{"id":"https://openalex.org/W4390100367","doi":"https://doi.org/10.1145/3589132.3625606","title":"A Post-routing ETA Model Providing Confidence Feedback","display_name":"A Post-routing ETA Model Providing Confidence Feedback","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4390100367","doi":"https://doi.org/10.1145/3589132.3625606"},"language":"en","primary_location":{"id":"doi:10.1145/3589132.3625606","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625606","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625606","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625606","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010058688","display_name":"Chiqun Zhang","orcid":"https://orcid.org/0000-0003-4332-6126"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chiqun Zhang","raw_affiliation_strings":["Microsoft, Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Mountain View, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065508800","display_name":"Dragomir Yankov","orcid":"https://orcid.org/0009-0006-4509-3222"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dragomir Yankov","raw_affiliation_strings":["Microsoft, Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Mountain View, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004407743","display_name":"Antonios Karatzoglou","orcid":"https://orcid.org/0000-0002-7939-1408"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Antonios Karatzoglou","raw_affiliation_strings":["Microsoft, Mountain View, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Mountain View, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101462076","display_name":"Michael R. Evans","orcid":"https://orcid.org/0000-0003-0893-3975"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Evans","raw_affiliation_strings":["Microsoft, Bellevue, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, United States","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093559169","display_name":"Florin Sabau","orcid":"https://orcid.org/0009-0006-7926-4413"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Florin Sabau","raw_affiliation_strings":["Microsoft, Bellevue, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, United States","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088713855","display_name":"Oussama Dhifallah","orcid":"https://orcid.org/0000-0002-8961-3553"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oussama Dhifallah","raw_affiliation_strings":["Microsoft, Bellevue, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft, Bellevue, United States","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5010058688"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":0.735,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78446871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991999864578247,"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/T11106","display_name":"Data Management and Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.6592457890510559},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6488540768623352},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6304712295532227},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6070636510848999},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5961138010025024},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5954174399375916},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4586098790168762},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.44671157002449036},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43204396963119507},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.4295191168785095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2671816051006317},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26670557260513306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26529228687286377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16110369563102722},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12740573287010193}],"concepts":[{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.6592457890510559},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6488540768623352},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6304712295532227},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6070636510848999},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5961138010025024},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5954174399375916},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4586098790168762},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.44671157002449036},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43204396963119507},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.4295191168785095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2671816051006317},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26670557260513306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26529228687286377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16110369563102722},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12740573287010193},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589132.3625606","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625606","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625606","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3589132.3625606","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625606","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625606","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390100367.pdf","grobid_xml":"https://content.openalex.org/works/W4390100367.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2135822894","https://openalex.org/W2139690358","https://openalex.org/W2809128166","https://openalex.org/W2988526340","https://openalex.org/W4226105509","https://openalex.org/W4255375128","https://openalex.org/W4281789464"],"related_works":["https://openalex.org/W2016188383","https://openalex.org/W2112284452","https://openalex.org/W2118155885","https://openalex.org/W2163515958","https://openalex.org/W2585070004","https://openalex.org/W2077108008","https://openalex.org/W2793335702","https://openalex.org/W1497739556","https://openalex.org/W2694164768","https://openalex.org/W4237325328"],"abstract_inverted_index":{"Map":[0],"search":[1],"engines":[2],"compute":[3],"the":[4,29,57,60,97,145,163,180,183],"estimated":[5],"time":[6],"of":[7,25,46,59,106,138,143,153,170,182],"arrival":[8],"(ETA)":[9],"from":[10],"location":[11,14],"A":[12],"to":[13,112,168],"B":[15],"by":[16],"first":[17],"performing":[18],"local":[19,50],"routing-engine":[20],"optimization":[21],"over":[22,117,154],"a":[23,73,81,102,107,121,131,136,150,155],"network":[24],"road":[26],"segments.":[27],"Once":[28],"optimal":[30],"route":[31,82,146],"candidates":[32],"are":[33,67],"identified":[34],"their":[35],"ETA":[36,42,63,75,118,147,184],"is":[37,124],"reevaluated":[38],"with":[39,120],"global":[40],"post-routing":[41,62],"(PostETA)":[43],"models":[44,53,141],"capable":[45,142],"correcting":[47],"multiple":[48],"accumulated":[49],"biases.":[51],"Sequence":[52],"have":[54,84],"emerged":[55],"as":[56,70],"state":[58],"art":[61],"predictors,":[64],"however,":[65],"they":[66],"usually":[68],"applied":[69],"regressors":[71],"fitting":[72,144],"single":[74,108],"value.":[76],"Here":[77],"we":[78,160],"demonstrate":[79,161],"that":[80,162,169],"can":[83],"very":[85],"different":[86,90],"travel":[87],"times":[88],"for":[89,179],"drivers":[91],"even":[92],"when":[93],"measured":[94],"at":[95],"approximately":[96],"same":[98],"starting":[99],"time.":[100],"Fitting":[101],"distribution":[103],"then,":[104],"instead":[105],"value,":[109],"and":[110,127],"returning":[111],"users":[113],"both":[114],"an":[115,176],"expectation":[116],"together":[119],"confidence":[122],"range":[123],"more":[125],"accurate":[126,177],"informative.":[128],"We":[129],"propose":[130],"novel":[132],"PostETA":[133],"system":[134,164],"including":[135],"set":[137,152],"sequence-to-sequence":[139],"attention":[140],"distribution.":[148],"On":[149],"data":[151],"hundred":[156],"thousand":[157],"user":[158],"trips":[159],"achieves":[165],"accuracy":[166],"comparable":[167],"regression":[171],"models,":[172],"providing":[173],"in":[174],"addition":[175],"estimate":[178],"variance":[181],"prediction.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}