{"id":"https://openalex.org/W7137268924","doi":"https://doi.org/10.1109/itsc60802.2025.11423202","title":"Modal Contributions to the Robustness of Fusion Perceptions in Autonomous Driving","display_name":"Modal Contributions to the Robustness of Fusion Perceptions in Autonomous Driving","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7137268924","doi":"https://doi.org/10.1109/itsc60802.2025.11423202"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103239127","display_name":"Thai Minh Nguyen","orcid":"https://orcid.org/0009-0007-5208-1649"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Thai M. Nguyen","raw_affiliation_strings":["Monash University,Faculty of Engineering,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Monash University,Faculty of Engineering,Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082029799","display_name":"Quang-Hung Luu","orcid":"https://orcid.org/0000-0002-7771-9836"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Quang-Hung Luu","raw_affiliation_strings":["Monash University,Faculty of Engineering,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Monash University,Faculty of Engineering,Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121532670","display_name":"Hai L. Vu","orcid":null},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hai L. Vu","raw_affiliation_strings":["Monash University,Faculty of Engineering,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Monash University,Faculty of Engineering,Australia","institution_ids":["https://openalex.org/I56590836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1104","last_page":"1110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.45320001244544983,"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":0.45320001244544983,"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/T10427","display_name":"Visual perception and processing mechanisms","score":0.06870000064373016,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.06639999896287918,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6342999935150146},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5810999870300293},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.45820000767707825},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.45339998602867126},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.39419999718666077}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6342999935150146},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5810999870300293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5525000095367432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46700000762939453},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.34209999442100525},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2621999979019165},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.26080000400543213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8851846645","display_name":"Context-aware verification and validation framework for autonomous driving","funder_award_id":"DP210102447","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320320971","display_name":"Monash University","ror":"https://ror.org/02bfwt286"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1784240019","https://openalex.org/W2150066425","https://openalex.org/W2888307014","https://openalex.org/W2963327228","https://openalex.org/W2963400571","https://openalex.org/W3035574168","https://openalex.org/W3045897451","https://openalex.org/W3134026309","https://openalex.org/W3191343975","https://openalex.org/W4385326096","https://openalex.org/W4386075636","https://openalex.org/W4386076667","https://openalex.org/W4390663385","https://openalex.org/W4399458387","https://openalex.org/W4408352647"],"related_works":[],"abstract_inverted_index":{"Fusion":[0],"systems":[1],"combining":[2],"inputs":[3],"from":[4],"multiple":[5],"sensors":[6],"(e.g.,":[7],"LiDAR":[8,149],"and":[9,55,68,106,111,119,138,155,169],"cameras)":[10],"are":[11,179],"standard":[12],"in":[13,27,91],"autonomous":[14],"vehicles":[15],"(AVs).":[16],"Yet,":[17],"their":[18],"robustness":[19,165,194],"against":[20],"unseen":[21],"conditions":[22,58,129],"is":[23,96,142],"challenging":[24],"to":[25,44,72,87,98,147,192],"assess":[26],"the":[28,73,89,112,188,193,196],"absence":[29],"of":[30,195],"ground-truth":[31,182],"data":[32],"or":[33,132],"modality-specific":[34],"degradation.":[35],"In":[36,75],"this":[37],"study,":[38],"we":[39,77],"propose":[40,78],"a":[41,79],"novel":[42],"approach":[43,95],"address":[45],"these":[46],"challenges":[47],"via":[48],"nine":[49],"metamorphic":[50],"relations":[51],"simulating":[52],"diverse":[53],"environmental":[54],"sensor":[56,101],"realistic":[57],"(snow,":[59],"rain,":[60,154],"fog,":[61],"sunlight,":[62],"motion,":[63],"noise,":[64],"shear,":[65],"scale,":[66],"rotation)":[67],"comparing":[69],"degraded":[70],"outputs":[71],"originals.":[74],"addition,":[76],"new":[80],"metric":[81],"called":[82],"Relative":[83],"Robustness":[84],"Score":[85],"(RSS)":[86],"quantify":[88],"decrease":[90],"system":[92],"performance.":[93],"Our":[94,176],"applied":[97],"two":[99],"typical":[100],"systems,":[102],"AVOD":[103,146],"(region-level":[104],"fusion)":[105],"LoGoNet":[107,141],"(attention-based":[108],"feature-level":[109],"fusion),":[110],"results":[113],"reveal":[114],"complex":[115],"relationships":[116],"between":[117],"accuracy":[118,137,161],"robustness,":[120],"with":[121,173],"both":[122],"models":[123],"significantly":[124],"affected":[125],"by":[126],"bad":[127],"weather":[128],"like":[130],"snow":[131],"fog.":[133],"Despite":[134],"superior":[135],"baseline":[136],"average":[139],"RRS,":[140],"less":[143],"robust":[144],"than":[145],"specific":[148],"corruptions,":[150],"such":[151],"as":[152],"snow,":[153],"sun":[156],"glare.":[157],"This":[158],"demonstrates":[159],"that":[160],"does":[162],"not":[163],"ensure":[164],"across":[166],"all":[167],"scenarios,":[168],"modality":[170],"importance":[171],"varies":[172],"corruption":[174],"type.":[175],"proposed":[177],"methods":[178],"built":[180],"without":[181],"labels,":[183],"offering":[184],"real-time":[185],"insights":[186],"into":[187],"individual":[189],"modal":[190],"contribution":[191],"fusion":[197],"systems.":[198]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-17T00:00:00"}