{"id":"https://openalex.org/W4286285648","doi":"https://doi.org/10.1109/iv51971.2022.9827255","title":"Uncertainty Aware Data Driven Precautionary Safety for Automated Driving Systems Considering Perception Failures and Event Exposure","display_name":"Uncertainty Aware Data Driven Precautionary Safety for Automated Driving Systems Considering Perception Failures and Event Exposure","publication_year":2022,"publication_date":"2022-06-05","ids":{"openalex":"https://openalex.org/W4286285648","doi":"https://doi.org/10.1109/iv51971.2022.9827255"},"language":"en","primary_location":{"id":"doi:10.1109/iv51971.2022.9827255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827255","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-312006","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089293467","display_name":"Magnus Gyllenhammar","orcid":"https://orcid.org/0000-0001-9020-6501"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]},{"id":"https://openalex.org/I4210086940","display_name":"Zenuity (Sweden)","ror":"https://ror.org/000dpyn16","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086940"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Magnus Gyllenhammar","raw_affiliation_strings":["Zenseact,Göteborg,Sweden","Mechatronics division, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Zenseact,Göteborg,Sweden","institution_ids":["https://openalex.org/I4210086940"]},{"raw_affiliation_string":"Mechatronics division, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089228662","display_name":"Gabriel Rodrigues de Campos","orcid":"https://orcid.org/0000-0002-8218-6915"},"institutions":[{"id":"https://openalex.org/I4210086940","display_name":"Zenuity (Sweden)","ror":"https://ror.org/000dpyn16","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086940"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Gabriel Rodrigues de Campos","raw_affiliation_strings":["Zenseact,Göteborg,Sweden"],"affiliations":[{"raw_affiliation_string":"Zenseact,Göteborg,Sweden","institution_ids":["https://openalex.org/I4210086940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003075014","display_name":"Fredrik Sandblom","orcid":null},"institutions":[{"id":"https://openalex.org/I4210086940","display_name":"Zenuity (Sweden)","ror":"https://ror.org/000dpyn16","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086940"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Sandblom","raw_affiliation_strings":["Zenseact,Göteborg,Sweden"],"affiliations":[{"raw_affiliation_string":"Zenseact,Göteborg,Sweden","institution_ids":["https://openalex.org/I4210086940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065527926","display_name":"Martin T\u00f6rngren","orcid":"https://orcid.org/0000-0002-4300-885X"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Martin Torngren","raw_affiliation_strings":["KTH Royal Institute of Technology,Mechatronics division,Stockholm,Sweden","Mechatronics division, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology,Mechatronics division,Stockholm,Sweden","institution_ids":["https://openalex.org/I86987016"]},{"raw_affiliation_string":"Mechatronics division, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015443350","display_name":"H\u00e5kan Sivencrona","orcid":"https://orcid.org/0000-0002-5371-5048"},"institutions":[{"id":"https://openalex.org/I4210086940","display_name":"Zenuity (Sweden)","ror":"https://ror.org/000dpyn16","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210086940"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Hakan Sivencrona","raw_affiliation_strings":["Zenseact,Göteborg,Sweden"],"affiliations":[{"raw_affiliation_string":"Zenseact,Göteborg,Sweden","institution_ids":["https://openalex.org/I4210086940"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089293467"],"corresponding_institution_ids":["https://openalex.org/I4210086940","https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":0.6243,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66934224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"607","last_page":"615"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T11357","display_name":"Risk and Safety Analysis","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12423","display_name":"Software Reliability and Analysis Research","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/computer-science","display_name":"Computer science","score":0.6032865047454834},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5158390402793884},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.49627095460891724},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.44212859869003296},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.37423622608184814},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34520378708839417},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.33298662304878235},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.183274507522583},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.10994872450828552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032865047454834},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5158390402793884},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.49627095460891724},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.44212859869003296},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.37423622608184814},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34520378708839417},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.33298662304878235},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.183274507522583},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.10994872450828552},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iv51971.2022.9827255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827255","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:kth-312006","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-312006","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:kth-312006","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-312006","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2438413413","https://openalex.org/W2508087128","https://openalex.org/W2514314667","https://openalex.org/W2765486331","https://openalex.org/W2798302089","https://openalex.org/W2896071688","https://openalex.org/W2901393860","https://openalex.org/W2951057540","https://openalex.org/W2963184890","https://openalex.org/W2970699259","https://openalex.org/W3002974307","https://openalex.org/W3004785469","https://openalex.org/W3009285402","https://openalex.org/W3046520285","https://openalex.org/W3093508452","https://openalex.org/W3158017657","https://openalex.org/W3164817606","https://openalex.org/W3210687381","https://openalex.org/W4230519770","https://openalex.org/W4232383088","https://openalex.org/W4297781990"],"related_works":["https://openalex.org/W2628861693","https://openalex.org/W3203087560","https://openalex.org/W4361279463","https://openalex.org/W4232814730","https://openalex.org/W2975814312","https://openalex.org/W4387697615","https://openalex.org/W2568121504","https://openalex.org/W2483836897","https://openalex.org/W2049668268","https://openalex.org/W3013520998"],"abstract_inverted_index":{"Ensuring":[0],"safety":[1,32,44,167,250],"is":[2,22,65,196],"arguably":[3],"one":[4],"of":[5,14,30,53,75,83,113,135,179,214,222,263],"the":[6,28,31,48,51,56,72,76,109,133,139,143,150,154,160,166,180,192,215,220,230,248,264],"largest":[7],"remaining":[8,236],"challenges":[9],"before":[10],"wide-spread":[11],"market":[12],"adoption":[13],"Automated":[15],"Driving":[16],"Systems":[17],"(ADSs).":[18],"One":[19],"central":[20],"aspect":[21],"how":[23,37,101,119,247],"to":[24,38,60,152,158,182,191,208,228],"provide":[25,61],"evidence":[26],"for":[27,68,164,258],"fulfilment":[29],"claims":[33],"and,":[34,116],"in":[35,55,117,149,226],"particular,":[36,118],"produce":[39],"a":[40,66,210,242],"predictive":[41],"and":[42,50,70,78,87,94,111,233,254,261],"reliable":[43],"case":[45],"considering":[46,176],"both":[47],"absence":[49],"presence":[52],"faults":[54],"system.":[57],"In":[58],"order":[59,227],"such":[62,104,120],"evidence,":[63],"there":[64],"need":[67],"describing":[69],"modelling":[71],"different":[73],"elements":[74],"ADS":[77,115],"its":[79],"operational":[80],"context:":[81],"models":[82,106,121,178],"event":[84],"exposure,":[85],"sensing":[86],"perception":[88,194],"models,":[89,201],"as":[90,92,186,188],"well":[91,187],"actuation":[93],"closed-loop":[95],"behaviour":[96],"representations.":[97],"This":[98],"paper":[99],"explores":[100],"estimates":[102],"from":[103,199],"statistical":[105,177,203],"can":[107,122,251],"impact":[108],"performance":[110],"operation":[112,134],"an":[114,174,183],"be":[123,252],"continuously":[124],"improved":[125],"by":[126],"incorporating":[127],"more":[128],"field":[129,224],"data":[130,225],"retrieved":[131],"during":[132],"(previous":[136],"versions":[137],"00":[138],"ADS.":[140,216,265],"Focusing":[141],"on":[142],"safe":[144,162,211],"driving":[145,155,212],"velocity,":[146,163],"this":[147],"results":[148,218],"ability":[151],"update":[153],"policy":[156,213],"so":[157],"maximise":[159],"allowed":[161],"which":[165],"claim":[168],"still":[169],"holds.":[170],"For":[171],"illustration":[172],"purposes,":[173],"example":[175],"exposure":[181],"adverse":[184],"event,":[185],"failures":[189],"related":[190],"system\u2019s":[193,231,249],"system,":[195],"analysed.":[197],"Estimations":[198],"these":[200],"using":[202],"confidence":[204],"limits,":[205],"are":[206],"used":[207],"derive":[209],"The":[217,238],"highlight":[219],"importance":[221],"leveraging":[223,241],"improve":[229],"abilities":[232],"performance,":[234],"while":[235,256],"safe.":[237],"proposed":[239],"methodology,":[240],"data-driven":[243],"approach,":[244],"also":[245],"shows":[246],"monitored":[253],"maintained,":[255],"allowing":[257],"incremental":[259],"expansion":[260],"improvements":[262]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}