{"id":"https://openalex.org/W4405838326","doi":"https://doi.org/10.1109/tits.2024.3516089","title":"CDRP3: Cascade Deep Reinforcement Learning for Urban Driving Safety With Joint Perception, Prediction, and Planning","display_name":"CDRP3: Cascade Deep Reinforcement Learning for Urban Driving Safety With Joint Perception, Prediction, and Planning","publication_year":2024,"publication_date":"2024-12-27","ids":{"openalex":"https://openalex.org/W4405838326","doi":"https://doi.org/10.1109/tits.2024.3516089"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3516089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3516089","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","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/A5042782010","display_name":"Yuxiang Yang","orcid":"https://orcid.org/0000-0001-8613-7822"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxiang Yang","raw_affiliation_strings":["School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fenglong Ge","orcid":"https://orcid.org/0009-0000-1488-1345"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenglong Ge","raw_affiliation_strings":["School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jinlong Fan","orcid":"https://orcid.org/0000-0002-3221-8149"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinlong Fan","raw_affiliation_strings":["School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075569212","display_name":"Jufeng Zhao","orcid":"https://orcid.org/0000-0002-4491-5566"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jufeng Zhao","raw_affiliation_strings":["School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061517548","display_name":"Zhekang Dong","orcid":"https://orcid.org/0000-0003-4639-3834"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhekang Dong","raw_affiliation_strings":["School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042782010"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":0.5976,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67980586,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"26","issue":"3","first_page":"3976","last_page":"3988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.984000027179718,"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":0.984000027179718,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9704999923706055,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9258999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7118579149246216},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6018810868263245},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5903083086013794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49291372299194336},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.49204108119010925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46770069003105164},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.30638599395751953},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2637169659137726},{"id":"https://openalex.org/keywords/civil-engineering","display_name":"Civil engineering","score":0.10008102655410767},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.09384939074516296}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7118579149246216},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6018810868263245},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5903083086013794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49291372299194336},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.49204108119010925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46770069003105164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30638599395751953},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2637169659137726},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.10008102655410767},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.09384939074516296},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3516089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3516089","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G10963990","display_name":null,"funder_award_id":"62376080","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5346386703","display_name":null,"funder_award_id":"2024C01143","funder_id":"https://openalex.org/F4320307131","funder_display_name":"Alternatives Research and Development Foundation"}],"funders":[{"id":"https://openalex.org/F4320307131","display_name":"Alternatives Research and Development Foundation","ror":"https://ror.org/02bsg4a02"},{"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":44,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1989345169","https://openalex.org/W2051228319","https://openalex.org/W2194775991","https://openalex.org/W2296073425","https://openalex.org/W2343568200","https://openalex.org/W2887286974","https://openalex.org/W2948153973","https://openalex.org/W2962894046","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2964007901","https://openalex.org/W2968008415","https://openalex.org/W2985713881","https://openalex.org/W2990123902","https://openalex.org/W3009593063","https://openalex.org/W3034445502","https://openalex.org/W3092297010","https://openalex.org/W3109791956","https://openalex.org/W3127561923","https://openalex.org/W3128395826","https://openalex.org/W3133988851","https://openalex.org/W3139187989","https://openalex.org/W3172477795","https://openalex.org/W3172863135","https://openalex.org/W3191652410","https://openalex.org/W3191687624","https://openalex.org/W3204475858","https://openalex.org/W3206877181","https://openalex.org/W3212409086","https://openalex.org/W3213557649","https://openalex.org/W4214759451","https://openalex.org/W4225937744","https://openalex.org/W4292347911","https://openalex.org/W4312771252","https://openalex.org/W4318586143","https://openalex.org/W4381733133","https://openalex.org/W4386066695","https://openalex.org/W4386076400","https://openalex.org/W4386824909","https://openalex.org/W4387885918","https://openalex.org/W4389666793","https://openalex.org/W4390872706","https://openalex.org/W4398249471"],"related_works":["https://openalex.org/W2153719181","https://openalex.org/W1971748923","https://openalex.org/W1566155057","https://openalex.org/W2060986072","https://openalex.org/W2052574922","https://openalex.org/W64588465","https://openalex.org/W3120641340","https://openalex.org/W2117825986","https://openalex.org/W3134067061","https://openalex.org/W2079855347"],"abstract_inverted_index":{"Safe":[0],"urban":[1,41,73,244],"driving":[2,37,53,71,145,189,228,240],"is":[3],"challenging":[4],"due":[5],"to":[6,33,48,86,108,130,139,154,185,217,226],"the":[7,19,35,59,80,84,88,91,110,170,176,212],"high":[8],"density":[9],"of":[10,22,52,79,90,114,222],"traffic":[11,160],"flow":[12],"and":[13,28,83,120,135,147,162,183,194,214,219],"various":[14],"potential":[15],"hazards,":[16],"such":[17],"as":[18],"sudden":[20],"appearance":[21],"unknown":[23],"objects.":[24],"Traditional":[25],"rule-based":[26],"approaches":[27],"imitation":[29],"learning":[30,44,104],"methods":[31],"struggle":[32],"address":[34],"diverse":[36],"scenarios":[38,54,119],"encountered":[39],"in":[40,64,72,117,169,242],"environments.":[42,245],"Reinforcement":[43],"(RL),":[45],"which":[46],"adapts":[47],"a":[49,76,99,124,148,192,202],"wide":[50],"range":[51],"through":[55],"continuous":[56],"interaction":[57],"with":[58],"environment,":[60],"has":[61],"demonstrated":[62],"success":[63],"autonomous":[65],"driving.":[66],"Making":[67],"safety":[68,111,223,241],"decisions":[69],"when":[70],"environments":[74],"necessitates":[75],"comprehensive":[77,177],"perception":[78,127,138,182,213],"current":[81],"scene":[82],"ability":[85],"predict":[87,164],"evolution":[89],"dynamic":[92,144],"scene.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97,174],"present":[98],"novel":[100],"cascade":[101],"deep":[102],"reinforcement":[103],"framework,":[105],"CDRP3,":[106],"designed":[107],"enhance":[109],"decision-making":[112,224],"capabilities":[113,225],"self-driving":[115],"vehicles":[116],"complex":[118,156,243],"emergencies.":[121],"We":[122],"leverage":[123],"multi-modal":[125,132],"spatio-temporal":[126,141],"(MmSTP)":[128],"module":[129,153],"fuse":[131],"sensor":[133],"data":[134],"introduce":[136],"temporal":[137],"capture":[140],"information":[142,179],"about":[143],"environments,":[146],"future":[149,166],"state":[150],"prediction":[151,184,215],"(FSP)":[152],"model":[155],"interactions":[157],"between":[158],"different":[159],"participants":[161],"explicitly":[163],"their":[165],"states.":[167],"Subsequently,":[168],"PPO-based":[171],"planning":[172],"module,":[173],"use":[175],"environmental":[178],"obtained":[180],"from":[181,211],"decode":[186],"an":[187],"optimized":[188],"strategy":[190],"using":[191],"lateral":[193],"longitudinal":[195],"separated":[196],"multi-branch":[197],"network":[198],"structure":[199],"guided":[200],"by":[201],"customized":[203],"reward":[204],"function.":[205],"This":[206],"approach":[207],"enables":[208],"knowledge":[209],"transfer":[210],"components":[216],"planning,":[218],"planning-oriented":[220],"enhancement":[221],"improve":[227],"safety.":[229],"Our":[230],"experiments":[231],"demonstrate":[232],"that":[233],"CDRP3":[234],"outperforms":[235],"state-of-the-art":[236],"methods,":[237],"providing":[238],"superior":[239]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}