{"id":"https://openalex.org/W2594201198","doi":"https://doi.org/10.23919/acc.2017.7963408","title":"The value of inferring the internal state of traffic participants for autonomous freeway driving","display_name":"The value of inferring the internal state of traffic participants for autonomous freeway driving","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2594201198","doi":"https://doi.org/10.23919/acc.2017.7963408","mag":"2594201198"},"language":"en","primary_location":{"id":"doi:10.23919/acc.2017.7963408","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7963408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","raw_type":"proceedings-article"},"type":"article","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/A5054686855","display_name":"Zachary N. Sunberg","orcid":"https://orcid.org/0000-0001-9707-3035"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zachary N. Sunberg","raw_affiliation_strings":["Department of Aeronautics and Astronautics, Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Aeronautics and Astronautics, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055716138","display_name":"C. J. Ho","orcid":"https://orcid.org/0000-0002-8990-8159"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher J. Ho","raw_affiliation_strings":["Department of Aeronautics and Astronautics, Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Aeronautics and Astronautics, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068326377","display_name":"Mykel J. Kochenderfer","orcid":"https://orcid.org/0000-0002-7238-9663"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mykel J. Kochenderfer","raw_affiliation_strings":["Department of Aeronautics and Astronautics, Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Aeronautics and Astronautics, Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.7859,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.96857662,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3004","last_page":"3010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"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/T10524","display_name":"Traffic control and management","score":0.9983999729156494,"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/T10370","display_name":"Traffic and Road Safety","score":0.988099992275238,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.774993896484375},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6794959306716919},{"id":"https://openalex.org/keywords/internal-model","display_name":"Internal model","score":0.6737094521522522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.669793963432312},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.51959228515625},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5021567344665527},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.45968198776245117},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.4485807716846466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4431527853012085},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4292401075363159},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.38126951456069946},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3469947576522827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3363683223724365},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3239266574382782},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.25616851449012756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16157597303390503},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1309736669063568}],"concepts":[{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.774993896484375},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6794959306716919},{"id":"https://openalex.org/C28427503","wikidata":"https://www.wikidata.org/wiki/Q13580300","display_name":"Internal model","level":3,"score":0.6737094521522522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.669793963432312},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.51959228515625},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5021567344665527},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.45968198776245117},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.4485807716846466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4431527853012085},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4292401075363159},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.38126951456069946},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3469947576522827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3363683223724365},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3239266574382782},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.25616851449012756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16157597303390503},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1309736669063568},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc.2017.7963408","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc.2017.7963408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W107054272","https://openalex.org/W123090642","https://openalex.org/W1557122569","https://openalex.org/W1605929701","https://openalex.org/W1801976851","https://openalex.org/W1947279355","https://openalex.org/W1961245208","https://openalex.org/W1965455100","https://openalex.org/W1996878604","https://openalex.org/W2030032449","https://openalex.org/W2056877664","https://openalex.org/W2073787051","https://openalex.org/W2083651391","https://openalex.org/W2124595631","https://openalex.org/W2126316555","https://openalex.org/W2171084228","https://openalex.org/W2202148372","https://openalex.org/W2319542951","https://openalex.org/W2336416123","https://openalex.org/W2411577903","https://openalex.org/W2565370028","https://openalex.org/W2966291251","https://openalex.org/W3135693734","https://openalex.org/W3148740559","https://openalex.org/W6604974139","https://openalex.org/W6633557274","https://openalex.org/W6638440308","https://openalex.org/W6678541622","https://openalex.org/W6684973485","https://openalex.org/W6699840735","https://openalex.org/W6791207710"],"related_works":["https://openalex.org/W2123651102","https://openalex.org/W2287992105","https://openalex.org/W2953027552","https://openalex.org/W2570299561","https://openalex.org/W2392831491","https://openalex.org/W804484174","https://openalex.org/W1568779110","https://openalex.org/W2117555338","https://openalex.org/W2160491016","https://openalex.org/W4252740972"],"abstract_inverted_index":{"Safe":[0],"interaction":[1],"with":[2,52,79,115,199],"human":[3,50],"drivers":[4,120],"is":[5,88,111,171],"one":[6],"of":[7,61,73,103],"the":[8,21,58,62,71,104,122,142,150,157,177],"primary":[9],"challenges":[10],"for":[11,49,69],"autonomous":[12],"vehicles.":[13],"In":[14],"order":[15],"to":[16,131,146,162,187],"plan":[17],"driving":[18],"maneuvers":[19],"effectively,":[20],"vehicle's":[22],"control":[23],"system":[24],"must":[25],"infer":[26],"and":[27,41,65,77,180],"predict":[28],"how":[29],"humans":[30],"will":[31],"behave":[32],"based":[33],"on":[34],"their":[35,80],"latent":[36],"internal":[37,59,105,124,143,151],"state":[38,144,152],"(e.g.,":[39],"intentions":[40],"aggressiveness).":[42],"This":[43],"research":[44],"uses":[45],"a":[46,67,133,163,172],"simple":[47],"model":[48,195],"behavior":[51],"unknown":[53],"parameters":[54,196],"that":[55,99,118,140,169],"make":[56],"up":[57],"states":[60,76],"traffic":[63],"participants":[64],"presents":[66],"method":[68,161],"quantifying":[70],"value":[72],"estimating":[74],"these":[75],"planning":[78,114,183],"uncertainty":[81,145],"explicitly":[82],"modeled.":[83],"An":[84],"upper":[85,178],"performance":[86,174],"bound":[87,110,179],"established":[89,112],"by":[90,113],"an":[91,154],"omniscient":[92],"Monte":[93],"Carlo":[94],"Tree":[95],"Search":[96],"(MCTS)":[97],"planner":[98],"has":[100],"perfect":[101],"knowledge":[102],"states.":[106],"A":[107],"baseline":[108],"lower":[109],"MCTS":[116,126],"assuming":[117],"all":[119],"have":[121],"same":[123],"state.":[125],"variants":[127],"are":[128,197],"then":[129],"used":[130],"solve":[132],"partially":[134],"observable":[135],"Markov":[136],"decision":[137],"process":[138],"(POMDP)":[139],"models":[141],"determine":[147],"whether":[148],"inferring":[149],"offers":[153],"advantage":[155],"over":[156],"baseline.":[158,181],"Applying":[159],"this":[160,189],"freeway":[164],"lane":[165],"changing":[166],"scenario":[167],"reveals":[168],"there":[170],"significant":[173],"gap":[175],"between":[176],"POMDP":[182],"techniques":[184],"come":[185],"close":[186],"closing":[188],"gap,":[190],"especially":[191],"when":[192],"important":[193],"hidden":[194],"correlated":[198],"measurable":[200],"parameters.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
