{"id":"https://openalex.org/W7167666314","doi":"https://doi.org/10.48550/arxiv.2607.05783","title":"Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective","display_name":"Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective","publication_year":2026,"publication_date":"2026-07-07","ids":{"openalex":"https://openalex.org/W7167666314","doi":"https://doi.org/10.48550/arxiv.2607.05783"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.05783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.05783","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140240008","display_name":"Tianyuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Tianyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140238808","display_name":"Xianglong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xianglong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140257388","display_name":"Aishan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Aishan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140290445","display_name":"Lu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140259633","display_name":"Yitong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yitong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140259365","display_name":"Peng Yue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140296994","display_name":"Mingchuan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Mingchuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140279294","display_name":"Siyuan Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Siyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140246850","display_name":"Dacheng Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Dacheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.8974999785423279,"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":0.8974999785423279,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.045899998396635056,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.01679999940097332,"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/robustness","display_name":"Robustness (evolution)","score":0.7132999897003174},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6330999732017517},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.49239999055862427},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.48649999499320984},{"id":"https://openalex.org/keywords/illusion","display_name":"Illusion","score":0.4138999879360199},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.3995000123977661},{"id":"https://openalex.org/keywords/cruise-control","display_name":"Cruise control","score":0.3874000012874603}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7132999897003174},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6330999732017517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6168000102043152},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.49239999055862427},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44040000438690186},{"id":"https://openalex.org/C184047640","wikidata":"https://www.wikidata.org/wiki/Q182593","display_name":"Illusion","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C113168747","wikidata":"https://www.wikidata.org/wiki/Q507295","display_name":"Cruise control","level":3,"score":0.3874000012874603},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.35359999537467957},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2648000121116638},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2646999955177307},{"id":"https://openalex.org/C28063669","wikidata":"https://www.wikidata.org/wiki/Q7167042","display_name":"Perceptual system","level":3,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.05783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.05783","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.05783","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Environmental":[0],"illusions":[1,114,149,210],"(eg.,":[2],"shadows,":[3],"reflections,":[4],"and":[5,29,72,85,115,138,168,182,253],"tire":[6],"marks)":[7],"are":[8],"naturally":[9],"existing":[10,40],"yet":[11],"overlooked":[12],"phenomena":[13],"in":[14,166,172,180,186,224],"real-world":[15,218],"driving":[16,36,215],"environments.":[17],"They":[18],"can":[19,211],"disturb":[20],"visual":[21,140],"perception,":[22],"leading":[23],"to":[24,34,120,202,213],"misinterpretation":[25],"of":[26,103,113,131,154],"the":[27,59,95,101,117,152,194,233],"scene":[28],"posing":[30],"serious":[31],"safety":[32],"risks":[33],"autonomous":[35],"(AD)":[37],"systems.":[38],"However,":[39],"researches":[41],"largely":[42],"overlook":[43],"these":[44,209],"phenomena,":[45],"leaving":[46],"a":[47,63,129,163,169,177,183],"critical":[48],"gap.":[49],"To":[50,228],"address":[51],"this":[52,91],"issue,":[53],"we":[54,93,231],"study":[55],"AD":[56],"robustness":[57,102,247],"through":[58],"lane":[60,73,82,104],"perception":[61,105],"perspective,":[62],"fundamental":[64],"task":[65],"supporting":[66],"core":[67],"functions":[68],"like":[69],"cruise":[70],"control":[71],"centering.":[74],"We":[75],"focus":[76],"on":[77,250,255],"two":[78],"representative":[79],"models:":[80],"conventional":[81],"detection":[83],"(LD)":[84],"vision-language":[86],"model-based":[87],"systems":[88],"(ADVLMs).":[89],"In":[90],"work,":[92],"introduce":[94],"first":[96],"benchmark,":[97],"LanEvil++,":[98],"for":[99],"evaluating":[100],"under":[106,243],"environmental":[107,148],"illusions.":[108],"LanEvil++":[109],"encompasses":[110],"14":[111],"types":[112],"leverages":[116],"CARLA":[118],"simulator":[119],"generate":[121],"94":[122],"high-fidelity,":[123],"fully":[124],"controllable":[125],"3D":[126],"scenes,":[127],"yielding":[128],"dataset":[130],"90,292":[132],"annotated":[133],"images,":[134],"1,596":[135],"video":[136],"clips,":[137],"41,855":[139],"question":[141],"answering":[142],"pairs.":[143],"Extensive":[144],"evaluations":[145],"demonstrate":[146],"that":[147,208],"substantially":[150],"degrade":[151],"performance":[153],"state-of-the-art":[155],"LD":[156,160,251],"methods.":[157],"On":[158],"average,":[159],"models":[161,252],"experience":[162],"5.27%":[164],"drop":[165,185],"Accuracy":[167],"10.49%":[170],"decline":[171],"F1-score,":[173],"while":[174],"ADVLMs":[175],"show":[176],"2.03%":[178],"reduction":[179],"GPT-score":[181],"0.75%":[184],"Language-score.":[187],"Among":[188],"all":[189],"illusions,":[190],"shadows":[191],"emerge":[192],"as":[193],"most":[195],"disruptive":[196],"factor,":[197],"reducing":[198],"accuracy":[199],"by":[200,248],"up":[201],"7.20%.":[203],"Furthermore,":[204],"closed-loop":[205],"simulations":[206],"reveal":[207],"lead":[212],"incorrect":[214],"decisions.":[216],"Complementary":[217],"case":[219],"studies":[220],"highlight":[221],"safety-critical":[222],"failures":[223],"actual":[225],"traffic":[226],"scenes.":[227],"enhance":[229],"robustness,":[230],"propose":[232],"Multimodal":[234],"Illusion":[235],"Defense":[236],"Approach":[237],"(MIDA).":[238],"MIDA":[239],"achieves":[240],"substantial":[241],"gains":[242],"challenging":[244],"conditions,":[245],"boosting":[246],"4.23%":[249],"3.82%":[254],"ADVLMs.":[256]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-09T00:00:00"}