{"id":"https://openalex.org/W2990187883","doi":"https://doi.org/10.1109/itsc.2019.8917429","title":"Uncertainty Estimation with Distributional Reinforcement Learning for Applications in Intelligent Transportation Systems: A Case Study","display_name":"Uncertainty Estimation with Distributional Reinforcement Learning for Applications in Intelligent Transportation Systems: A Case Study","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2990187883","doi":"https://doi.org/10.1109/itsc.2019.8917429","mag":"2990187883"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2019.8917429","doi":"https://doi.org/10.1109/itsc.2019.8917429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"IEEE International Conference on Intelligent Transportation Systems (ITSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5103076742","display_name":"Pengyue Wang","orcid":"https://orcid.org/0009-0001-6664-0938","observed_orcids":["https://orcid.org/0009-0001-6664-0938"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengyue Wang","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380373","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-6674-2483","observed_orcids":["https://orcid.org/0000-0002-6674-2483"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102940260","display_name":"Shashi Shekhar","orcid":"https://orcid.org/0000-0002-3191-3879","observed_orcids":["https://orcid.org/0000-0002-3191-3879","https://orcid.org/0000-0001-8217-3244","https://orcid.org/0000-0002-9576-3865","https://orcid.org/0009-0001-8592-2500"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shashi Shekhar","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034090257","display_name":"William F. Northrop","orcid":"https://orcid.org/0000-0001-7189-2075","observed_orcids":["https://orcid.org/0000-0001-7189-2075"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William F. Northrop","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":0.3252,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.56742345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3822","last_page":"3827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.00019999999494757503,"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/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.00019999999494757503,"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/distributional-reinforcement-learning","display_name":"distributional reinforcement learning","score":0.9710000157356262},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.9950000047683716},{"id":"https://openalex.org/keywords/intelligent-transportation-systems","display_name":"intelligent transportation systems","score":0.796999990940094},{"id":"https://openalex.org/keywords/energy-management-strategy","display_name":"energy management strategy","score":0.722000002861023},{"id":"https://openalex.org/keywords/hybrid-electric-vehicles","display_name":"hybrid electric vehicles","score":1.0},{"id":"https://openalex.org/keywords/return-distribution","display_name":"return distribution","score":0.9399999976158142},{"id":"https://openalex.org/keywords/utility-functions","display_name":"utility functions","score":0.8479999899864197},{"id":"https://openalex.org/keywords/domain-knowledge-integration","display_name":"domain knowledge integration","score":0.7699999809265137},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.5740000009536743}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8525477051734924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6969431638717651},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5520013570785522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5297898650169373},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5284329056739807},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4439737796783447},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16694232821464539},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.12727990746498108},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.12546873092651367}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2019.8917429","doi":"https://doi.org/10.1109/itsc.2019.8917429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"IEEE International Conference on Intelligent Transportation Systems (ITSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7088000178337097,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W2121863487","https://openalex.org/W2165150801","https://openalex.org/W2173248099","https://openalex.org/W2342840547","https://openalex.org/W2545546008","https://openalex.org/W2739473244","https://openalex.org/W2745090846","https://openalex.org/W2788086877","https://openalex.org/W2794842204","https://openalex.org/W2798705390","https://openalex.org/W2803308811","https://openalex.org/W2904529603","https://openalex.org/W2907543530","https://openalex.org/W2963423916","https://openalex.org/W2970353014","https://openalex.org/W3148740559","https://openalex.org/W4302570325"],"related_works":["https://openalex.org/W4378190882","https://openalex.org/W2946159594","https://openalex.org/W3127384044","https://openalex.org/W7024269167","https://openalex.org/W4372183490","https://openalex.org/W2122463624","https://openalex.org/W3132227397","https://openalex.org/W7214046644","https://openalex.org/W3200086106","https://openalex.org/W4382981485"],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1],"(RL)":[2],"algorithms":[3],"have":[4],"been":[5],"successfully":[6],"used":[7],"in":[8,140],"the":[9,56,60,93,96,110,134,148,152,162],"area":[10],"of":[11,24,58,85,92,99,112,143],"Intelligent":[12],"Transportation":[13],"Systems":[14],"(ITS)":[15],"for":[16,116],"applications":[17,77],"such":[18,146],"as":[19,50,78,147],"energy":[20],"management":[21],"strategies":[22,168],"(EMS)":[23],"hybrid":[25],"electric":[26],"vehicles,":[27],"autonomous":[28],"driving,":[29],"traffic":[30],"light":[31],"cycle":[32],"control":[33],"and":[34,80,95,103],"bottleneck":[35],"decongestion.":[36],"In":[37],"this":[38],"work,":[39],"we":[40],"investigate":[41],"a":[42,51,113,121,126,141,178],"distributional":[43],"RL":[44],"algorithm":[45],"on":[46],"an":[47,118],"EMS":[48],"problem":[49],"case":[52,127],"study":[53,128],"to":[54,75,89,129,160,172],"show":[55,130],"benefits":[57],"estimating":[59],"uncertainty":[61,70,81,108],"associated":[62],"with":[63],"different":[64,67],"actions":[65],"at":[66,120],"states.":[68],"The":[69,106],"estimation":[71],"is":[72],"highly":[73],"beneficial":[74],"ITS":[76],"randomness":[79],"are":[82],"intrinsic":[83],"characteristics":[84],"real-world":[86,101],"problems":[87],"due":[88],"incomplete":[90],"knowledge":[91,156],"environment":[94],"stochastic":[97],"nature":[98],"some":[100],"systems":[102],"human":[104],"behaviors.":[105],"modeled":[107],"has":[109],"form":[111],"return":[114,153],"distribution":[115],"taking":[117],"action":[119],"certain":[122],"state.":[123],"We":[124],"provide":[125],"that":[131],"only":[132],"considering":[133],"expected":[135],"reward":[136],"value":[137],"would":[138],"result":[139],"loss":[142],"important":[144],"information":[145],"spread.":[149],"By":[150],"modeling":[151],"distribution,":[154],"domain":[155],"can":[157,169],"be":[158,170],"incorporated":[159],"make":[161],"results":[163],"more":[164,174],"interpretable.":[165],"Also,":[166],"risk-sensitive":[167],"developed":[171],"build":[173],"robust":[175],"solutions":[176],"using":[177],"chosen":[179],"utility":[180],"function.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2019-12-05T00:00:00"}
