{"id":"https://openalex.org/W4414603504","doi":"https://doi.org/10.1109/access.2025.3615723","title":"Dynamic Scenario Transfer for Motion Planning in Autonomous Driving: A Successor Representation Approach","display_name":"Dynamic Scenario Transfer for Motion Planning in Autonomous Driving: A Successor Representation Approach","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414603504","doi":"https://doi.org/10.1109/access.2025.3615723"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3615723","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615723","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3615723","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037353988","display_name":"Naghmeh Niroomand","orcid":"https://orcid.org/0000-0002-2122-1959"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naghmeh Niroomand","raw_affiliation_strings":["Department of Information Technology and Electrical Engineering (D-ITET), ETH Zürich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology and Electrical Engineering (D-ITET), ETH Zürich, Switzerland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027726192","display_name":"Christian Bach","orcid":"https://orcid.org/0000-0001-6204-2327"},"institutions":[{"id":"https://openalex.org/I71824836","display_name":"Swiss Federal Laboratories for Materials Science and Technology","ror":"https://ror.org/02x681a42","country_code":"CH","type":"facility","lineage":["https://openalex.org/I2799323385","https://openalex.org/I71824836"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Christian Bach","raw_affiliation_strings":["Chemical Energy Carriers and Vehicle Systems Laboratory, Empa -Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-6204-2327","affiliations":[{"raw_affiliation_string":"Chemical Energy Carriers and Vehicle Systems Laboratory, Empa -Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland","institution_ids":["https://openalex.org/I71824836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2224822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9829000234603882,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9746999740600586,"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/motion-planning","display_name":"Motion planning","score":0.6593000292778015},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6583999991416931},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6366000175476074},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6136999726295471},{"id":"https://openalex.org/keywords/successor-cardinal","display_name":"Successor cardinal","score":0.5618000030517578},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.5501000285148621},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4941999912261963},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.462799996137619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7583000063896179},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6593000292778015},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6583999991416931},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6366000175476074},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6136999726295471},{"id":"https://openalex.org/C75306776","wikidata":"https://www.wikidata.org/wiki/Q7632662","display_name":"Successor cardinal","level":2,"score":0.5618000030517578},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.5501000285148621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.536300003528595},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4072999954223633},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3050000071525574},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.29490000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.27810001373291016},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.25200000405311584}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/access.2025.3615723","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615723","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/798949","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/798949","pdf_url":null,"source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access, 13","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:dora:empa_42927","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401298","display_name":"DORA Empa (Swiss Federal Laboratories for Materials Science and Technology (Empa))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71824836","host_organization_name":"Swiss Federal Laboratories for Materials Science and Technology","host_organization_lineage":["https://openalex.org/I71824836"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"IEEE Access","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:2ac3b289882e46699612fb5fc119d6ac","is_oa":true,"landing_page_url":"https://doaj.org/article/2ac3b289882e46699612fb5fc119d6ac","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 170636-170659 (2025)","raw_type":"article"},{"id":"doi:10.3929/ethz-c-000798949","is_oa":true,"landing_page_url":"https://doi.org/10.3929/ethz-c-000798949","pdf_url":null,"source":{"id":"https://openalex.org/S7407051236","display_name":"ETH Z\u00fcrich Research Collection","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"article-journal"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3615723","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3615723","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Adaptive":[0],"motion":[1,17,49,139],"planning":[2,18,50,127,140],"systems":[3,159],"are":[4],"essential":[5],"for":[6],"autonomous":[7,157],"vehicles":[8],"to":[9,77,137],"navigate":[10],"complex":[11],"and":[12,31,90,108,132,154],"dynamic":[13,32],"urban":[14],"environments.":[15,79,164],"Traditional":[16],"approaches":[19],"often":[20],"struggle":[21],"in":[22,160],"environments":[23],"lacking":[24],"structured":[25],"references":[26],"or":[27,162],"involving":[28],"both":[29],"static":[30,107],"obstacles,":[33],"such":[34],"as":[35,115],"parking":[36],"lots.":[37],"This":[38,80,96],"study":[39,97],"proposes":[40],"a":[41,116],"semi-supervised":[42],"deep":[43],"transfer":[44,55,148],"learning":[45],"framework":[46,64,103],"that":[47,123,145],"enhances":[48,133],"by":[51],"enabling":[52],"scenario-level":[53,146],"knowledge":[54,76,147],"across":[56],"diverse":[57],"contexts.":[58],"By":[59],"leveraging":[60],"successor":[61],"representations,":[62],"the":[63,72,85,101,152],"captures":[65],"transition":[66],"relationships":[67],"within":[68],"specific":[69],"scenarios,":[70],"facilitating":[71],"adaptation":[73],"of":[74,156],"learned":[75],"new":[78],"capability":[81],"is":[82],"incorporated":[83],"through":[84,104],"Knowledge-based":[86],"Scenario":[87],"Transfer":[88],"Learning":[89],"Artificial":[91],"Potential":[92],"Fields":[93],"(KSTL-APF)":[94],"approach.":[95],"focuses":[98],"on":[99],"validating":[100],"proposed":[102],"simulation":[105],"under":[106],"semi-dynamic":[109],"conditions,":[110],"with":[111],"real-world":[112],"deployment":[113],"identified":[114],"future":[117],"development":[118],"phase.":[119],"Experimental":[120],"results":[121],"indicate":[122],"KSTL-APF":[124],"significantly":[125,150],"improves":[126],"efficiency,":[128],"reduces":[129],"computational":[130],"time,":[131],"trajectory":[134],"robustness":[135],"compared":[136],"conventional":[138],"methods.":[141],"These":[142],"findings":[143],"suggest":[144],"can":[149],"increase":[151],"adaptability":[153],"reliability":[155],"vehicle":[158],"unstructured":[161],"unfamiliar":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}