{"id":"https://openalex.org/W7137832653","doi":"https://doi.org/10.1609/aaai.v40i15.38230","title":"Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving","display_name":"Perception in Plan: Coupled Perception and Planning for End-to-End Autonomous Driving","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137832653","doi":"https://doi.org/10.1609/aaai.v40i15.38230"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i15.38230","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38230","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i15.38230","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129718694","display_name":"Bozhou Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bozhou Zhang","raw_affiliation_strings":["School of Data Science, Fudan University\nShanghai Innovation Institute"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University\nShanghai Innovation Institute","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129705337","display_name":"Jingyu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Li","raw_affiliation_strings":["School of Data Science, Fudan University\nShanghai Innovation Institute"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University\nShanghai Innovation Institute","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129700395","display_name":"Nan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Song","raw_affiliation_strings":["School of Data Science, Fudan University\nShanghai Innovation Institute"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University\nShanghai Innovation Institute","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129732734","display_name":"Li Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["School of Data Science, Fudan University\nShanghai Innovation Institute"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University\nShanghai Innovation Institute","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129718694"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12727273,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"15","first_page":"12376","last_page":"12384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9082000255584717,"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":0.9082000255584717,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.03830000013113022,"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":0.012500000186264515,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.8540999889373779},{"id":"https://openalex.org/keywords/active-perception","display_name":"Active perception","score":0.36390000581741333},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.34380000829696655},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.29649999737739563},{"id":"https://openalex.org/keywords/integrated-business-planning","display_name":"Integrated business planning","score":0.2628999948501587}],"concepts":[{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.8540999889373779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497000217437744},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42649999260902405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.36390000581741333},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.34380000829696655},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C191489605","wikidata":"https://www.wikidata.org/wiki/Q6043021","display_name":"Integrated business planning","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.2621999979019165},{"id":"https://openalex.org/C48243021","wikidata":"https://www.wikidata.org/wiki/Q932522","display_name":"Strategic planning","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i15.38230","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38230","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i15.38230","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i15.38230","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6852251291275024,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"End-to-end":[0],"autonomous":[1,80],"driving":[2,171],"has":[3],"achieved":[4],"remarkable":[5],"advancements":[6],"in":[7],"recent":[8],"years.":[9],"Existing":[10],"methods":[11],"primarily":[12],"follow":[13],"a":[14,25,38,72],"perception\u2013planning":[15],"paradigm,":[16],"where":[17],"perception":[18,44,53,74,91,117,125,146],"and":[19,75,105,119,169,178],"planning":[20,47,57,63,76,88,121],"are":[21,110],"executed":[22],"sequentially":[23],"within":[24],"fully":[26,126,157],"differentiable":[27],"framework":[28,40,77],"for":[29,78,144],"planning-oriented":[30,162],"optimization.":[31],"We":[32],"further":[33],"advance":[34],"this":[35,67,151],"paradigm":[36],"through":[37],"\"perception-in-plan''":[39],"design,":[41,155],"which":[42],"integrates":[43],"into":[45],"the":[46,90,116,120,159,176],"process.":[48],"This":[49],"design":[50],"facilitates":[51],"targeted":[52,106,145],"guided":[54],"by":[55],"evolving":[56],"objectives":[58],"over":[59],"time,":[60],"ultimately":[61],"enhancing":[62],"performance.":[64,187],"Building":[65],"on":[66,114,141,175],"insight,":[68],"we":[69,129],"introduce":[70],"VeteranAD,":[71],"coupled":[73],"end-to-end":[79,163],"driving.":[81],"By":[82],"incorporating":[83],"multi-mode":[84],"anchored":[85],"trajectories":[86,109,138],"as":[87],"priors,":[89],"module":[92],"is":[93],"specifically":[94],"designed":[95],"to":[96,166],"gather":[97],"traffic":[98],"elements":[99],"along":[100],"these":[101],"trajectories,":[102],"enabling":[103],"comprehensive":[104],"perception.":[107],"Planning":[108],"then":[111],"generated":[112],"based":[113],"both":[115],"results":[118],"priors.":[122],"To":[123],"make":[124],"serve":[127],"planning,":[128],"adopt":[130],"an":[131],"autoregressive":[132],"strategy":[133],"that":[134,182],"progressively":[135],"predicts":[136],"future":[137],"while":[139],"focusing":[140],"relevant":[142],"regions":[143],"at":[147],"each":[148],"step.":[149],"With":[150],"simple":[152],"yet":[153],"effective":[154],"VeteranAD":[156,184],"unleashes":[158],"potential":[160],"of":[161],"methods,":[164],"leading":[165],"more":[167],"accurate":[168],"reliable":[170],"behavior.":[172],"Extensive":[173],"experiments":[174],"NAVSIM":[177],"Bench2Drive":[179],"datasets":[180],"demonstrate":[181],"our":[183],"achieves":[185],"state-of-the-art":[186]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}