{"id":"https://openalex.org/W4414459055","doi":"https://doi.org/10.1109/tvt.2025.3613697","title":"RAKD: Risk-Aware Knowledge Distillation for Autonomous Driving in Adversarial Scenarios","display_name":"RAKD: Risk-Aware Knowledge Distillation for Autonomous Driving in Adversarial Scenarios","publication_year":2025,"publication_date":"2025-09-24","ids":{"openalex":"https://openalex.org/W4414459055","doi":"https://doi.org/10.1109/tvt.2025.3613697"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2025.3613697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3613697","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5085219433","display_name":"Yuenan Zhao","orcid":"https://orcid.org/0009-0006-2848-3720"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuenan Zhao","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0006-2848-3720","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaoyu Xu","orcid":"https://orcid.org/0000-0002-1580-8905"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Xu","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-1580-8905","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ruitong Li","orcid":"https://orcid.org/0009-0005-7269-2194"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruitong Li","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0005-7269-2194","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047100124","display_name":"Ran Song","orcid":"https://orcid.org/0000-0002-1344-4415"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Song","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-1344-4415","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100756634","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-4960-3190"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-4960-3190","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1211409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"75","issue":"3","first_page":"3845","last_page":"3858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9797999858856201,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9571999907493591,"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/adversarial-system","display_name":"Adversarial system","score":0.8141999840736389},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.744700014591217},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5806999802589417},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.573199987411499},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5511000156402588},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.5425999760627747},{"id":"https://openalex.org/keywords/policy-learning","display_name":"Policy learning","score":0.45419999957084656},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.3797000050544739}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8141999840736389},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.744700014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.595300018787384},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5806999802589417},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.573199987411499},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42660000920295715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41429999470710754},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.37619999051094055},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32100000977516174},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3066999912261963},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2685000002384186},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C43091099","wikidata":"https://www.wikidata.org/wiki/Q1067788","display_name":"Through-the-lens metering","level":3,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2025.3613697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2025.3613697","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G320566030","display_name":null,"funder_award_id":"2021ZD0112002","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G6033659780","display_name":null,"funder_award_id":"U22A2057","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"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2798786289","https://openalex.org/W2837605352","https://openalex.org/W2905173465","https://openalex.org/W2962894046","https://openalex.org/W2990123902","https://openalex.org/W3003296750","https://openalex.org/W3011462663","https://openalex.org/W3034445502","https://openalex.org/W3128395826","https://openalex.org/W3131231561","https://openalex.org/W3133988851","https://openalex.org/W3147335029","https://openalex.org/W3172863135","https://openalex.org/W3193987867","https://openalex.org/W3198460218","https://openalex.org/W4285227658","https://openalex.org/W4291653325","https://openalex.org/W4292347911","https://openalex.org/W4312406013","https://openalex.org/W4312609010","https://openalex.org/W4312769831","https://openalex.org/W4312862130","https://openalex.org/W4368232744","https://openalex.org/W4383108532","https://openalex.org/W4385245566","https://openalex.org/W4386066695","https://openalex.org/W4386071479","https://openalex.org/W4386071585","https://openalex.org/W4386494430","https://openalex.org/W4389879653","https://openalex.org/W4390873009","https://openalex.org/W4393140561","https://openalex.org/W4399666337","https://openalex.org/W4399994102","https://openalex.org/W4401109681","https://openalex.org/W4402557700","https://openalex.org/W7133208528"],"related_works":[],"abstract_inverted_index":{"Aggressive":[0],"driving":[1,26,138],"behaviors":[2],"of":[3,13],"surrounding":[4],"road":[5],"users":[6],"pose":[7],"substantial":[8],"threats":[9],"to":[10,22,31,65,90,148],"the":[11,33,111,116],"safety":[12],"autonomous":[14],"vehicles.":[15],"However,":[16],"current":[17],"imitation":[18,96],"learning":[19,64],"methods":[20],"struggle":[21],"learn":[23,32],"a":[24,49,58,67,107],"risk-aware":[25,51,87],"policy,":[27],"as":[28],"they":[29],"fail":[30],"intrinsic":[34],"decision-making":[35],"principles":[36],"and":[37,72,86,140],"safety-relevant":[38],"features":[39,118],"from":[40],"high-dimensional":[41],"records.":[42],"To":[43],"address":[44],"this":[45],"issue,":[46],"we":[47,105],"propose":[48],"robust":[50],"knowledge":[52],"distillation":[53],"(RAKD)":[54],"framework.":[55],"RAKD":[56],"employs":[57],"privileged":[59,76],"teacher":[60,77],"based":[61],"on":[62,102,125],"reinforcement":[63],"supervise":[66],"vision-based":[68],"student":[69,112,135],"via":[70],"policy":[71],"feature":[73,122],"distillation.":[74],"The":[75],"leverages":[78],"two":[79],"novel":[80],"safetycritical":[81],"representations":[82],"in":[83,110,143],"bird's-eye":[84],"view":[85],"reward":[88],"shaping":[89],"enhance":[91],"risk-sensitive":[92],"learning,":[93],"establishing":[94],"superior":[95,137],"benchmarks":[97],"through":[98,119],"on-policy":[99],"learning.":[100],"Building":[101],"these":[103],"benchmarks,":[104],"integrate":[106],"teachable":[108],"module":[109],"network,":[113],"aligning":[114],"with":[115],"teacher's":[117],"multiscale":[120],"attention-based":[121],"distillation,":[123],"focusing":[124],"collision":[126,141],"risk-related":[127],"information.":[128],"Experimental":[129],"results":[130],"demonstrate":[131],"that":[132],"our":[133],"RAKD-trained":[134],"achieves":[136],"score":[139],"avoidance":[142],"diverse":[144],"adversarial":[145],"scenarios":[146],"compared":[147],"baselines.":[149],"Our":[150],"repository":[151],"is":[152],"publicly":[153],"available":[154],"at":[155],"https://github.":[156],"com/quliang93/RAKD.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}