{"id":"https://openalex.org/W4413018521","doi":"https://doi.org/10.1109/iv64158.2025.11097823","title":"Graph-based Path Planning with Dynamic Obstacle Avoidance for Autonomous Parking","display_name":"Graph-based Path Planning with Dynamic Obstacle Avoidance for Autonomous Parking","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4413018521","doi":"https://doi.org/10.1109/iv64158.2025.11097823"},"language":"en","primary_location":{"id":"doi:10.1109/iv64158.2025.11097823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv64158.2025.11097823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Intelligent Vehicles Symposium (IV)","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/A5052604315","display_name":"Farhad Nawaz","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Farhad Nawaz","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minjun Sung","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Minjun Sung","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071341539","display_name":"Darshan Gadginmath","orcid":"https://orcid.org/0000-0002-6142-7820"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Darshan Gadginmath","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033048366","display_name":"Jovin D\u2019sa","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jovin D'sa","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037040732","display_name":"Sangjae Bae","orcid":"https://orcid.org/0000-0001-7974-8203"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sangjae Bae","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063634505","display_name":"David Isele","orcid":"https://orcid.org/0000-0001-9749-6951"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"David Isele","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074348852","display_name":"Nadia Figueroa","orcid":"https://orcid.org/0000-0002-6873-4671"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nadia Figueroa","raw_affiliation_strings":["University of Pennsylvania,GRASP Lab,PA,USA,19104"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,GRASP Lab,PA,USA,19104","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052941508","display_name":"Nikolai Matni","orcid":"https://orcid.org/0000-0003-4936-3921"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikolai Matni","raw_affiliation_strings":["University of Pennsylvania,GRASP Lab,PA,USA,19104"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,GRASP Lab,PA,USA,19104","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086139281","display_name":"Faizan M. Tariq","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Faizan M. Tariq","raw_affiliation_strings":["Honda Research Institute (HRI),San Jose,CA,USA,95134"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute (HRI),San Jose,CA,USA,95134","institution_ids":["https://openalex.org/I1283473643"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6747,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.95164332,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"702","last_page":"709"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9991999864578247,"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":0.9991999864578247,"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/T12288","display_name":"Optimization and Search Problems","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9789999723434448,"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/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.776836633682251},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.713415801525116},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6562500596046448},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.6341827511787415},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4639676809310913},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4150264263153076},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3297291100025177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28807324171066284},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.28441548347473145},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21749556064605713},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16304084658622742},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.16165274381637573},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.062259674072265625}],"concepts":[{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.776836633682251},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.713415801525116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6562500596046448},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.6341827511787415},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4639676809310913},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4150264263153076},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3297291100025177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28807324171066284},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.28441548347473145},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21749556064605713},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16304084658622742},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.16165274381637573},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.062259674072265625},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv64158.2025.11097823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv64158.2025.11097823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1424654272","https://openalex.org/W1544016679","https://openalex.org/W1576408494","https://openalex.org/W1969483458","https://openalex.org/W1971998222","https://openalex.org/W1976930960","https://openalex.org/W2073787051","https://openalex.org/W2127203018","https://openalex.org/W2166077797","https://openalex.org/W2406067508","https://openalex.org/W2589869525","https://openalex.org/W2782393959","https://openalex.org/W2946036483","https://openalex.org/W3015470607","https://openalex.org/W3081307049","https://openalex.org/W3113727404","https://openalex.org/W3154093784","https://openalex.org/W3181936250","https://openalex.org/W3187511524","https://openalex.org/W3198919602","https://openalex.org/W3207957463","https://openalex.org/W4250589301","https://openalex.org/W4294692071","https://openalex.org/W4301358044","https://openalex.org/W4312270460","https://openalex.org/W4315472204","https://openalex.org/W4320804413","https://openalex.org/W4383097531","https://openalex.org/W4389666601","https://openalex.org/W4391012675","https://openalex.org/W4391216825","https://openalex.org/W4391770190","https://openalex.org/W4392208019","https://openalex.org/W4402738197","https://openalex.org/W4408859815","https://openalex.org/W6605295560"],"related_works":["https://openalex.org/W2930076404","https://openalex.org/W4253519380","https://openalex.org/W2071957557","https://openalex.org/W2596413128","https://openalex.org/W4391249562","https://openalex.org/W2356867392","https://openalex.org/W2782776446","https://openalex.org/W3043170174","https://openalex.org/W2155948905","https://openalex.org/W4380590094"],"abstract_inverted_index":{"Safe":[0],"and":[1,22,32,130,145],"efficient":[2,34],"path":[3],"planning":[4,35,47,101,109,156],"in":[5,82,123,140],"parking":[6,125,159],"scenarios":[7],"presents":[8],"a":[9,30,67],"significant":[10],"challenge":[11],"due":[12],"to":[13,103,149],"the":[14,40,46,50,59,74,83,92,143,150,153],"presence":[15],"of":[16,42,52,76,152],"cluttered":[17],"environments":[18],"filled":[19],"with":[20],"static":[21],"dynamic":[23,43,77,87],"obstacles.":[24],"To":[25],"address":[26],"this,":[27],"we":[28,135],"propose":[29],"novel":[31],"computationally":[33],"strategy":[36],"that":[37,70],"seamlessly":[38],"integrates":[39],"predictions":[41,75],"obstacles":[44,78],"into":[45],"process,":[48],"ensuring":[49],"generation":[51],"collision-free":[53],"paths.":[54],"Our":[55],"approach":[56],"builds":[57],"upon":[58],"conventional":[60],"Hybrid":[61,94],"A":[62,95],"star":[63,96],"algorithm":[64,97],"by":[65,112],"introducing":[66],"time-indexed":[68,93],"variant":[69],"explicitly":[71],"accounts":[72],"for":[73,158],"during":[79],"node":[80],"exploration":[81],"graph,":[84],"thus":[85],"enabling":[86],"obstacle":[88],"avoidance.":[89],"We":[90],"integrate":[91],"within":[98],"an":[99,113],"online":[100],"framework":[102],"compute":[104],"local":[105],"paths":[106],"at":[107],"each":[108],"step,":[110],"guided":[111],"adaptively":[114],"chosen":[115],"intermediate":[116],"goal.":[117],"The":[118],"proposed":[119],"method":[120,157],"is":[121],"validated":[122],"diverse":[124],"scenarios,":[126],"including":[127],"perpendicular,":[128],"angled,":[129],"parallel":[131],"parking.":[132],"Through":[133],"simulations,":[134],"showcase":[136],"our":[137],"approach's":[138],"potential":[139],"greatly":[141],"improving":[142],"efficiency":[144],"safety":[146],"when":[147],"compared":[148],"state":[151],"art":[154],"spline-based":[155],"situations.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
