{"id":"https://openalex.org/W4408700591","doi":"https://doi.org/10.1109/itsc58415.2024.10919538","title":"Dream to Drive: Learning Conditional Driving Policies in Imagination","display_name":"Dream to Drive: Learning Conditional Driving Policies in Imagination","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4408700591","doi":"https://doi.org/10.1109/itsc58415.2024.10919538"},"language":"en","primary_location":{"id":"doi:10.1109/itsc58415.2024.10919538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10919538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061842508","display_name":"Tim Joseph","orcid":null},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tim Joseph","raw_affiliation_strings":["FZI Research Center for Information Technology,Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040476911","display_name":"Marcus Fechner","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marcus Fechner","raw_affiliation_strings":["Institute of Applied Informatics and Formal Description Methods (AIFB), Karlsruhe Institute of Technology,Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Applied Informatics and Formal Description Methods (AIFB), Karlsruhe Institute of Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025333727","display_name":"Ahmed Abouelazm","orcid":null},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ahmed Abouelazm","raw_affiliation_strings":["FZI Research Center for Information Technology,Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108795823","display_name":"Marius Z\u00f6llner","orcid":null},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marius J. Z\u00f6llner","raw_affiliation_strings":["FZI Research Center for Information Technology,Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology,Karlsruhe,Germany","institution_ids":["https://openalex.org/I143379178"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3556,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6302527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1716","last_page":"1723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.986299991607666,"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":0.986299991607666,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9431999921798706,"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/T10731","display_name":"Educational Games and Gamification","score":0.9132000207901001,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational 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/dream","display_name":"Dream","score":0.8378822207450867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4367259740829468},{"id":"https://openalex.org/keywords/policy-learning","display_name":"Policy learning","score":0.4260249435901642},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3829740285873413},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.34753429889678955},{"id":"https://openalex.org/keywords/aesthetics","display_name":"Aesthetics","score":0.32526034116744995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1952773630619049},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.1809072494506836}],"concepts":[{"id":"https://openalex.org/C2781095916","wikidata":"https://www.wikidata.org/wiki/Q36348","display_name":"Dream","level":2,"score":0.8378822207450867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4367259740829468},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.4260249435901642},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3829740285873413},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.34753429889678955},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.32526034116744995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1952773630619049},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.1809072494506836},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc58415.2024.10919538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10919538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W2073787051","https://openalex.org/W2167224731","https://openalex.org/W2342840547","https://openalex.org/W2467604901","https://openalex.org/W2492794003","https://openalex.org/W2599174273","https://openalex.org/W2795064979","https://openalex.org/W2888100907","https://openalex.org/W2890208753","https://openalex.org/W2953303875","https://openalex.org/W2963625099","https://openalex.org/W2981207549","https://openalex.org/W2991137823","https://openalex.org/W3047545417","https://openalex.org/W3092297010","https://openalex.org/W3102777717","https://openalex.org/W3127561923","https://openalex.org/W3128395826","https://openalex.org/W3171935329","https://openalex.org/W3199113962","https://openalex.org/W3204174732","https://openalex.org/W4248396528","https://openalex.org/W4285813059","https://openalex.org/W4285813067","https://openalex.org/W4286285560","https://openalex.org/W4286285582","https://openalex.org/W4308068595","https://openalex.org/W4308081119","https://openalex.org/W4385367241","https://openalex.org/W4387294122","https://openalex.org/W4391768741","https://openalex.org/W4391793331","https://openalex.org/W4401109681","https://openalex.org/W6616173779","https://openalex.org/W6640963894","https://openalex.org/W6683195989","https://openalex.org/W6704559304","https://openalex.org/W6745935785","https://openalex.org/W6754184789","https://openalex.org/W6756256016","https://openalex.org/W6771217966","https://openalex.org/W6783988234"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W1762480892","https://openalex.org/W597599663","https://openalex.org/W3194824274","https://openalex.org/W4205387075","https://openalex.org/W1537165133","https://openalex.org/W2390579330","https://openalex.org/W1578892932","https://openalex.org/W2387132837"],"abstract_inverted_index":{"Learning":[0],"driving":[1,17,32,90],"policies":[2],"to":[3,14,30,47],"control":[4,60],"autonomous":[5],"vehicles":[6],"via":[7],"reinforcement":[8],"learning":[9],"(RL)":[10],"offers":[11],"a":[12,25,31,77,82,88,103],"solution":[13],"learn":[15],"optimal":[16],"behavior":[18,94],"directly":[19],"from":[20],"sensor":[21],"data.":[22],"However,":[23],"designing":[24],"reward":[26,50,72,98,116],"function":[27,73,117],"that":[28,34,86,113,123,137],"leads":[29],"policy":[33,91,122],"works":[35],"in":[36,100,133],"any":[37,69],"situation":[38],"has":[39,46],"not":[40],"yet":[41],"been":[42],"achieved.":[43],"Instead,":[44],"one":[45],"use":[48],"different":[49,53,78,97],"functions":[51,99],"for":[52,95],"situation.":[54],"While":[55],"possible":[56],"with":[57,145],"model":[58],"predictive":[59],"(MPC),":[61],"approaches":[62],"based":[63],"on":[64,126],"RL":[65,84],"must":[66],"be":[67],"re-trained":[68],"time":[70],"the":[71,115,141,146],"changes.":[74],"We":[75,106,129],"suggest":[76],"direction:":[79],"we":[80],"propose":[81],"model-based":[83],"agent":[85],"learns":[87],"conditional":[89],"by":[92,109],"simulating":[93],"many":[96],"imagination":[101],"using":[102],"world":[104],"model.":[105],"do":[107],"so":[108],"randomly":[110],"sampling":[111],"parameters":[112],"shape":[114],"and":[118,135,149],"optimizing":[119],"an":[120],"actor-critic":[121],"is":[124],"conditioned":[125],"these":[127],"parameters.":[128],"evaluate":[130],"our":[131,138],"approach":[132,139],"CARLA":[134],"demonstrate":[136],"combines":[140],"flexibility":[142],"of":[143,152],"MPC":[144],"long-term":[147],"capabilities":[148],"execution":[150],"speed":[151],"RL.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}