{"id":"https://openalex.org/W7128023367","doi":"https://doi.org/10.48550/arxiv.2602.05053","title":"Quantile-Physics Hybrid Framework for Safe-Speed Recommendation under Diverse Weather Conditions Leveraging Connected Vehicle and Road Weather Information Systems Data","display_name":"Quantile-Physics Hybrid Framework for Safe-Speed Recommendation under Diverse Weather Conditions Leveraging Connected Vehicle and Road Weather Information Systems Data","publication_year":2026,"publication_date":"2026-02-04","ids":{"openalex":"https://openalex.org/W7128023367","doi":"https://doi.org/10.48550/arxiv.2602.05053"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.05053","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125190222","display_name":"Wen Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035431016","display_name":"Adel W. Sadek","orcid":"https://orcid.org/0000-0002-9976-0047"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadek, Adel W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125108951","display_name":"Chunming Qiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Chunming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10700734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.4977000057697296,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.4977000057697296,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.19179999828338623,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.07900000363588333,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.7202000021934509},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5929999947547913},{"id":"https://openalex.org/keywords/speed-limit","display_name":"Speed limit","score":0.4959000051021576},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.46540001034736633},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4413999915122986},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.39089998602867126},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.3781000077724457},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.37560001015663147},{"id":"https://openalex.org/keywords/road-surface","display_name":"Road surface","score":0.3637000024318695}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.7202000021934509},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5929999947547913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5802000164985657},{"id":"https://openalex.org/C2780210587","wikidata":"https://www.wikidata.org/wiki/Q1077350","display_name":"Speed limit","level":2,"score":0.4959000051021576},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.39089998602867126},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C2780042925","wikidata":"https://www.wikidata.org/wiki/Q1049667","display_name":"Road surface","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C2779628075","wikidata":"https://www.wikidata.org/wiki/Q1253258","display_name":"Downgrade","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.3353999853134155},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C103402496","wikidata":"https://www.wikidata.org/wiki/Q1106171","display_name":"Prediction interval","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3091999888420105},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3086000084877014},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C205537798","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Extreme weather","level":3,"score":0.2750000059604645},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C188048851","wikidata":"https://www.wikidata.org/wiki/Q2298569","display_name":"Road map","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C202176563","wikidata":"https://www.wikidata.org/wiki/Q2527484","display_name":"Automatic vehicle location","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C2777129202","wikidata":"https://www.wikidata.org/wiki/Q190107","display_name":"Weather station","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.05053","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.05053","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05053","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.05053","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.5138810873031616,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Inclement":[0],"weather":[1,39,186,195],"conditions":[2,196],"can":[3,127],"significantly":[4],"impact":[5],"driver":[6],"visibility":[7],"and":[8,47,100,122,146,182,197,211],"tire-road":[9],"surface":[10],"friction,":[11],"requiring":[12],"adjusted":[13],"safe":[14,31],"driving":[15],"speeds":[16],"to":[17,60,84,191,193],"reduce":[18],"crash":[19],"risk.":[20],"This":[21],"study":[22],"proposes":[23],"a":[24,64,107,161,177],"hybrid":[25],"predictive":[26,155],"framework":[27],"that":[28,96,125],"recommends":[29],"real-time":[30,119],"speed":[32,87,110,144,172],"intervals":[33],"for":[34,114,204],"freeway":[35],"travel":[36],"under":[37],"diverse":[38],"conditions.":[40,102],"Leveraging":[41],"high-resolution":[42],"Connected":[43],"Vehicle":[44],"(CV)":[45],"data":[46,53],"Road":[48],"Weather":[49],"Information":[50],"System":[51],"(RWIS)":[52],"collected":[54],"in":[55,89],"Buffalo,":[56],"NY,":[57],"from":[58],"2022":[59],"2023,":[61],"we":[62],"construct":[63],"spatiotemporally":[65],"aligned":[66],"dataset":[67],"containing":[68],"over":[69],"6.6":[70],"million":[71],"records":[72],"across":[73,185,199],"73":[74],"days.":[75],"The":[76,134,188],"core":[77],"model":[78,159],"employs":[79],"Quantile":[80],"Regression":[81],"Forests":[82],"(QRF)":[83],"estimate":[85],"vehicle":[86],"distributions":[88],"10-minute":[90],"windows,":[91],"using":[92],"26":[93],"input":[94],"features":[95],"capture":[97],"meteorological,":[98],"pavement,":[99],"temporal":[101],"To":[103],"enforce":[104],"safety":[105,210],"constraints,":[106],"physics-based":[108],"upper":[109,149],"limit":[111],"is":[112],"computed":[113],"each":[115],"interval":[116,137],"based":[117],"on":[118],"road":[120,200],"grip":[121],"visibility,":[123],"ensuring":[124],"vehicles":[126],"safely":[128],"stop":[129],"within":[130,174],"their":[131],"sight":[132],"distance.":[133],"final":[135],"recommended":[136],"fuses":[138],"QRF-predicted":[139],"quantiles":[140],"with":[141,168],"both":[142],"posted":[143],"limits":[145],"the":[147,157],"physics-derived":[148],"bound.":[150],"Experimental":[151],"results":[152],"demonstrate":[153],"strong":[154],"performance:":[156],"QRF":[158],"achieves":[160],"mean":[162],"absolute":[163],"error":[164],"of":[165,170,180],"1.55":[166],"mph,":[167,176],"96.43%":[169],"median":[171],"predictions":[173],"5":[175],"PICP":[178],"(50%)":[179],"48.55%,":[181],"robust":[183],"generalization":[184],"types.":[187],"model's":[189],"ability":[190],"respond":[192],"changing":[194],"generalize":[198],"segments":[201],"shows":[202],"promise":[203],"real-world":[205],"deployment,":[206],"thereby":[207],"improving":[208],"traffic":[209],"reducing":[212],"weather-related":[213],"crashes.":[214]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-07T00:00:00"}