{"id":"https://openalex.org/W4308079998","doi":"https://doi.org/10.1109/itsc55140.2022.9921981","title":"Parameterisation of lane-change scenarios from real-world data","display_name":"Parameterisation of lane-change scenarios from real-world data","publication_year":2022,"publication_date":"2022-10-08","ids":{"openalex":"https://openalex.org/W4308079998","doi":"https://doi.org/10.1109/itsc55140.2022.9921981"},"language":"en","primary_location":{"id":"doi:10.1109/itsc55140.2022.9921981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc55140.2022.9921981","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","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 25th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-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/A5026001391","display_name":"Dhanoop Karunakaran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]},{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Dhanoop Karunakaran","raw_affiliation_strings":["University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]},{"raw_affiliation_string":"Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038732366","display_name":"Julie Stephany Berr\u00edo","orcid":"https://orcid.org/0000-0003-3126-7042"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Julie Stephany Berrio","raw_affiliation_strings":["University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]},{"raw_affiliation_string":"Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070356056","display_name":"Stewart Worrall","orcid":"https://orcid.org/0000-0001-7940-4742"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Stewart Worrall","raw_affiliation_strings":["University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]},{"raw_affiliation_string":"Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053507972","display_name":"E. Nebot","orcid":"https://orcid.org/0000-0002-3914-3741"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Eduardo Nebot","raw_affiliation_strings":["University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of Sydney,Australian Centre for Field Robotics (ACFR),NSW,Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]},{"raw_affiliation_string":"Australian Centre for Field Robotics (ACFR), University of Sydney, NSW, Australia","institution_ids":["https://openalex.org/I4210127558","https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026001391"],"corresponding_institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"],"apc_list":null,"apc_paid":null,"fwci":1.0819,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78337122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2607","last_page":"2613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"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":0.9995999932289124,"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/T10370","display_name":"Traffic and Road Safety","score":0.9621000289916992,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T13295","display_name":"Safety Systems Engineering in Autonomy","score":0.9466000199317932,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7632243633270264},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6469593644142151},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5791386961936951},{"id":"https://openalex.org/keywords/scenario-testing","display_name":"Scenario testing","score":0.56820148229599},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5138657093048096},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.513566255569458},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4892103672027588},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.4427911043167114},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.43602487444877625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4221016764640808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.287795752286911},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1268598735332489}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7632243633270264},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6469593644142151},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5791386961936951},{"id":"https://openalex.org/C80519477","wikidata":"https://www.wikidata.org/wiki/Q3532236","display_name":"Scenario testing","level":3,"score":0.56820148229599},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5138657093048096},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.513566255569458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4892103672027588},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.4427911043167114},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43602487444877625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4221016764640808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.287795752286911},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1268598735332489},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc55140.2022.9921981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc55140.2022.9921981","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","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 25th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320314947","display_name":"Institute of Australian Geographers","ror":null},{"id":"https://openalex.org/F4320323141","display_name":"Australian Centre for Field Robotics","ror":"https://ror.org/0384j8v12"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W629029206","https://openalex.org/W2438413413","https://openalex.org/W2513826099","https://openalex.org/W2739735772","https://openalex.org/W2810908953","https://openalex.org/W2896642734","https://openalex.org/W2965452642","https://openalex.org/W2971031619","https://openalex.org/W2983720674","https://openalex.org/W3096585949","https://openalex.org/W3111434224","https://openalex.org/W4285071850","https://openalex.org/W4297781990","https://openalex.org/W4385325965","https://openalex.org/W6620183896","https://openalex.org/W6743333067","https://openalex.org/W6788414202"],"related_works":["https://openalex.org/W426968574","https://openalex.org/W2365639220","https://openalex.org/W2382520895","https://openalex.org/W2393709043","https://openalex.org/W2080567403","https://openalex.org/W2539387137","https://openalex.org/W2374952201","https://openalex.org/W2374808384","https://openalex.org/W2385449752","https://openalex.org/W2619844325"],"abstract_inverted_index":{"Recent":[0],"Autonomous":[1],"Vehicles":[2],"(AV)":[3],"technology":[4],"includes":[5],"machine":[6],"learning":[7],"and":[8,19,25,180],"probabilistic":[9],"techniques":[10],"that":[11,87,108,166],"add":[12],"significant":[13],"complexity":[14],"to":[15,63,78,101,120,146,162,171,186],"the":[16,33,43,51,66,80,84,98,103,148,152,156,188],"traditional":[17],"verification":[18],"validation":[20],"methods.":[21],"The":[22,94],"research":[23],"community":[24],"industry":[26],"have":[27],"widely":[28],"accepted":[29],"scenario-based":[30,72],"testing":[31,135],"in":[32,54,71,92],"last":[34],"few":[35,173],"years.":[36],"As":[37],"it":[38,48,75,117],"is":[39,61,76,100,118],"focused":[40],"directly":[41],"on":[42],"relevant":[44],"crucial":[45],"road":[46],"situations,":[47],"can":[49,88,176],"reduce":[50],"effort":[52],"required":[53],"testing.":[55,73],"Encoding":[56],"real-world":[57,85,111,157],"traffic":[58],"participants'":[59],"behaviour":[60],"essential":[62],"efficiently":[64],"assess":[65],"System":[67],"Under":[68],"Test":[69],"(SUT)":[70],"So,":[74],"necessary":[77],"capture":[79],"scenario":[81,174],"parameters":[82,107,154,175],"from":[83],"data":[86],"model":[89,110],"scenarios":[90,132,149,179],"realistically":[91],"simulation.":[93],"primary":[95],"emphasis":[96],"of":[97,105,126,130],"paper":[99],"identify":[102],"list":[104],"meaningful":[106],"adequately":[109],"lane-change":[112],"scenarios.":[113],"With":[114],"these":[115],"parameters,":[116],"possible":[119],"build":[121],"a":[122,128,168,172],"parameter":[123],"space":[124],"capable":[125],"generating":[127],"range":[129],"challenging":[131],"for":[133],"AV":[134],"efficiently.":[136],"We":[137],"validate":[138],"our":[139],"approach":[140],"using":[141,151],"Root":[142],"Mean":[143],"Square":[144],"Error(RMSE)":[145],"compare":[147],"generated":[150],"proposed":[153],"against":[155],"trajectory":[158],"data.":[159],"In":[160],"addition":[161],"that,":[163],"we":[164],"demonstrate":[165],"adding":[167],"slight":[169],"disturbance":[170],"generate":[177],"different":[178],"utilise":[181],"Responsibility-Sensitive":[182],"Safety":[183],"(RSS)":[184],"metric":[185],"measure":[187],"scenarios'":[189],"risk.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
