{"id":"https://openalex.org/W7143447270","doi":"https://doi.org/10.48550/arxiv.2603.25968","title":"Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control","display_name":"Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7143447270","doi":"https://doi.org/10.48550/arxiv.2603.25968"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25968","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25968","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012199535","display_name":"Zhuoli Zhuang","orcid":"https://orcid.org/0009-0008-5088-3370"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Zhuoli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130991496","display_name":"Yu-Cheng Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Yu-Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130918679","display_name":"Yu-Kai Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yu-Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124947572","display_name":"Thomas Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130967211","display_name":"Chin-Teng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Chin-Teng","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":false,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.4632999897003174,"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":0.4632999897003174,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.21559999883174896,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.10980000346899033,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7699000239372253},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.5371999740600586},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4855000078678131},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41999998688697815},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.37929999828338623},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.373199999332428},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.3630000054836273}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7699000239372253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7124000191688538},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5575000047683716},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.5371999740600586},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42089998722076416},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41999998688697815},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4011000096797943},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.32899999618530273},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.31779998540878296},{"id":"https://openalex.org/C161407221","wikidata":"https://www.wikidata.org/wiki/Q4382939","display_name":"Cognitive model","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C2986342778","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Cognitive systems","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C61641136","wikidata":"https://www.wikidata.org/wiki/Q1107019","display_name":"Cognitive load","level":3,"score":0.28610000014305115},{"id":"https://openalex.org/C117035363","wikidata":"https://www.wikidata.org/wiki/Q3769299","display_name":"Human behavior","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C170494330","wikidata":"https://www.wikidata.org/wiki/Q1778434","display_name":"Cognitive map","level":3,"score":0.2615000009536743},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25968","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25968","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25968","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.6978316307067871,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,19,120,130,197],"computer":[3],"vision":[4],"have":[5],"accelerated":[6],"the":[7,145,151,161,168,172,183,188,192],"development":[8],"of":[9,44,147,163,171,187,194],"autonomous":[10,111,199],"driving.":[11,112],"Despite":[12],"these":[13],"advancements,":[14],"training":[15],"machines":[16],"to":[17,97,132,143],"drive":[18],"a":[20,28,39,121,140],"way":[21],"that":[22,178],"aligns":[23],"with":[24,55,61,64],"human":[25,56,74,99],"expectations":[26],"remains":[27],"significant":[29],"challenge.":[30],"Human":[31,65],"factors":[32],"are":[33],"still":[34],"essential,":[35],"as":[36],"humans":[37],"possess":[38],"sophisticated":[40],"cognitive":[41,100,152,165],"system":[42],"capable":[43],"rapidly":[45],"interpreting":[46],"scene":[47,156],"information":[48,153,166],"and":[49,85,125],"making":[50],"accurate":[51],"decisions.":[52],"Aligning":[53],"machine":[54],"intent":[57],"has":[58],"been":[59],"explored":[60],"Reinforcement":[62],"Learning":[63],"Feedback":[66],"(RLHF).":[67],"Conventional":[68],"RLHF":[69],"methods":[70],"rely":[71],"on":[72,150],"collecting":[73],"preference":[75],"data":[76],"by":[77],"manually":[78],"ranking":[79],"generated":[80],"outputs,":[81],"which":[82],"is":[83],"time-consuming":[84],"indirect.":[86],"In":[87],"this":[88],"work,":[89],"we":[90,159],"propose":[91],"an":[92],"electroencephalography":[93],"(EEG)-guided":[94],"decision-making":[95],"framework":[96,138,180],"incorporate":[98],"insights":[101],"without":[102],"behaviour":[103],"response":[104,131],"interruption":[105],"into":[106,167],"reinforcement":[107],"learning":[108],"(RL)":[109],"for":[110],"We":[113],"collected":[114],"EEG":[115],"signals":[116],"from":[117,154],"20":[118],"participants":[119],"realistic":[122],"driving":[123,200],"simulator":[124],"analyzed":[126],"event-related":[127],"potentials":[128],"(ERP)":[129],"sudden":[133],"environmental":[134],"changes.":[135],"Our":[136,202],"proposed":[137],"employs":[139],"neural":[141],"network":[142],"predict":[144],"strength":[146],"ERP":[148],"based":[149],"visual":[155],"information.":[157],"Moreover,":[158],"explore":[160],"integration":[162],"such":[164],"reward":[169],"signal":[170],"RL":[173,189],"algorithm.":[174],"Experimental":[175],"results":[176],"show":[177],"our":[179],"can":[181],"improve":[182],"collision":[184],"avoidance":[185],"ability":[186],"algorithm,":[190],"highlighting":[191],"potential":[193],"neuro-cognitive":[195],"feedback":[196],"enhancing":[198],"systems.":[201],"project":[203],"page":[204],"is:":[205],"https://alex95gogo.github.io/Cognitive-Reward/.":[206]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-31T00:00:00"}
