{"id":"https://openalex.org/W4417035282","doi":"https://doi.org/10.48550/arxiv.2512.04004","title":"Physics-Embedded Gaussian Process for Traffic State Estimation","display_name":"Physics-Embedded Gaussian Process for Traffic State Estimation","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4417035282","doi":"https://doi.org/10.48550/arxiv.2512.04004"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.04004","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.04004","pdf_url":"https://arxiv.org/pdf/2512.04004","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.04004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101631971","display_name":"Yanlin Chen","orcid":"https://orcid.org/0000-0003-1016-3535"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yanlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chen, Kehua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kehua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012268687","display_name":"Yinhai Wang","orcid":"https://orcid.org/0000-0002-4180-5628"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yinhai","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":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5586000084877014,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5586000084877014,"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/T10524","display_name":"Traffic control and management","score":0.16179999709129333,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.054099999368190765,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/gaussian-process","display_name":"Gaussian process","score":0.6607999801635742},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5425999760627747},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5182999968528748},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5105999708175659},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.46239998936653137},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.421999990940094},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.38429999351501465}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6607999801635742},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5182999968528748},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5105999708175659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49779999256134033},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45179998874664307},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4065999984741211},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.365200012922287},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.31470000743865967},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29760000109672546},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.04004","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.04004","pdf_url":"https://arxiv.org/pdf/2512.04004","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.04004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.04004","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:oai:arXiv.org:2512.04004","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.04004","pdf_url":"https://arxiv.org/pdf/2512.04004","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417035282.pdf","grobid_xml":"https://content.openalex.org/works/W4417035282.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"state":[1,130],"estimation":[2],"(TSE)":[3],"becomes":[4],"challenging":[5],"when":[6,26],"probe-vehicle":[7],"penetration":[8],"is":[9,29],"low":[10],"and":[11,22,39,93,190,201],"observations":[12],"are":[13,198],"spatially":[14],"sparse.":[15,30],"Pure":[16],"data-driven":[17,126],"methods":[18,87,127],"lack":[19,94],"physical":[20,33,58,211],"explanations":[21],"have":[23,35,52],"poor":[24],"generalization":[25],"observed":[27],"data":[28],"In":[31,105],"contrast,":[32],"models":[34],"difficulty":[36],"integrating":[37],"uncertainties":[38],"capturing":[40],"the":[41,67,76,146,150],"real":[42],"complexity":[43],"of":[44,78,149],"traffic.":[45],"To":[46],"bridge":[47],"this":[48,106],"gap,":[49],"recent":[50],"studies":[51],"explored":[53],"combining":[54],"them":[55,100],"by":[56,112,139],"embedding":[57],"structure":[59,80],"into":[60],"Gaussian":[61,117],"process.":[62],"These":[63],"approaches":[64],"typically":[65],"introduce":[66],"governing":[68],"equations":[69],"as":[70],"soft":[71],"constraints":[72],"through":[73],"pseudo-observations,":[74],"enabling":[75],"integration":[77],"model":[79,103],"within":[81],"a":[82,114],"variational":[83],"framework.":[84],"However,":[85],"these":[86,110],"rely":[88],"heavily":[89],"on":[90,155],"penalty":[91],"tuning":[92],"principled":[95],"uncertainty":[96,213],"calibration,":[97],"which":[98,215],"makes":[99],"sensitive":[101],"to":[102,121],"mis-specification.":[104],"work,":[107],"we":[108,133],"address":[109],"limitations":[111],"presenting":[113],"novel":[115],"Physics-Embedded":[116],"Process":[118],"(PEGP),":[119],"designed":[120],"integrate":[122],"domain":[123],"knowledge":[124],"with":[125,176,188],"in":[128],"traffic":[129,141],"estimation.":[131],"Specifically,":[132],"design":[134],"two":[135],"multi-output":[136],"kernels":[137],"informed":[138],"classic":[140],"flow":[142],"models,":[143],"constructed":[144],"via":[145],"explicit":[147],"application":[148],"linearized":[151],"differential":[152],"operator.":[153],"Experiments":[154],"HighD,":[156],"NGSIM":[157],"show":[158],"consistent":[159],"improvements":[160],"over":[161],"non-physics":[162],"baselines.":[163],"PEGP-ARZ":[164,184],"proves":[165],"more":[166,199],"reliable":[167,218],"under":[168],"sparse":[169],"observation,":[170],"while":[171],"PEGP-LWR":[172,196],"achieves":[173],"lower":[174],"errors":[175],"denser":[177],"observation.":[178],"Ablation":[179],"study":[180],"further":[181],"reveals":[182],"that":[183],"residuals":[185,197],"align":[186],"closely":[187],"physics":[189],"yield":[191],"calibrated,":[192],"interpretable":[193],"uncertainty,":[194],"whereas":[195],"orthogonal":[200],"produce":[202],"nearly":[203],"constant":[204],"variance":[205],"fields.":[206],"This":[207],"PEGP":[208],"framework":[209],"combines":[210],"priors,":[212],"quantification,":[214],"can":[216],"provide":[217],"support":[219],"for":[220],"TSE.":[221]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-12-05T00:00:00"}
