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.6728,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68248793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"6","issue":"2","first_page":"227","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13553","display_name":"Age of Information Optimization","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9641000032424927,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9409000277519226,"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/computer-science","display_name":"Computer science","score":0.3119150400161743}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3119150400161743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/23m155699x","is_oa":true,"landing_page_url":"https://doi.org/10.1137/23m155699x","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1137/23m155699x","is_oa":true,"landing_page_url":"https://doi.org/10.1137/23m155699x","pdf_url":null,"source":{"id":"https://openalex.org/S4210229561","display_name":"SIAM Journal on Mathematics of Data Science","issn_l":"2577-0187","issn":["2577-0187"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Mathematics of Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1507943102","https://openalex.org/W1587094587","https://openalex.org/W1779869868","https://openalex.org/W1988520084","https://openalex.org/W2073209910","https://openalex.org/W2088061407","https://openalex.org/W2115868680","https://openalex.org/W2145638978","https://openalex.org/W2183104740","https://openalex.org/W2909452395","https://openalex.org/W2962917186","https://openalex.org/W3042411963","https://openalex.org/W4248681815"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{".Modern":[0],"mobile":[1],"applications":[2],"such":[3,94],"as":[4,95],"navigation":[5],"services":[6],"and":[7,79,97,122,147],"ride-sharing":[8],"platforms":[9],"rely":[10],"heavily":[11],"on":[12],"geospatial":[13],"technologies,":[14],"most":[15],"critically":[16],"predictions":[17],"of":[18,35,49,68,74,106,138,142,160,169,179],"the":[19,31,50,55,66,83,92,134,139,167,177,180,185],"time":[20,34,64,157],"required":[21],"for":[22],"a":[23,27,72,151],"vehicle":[24],"to":[25,99],"traverse":[26],"particular":[28],"route,":[29,84],"or":[30],"so-called":[32],"estimated":[33],"arrival":[36],"(ETA).":[37],"There":[38],"are":[39,192],"various":[40,104,143],"methods":[41,61,87,108,146,191],"used":[42],"in":[43,47,126,154],"practice,":[44],"which":[45,54,189],"differ":[46],"terms":[48],"geographic":[51],"granularity":[52,187],"at":[53,65,188],"predictive":[56,140],"model":[57,181],"is":[58,158,172],"trained\u2014e.g.,":[59],"segment-based":[60],"predict":[62,100],"travel":[63,101,156],"level":[67],"road":[69,77],"segments":[70],"(or":[71],"combination":[73],"several":[75],"adjacent":[76],"segments)":[78],"then":[80],"aggregate":[81],"across":[82],"whereas":[85],"route-based":[86],"use":[88],"generic":[89],"information":[90],"about":[91],"trip,":[93],"origin":[96],"destination,":[98],"time.":[102],"Though":[103],"forms":[105],"these":[107],"have":[109],"been":[110,114],"developed,":[111],"there":[112],"has":[113],"no":[115],"rigorous":[116],"theoretical":[117,136],"comparison":[118],"regarding":[119],"their":[120],"accuracies,":[121],"empirical":[123],"studies":[124],"have,":[125],"many":[127],"cases,":[128],"drawn":[129],"opposite":[130],"conclusions.":[131],"We":[132],"provide":[133],"first":[135],"analysis":[137],"accuracy":[141,168],"ETA":[144,170],"prediction":[145,171],"argue":[148],"that":[149,166],"maintaining":[150],"segment-level":[152],"architecture":[153],"predicting":[155],"often":[159],"first-order":[161],"importance.":[162],"Our":[163],"work":[164],"highlights":[165],"driven":[173],"not":[174],"just":[175],"by":[176,184],"sophistication":[178],"but":[182],"also":[183],"spatial":[186],"those":[190],"applied.KeywordsETA":[193],"predictionstatistical":[194],"efficiencypoint":[195],"estimationMSC":[196],"codes62P30":[197]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}