{"id":"https://openalex.org/W4390285306","doi":"https://doi.org/10.1109/tiv.2023.3347531","title":"Deep Reinforcement Learning-Based Off-Road Path Planning via Low-Dimensional Simulation","display_name":"Deep Reinforcement Learning-Based Off-Road Path Planning via Low-Dimensional Simulation","publication_year":2023,"publication_date":"2023-12-27","ids":{"openalex":"https://openalex.org/W4390285306","doi":"https://doi.org/10.1109/tiv.2023.3347531"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2023.3347531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3347531","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-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/A5100407927","display_name":"Xu Wang","orcid":"https://orcid.org/0000-0003-0935-6735"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Wang","raw_affiliation_strings":["Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0003-0935-6735","affiliations":[{"raw_affiliation_string":"Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034078423","display_name":"Erke Shang","orcid":"https://orcid.org/0000-0002-6669-3933"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Erke Shang","raw_affiliation_strings":["National Innovation Institute of Defense Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6669-3933","affiliations":[{"raw_affiliation_string":"National Innovation Institute of Defense Technology, Beijing, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005995567","display_name":"Bin Dai","orcid":"https://orcid.org/0000-0001-9405-2626"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Dai","raw_affiliation_strings":["National Innovation Institute of Defense Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Innovation Institute of Defense Technology, Beijing, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103213763","display_name":"Qiguang Miao","orcid":"https://orcid.org/0000-0001-6766-8310"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiguang Miao","raw_affiliation_strings":["Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China","National Innovation Institute of Defense Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6766-8310","affiliations":[{"raw_affiliation_string":"Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Innovation Institute of Defense Technology, Beijing, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100882870","display_name":"Yiming Nie","orcid":"https://orcid.org/0000-0003-0421-595X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Nie","raw_affiliation_strings":["National Innovation Institute of Defense Technology, Beijing, China","Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0003-0421-595X","affiliations":[{"raw_affiliation_string":"National Innovation Institute of Defense Technology, Beijing, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Xi&#x0027;an Key Laboratory of Big Data and Intelligent Vision, Xidian University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9426,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.70876139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"9","issue":"9","first_page":"5543","last_page":"5553"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9926999807357788,"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8273527026176453},{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.7553554773330688},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.7043381333351135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6887397766113281},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6427559852600098},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6262065172195435},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6116282343864441},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5630267262458801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5491993427276611},{"id":"https://openalex.org/keywords/grid-method-multiplication","display_name":"Grid method multiplication","score":0.4798792898654938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3676247298717499},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32169634103775024},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.18482354283332825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17813459038734436},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.1306987702846527},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.11358943581581116},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06821262836456299}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8273527026176453},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.7553554773330688},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.7043381333351135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887397766113281},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6427559852600098},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6262065172195435},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6116282343864441},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5630267262458801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5491993427276611},{"id":"https://openalex.org/C91370436","wikidata":"https://www.wikidata.org/wiki/Q5608616","display_name":"Grid method multiplication","level":3,"score":0.4798792898654938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3676247298717499},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32169634103775024},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.18482354283332825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17813459038734436},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.1306987702846527},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.11358943581581116},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06821262836456299},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2023.3347531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2023.3347531","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G6834291205","display_name":null,"funder_award_id":"62272364","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1969483458","https://openalex.org/W2002219970","https://openalex.org/W2058966437","https://openalex.org/W2063346307","https://openalex.org/W2076337359","https://openalex.org/W2077057258","https://openalex.org/W2117211893","https://openalex.org/W2119717200","https://openalex.org/W2145339207","https://openalex.org/W2196524641","https://openalex.org/W2296073425","https://openalex.org/W2395579298","https://openalex.org/W2903709398","https://openalex.org/W2905173465","https://openalex.org/W2942307437","https://openalex.org/W2966477753","https://openalex.org/W2995481444","https://openalex.org/W3011646207","https://openalex.org/W3088197938","https://openalex.org/W3120991176","https://openalex.org/W3122209084","https://openalex.org/W3162923460","https://openalex.org/W3170571425","https://openalex.org/W3205321526","https://openalex.org/W3210290940","https://openalex.org/W4297964528","https://openalex.org/W4306835713","https://openalex.org/W4308080451","https://openalex.org/W4327662239","https://openalex.org/W4353056919","https://openalex.org/W4383108453","https://openalex.org/W4386083237","https://openalex.org/W4386494508","https://openalex.org/W4386702654","https://openalex.org/W4386918930","https://openalex.org/W6605295560","https://openalex.org/W6627932998","https://openalex.org/W6631015714","https://openalex.org/W6638018090","https://openalex.org/W6692846177","https://openalex.org/W6745935785","https://openalex.org/W6756486208","https://openalex.org/W6756840741","https://openalex.org/W6775683342","https://openalex.org/W6784049536","https://openalex.org/W6788927584","https://openalex.org/W6790728114"],"related_works":["https://openalex.org/W2908094156","https://openalex.org/W2030136595","https://openalex.org/W3172527413","https://openalex.org/W2142360609","https://openalex.org/W4313270149","https://openalex.org/W4220840932","https://openalex.org/W2007857089","https://openalex.org/W2403683192","https://openalex.org/W3036618925","https://openalex.org/W2147898618"],"abstract_inverted_index":{"Path":[0],"planning":[1,32],"is":[2,54,70,83],"a":[3,26,41],"critical":[4],"aspect":[5],"of":[6],"autonomous":[7],"driving.":[8],"Traditional":[9],"methods":[10],"have":[11],"excelled":[12],"in":[13,40,87],"urban":[14],"environments":[15],"but":[16],"struggle":[17],"off-road":[18,30],"due":[19],"to":[20,56,60,72,105],"unpredictable":[21],"conditions.":[22],"This":[23],"paper":[24],"introduces":[25],"Deep":[27],"Reinforcement":[28],"Learning-based":[29],"path":[31],"approach":[33],"called":[34],"PPOAC":[35],"by":[36,45],"training":[37,76],"the":[38,58,74],"agent":[39,59,82],"low-dimensional":[42],"simulator":[43],"built":[44],"Occupancy":[46],"Grid":[47],"Maps":[48],"(OGMs).":[49],"A":[50],"self-supervised":[51],"auxiliary":[52],"task":[53],"proposed":[55],"help":[57],"learn":[61],"environmental":[62],"knowledge.":[63],"Moreover,":[64],"an":[65],"adaptive":[66],"curriculum":[67],"learning":[68],"method":[69],"introduced":[71],"enhance":[73],"agent's":[75],"efficiency":[77],"and":[78,85,90,99],"generalization":[79],"ability.":[80],"The":[81],"trained":[84],"evaluated":[86],"real-world":[88],"data,":[89],"experimental":[91],"results":[92],"demonstrate":[93],"that":[94],"it":[95],"can":[96],"obtain":[97],"traversable":[98],"safe":[100],"paths":[101],"while":[102],"generalizing":[103],"effectively":[104],"unknown":[106],"environments.":[107]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
