{"id":"https://openalex.org/W2017205399","doi":"https://doi.org/10.1109/itsc.2014.6957721","title":"Risk assessment for Collision Avoidance Systems","display_name":"Risk assessment for Collision Avoidance Systems","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2017205399","doi":"https://doi.org/10.1109/itsc.2014.6957721","mag":"2017205399"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2014.6957721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2014.6957721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"17th International IEEE 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/A5074542849","display_name":"Adam Houenou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adam Houenou","raw_affiliation_strings":["Sherpa Engineering (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sherpa Engineering (France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050418541","display_name":"Philippe Bonnifait","orcid":"https://orcid.org/0000-0002-5842-1399"},"institutions":[{"id":"https://openalex.org/I102516824","display_name":"Universit\u00e9 de Technologie de Compi\u00e8gne","ror":"https://ror.org/04y5kwa70","country_code":"FR","type":"education","lineage":["https://openalex.org/I102516824"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210088387","display_name":"Heuristics and Diagnostics for Complex Systems","ror":"https://ror.org/0075hvk77","country_code":"FR","type":"facility","lineage":["https://openalex.org/I102516824","https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210088387","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Philippe Bonnifait","raw_affiliation_strings":["Heudiasyc UMR CNRS 7253, University of Technology of Compiegne, France","Heudiasyc UMR CNRS 7253, University of Technology of Compi\u00e8gne (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heudiasyc UMR CNRS 7253, University of Technology of Compiegne, France","institution_ids":["https://openalex.org/I4210088387","https://openalex.org/I102516824","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Heudiasyc UMR CNRS 7253, University of Technology of Compi\u00e8gne (France)","institution_ids":["https://openalex.org/I102516824","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107726313","display_name":"V\u00e9ronique Cherfaoui","orcid":null},"institutions":[{"id":"https://openalex.org/I102516824","display_name":"Universit\u00e9 de Technologie de Compi\u00e8gne","ror":"https://ror.org/04y5kwa70","country_code":"FR","type":"education","lineage":["https://openalex.org/I102516824"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210088387","display_name":"Heuristics and Diagnostics for Complex Systems","ror":"https://ror.org/0075hvk77","country_code":"FR","type":"facility","lineage":["https://openalex.org/I102516824","https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210088387","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Veronique Cherfaoui","raw_affiliation_strings":["Heudiasyc UMR CNRS 7253, University of Technology of Compiegne, France","Heudiasyc UMR CNRS 7253, University of Technology of Compi\u00e8gne (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heudiasyc UMR CNRS 7253, University of Technology of Compiegne, France","institution_ids":["https://openalex.org/I4210088387","https://openalex.org/I102516824","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Heudiasyc UMR CNRS 7253, University of Technology of Compi\u00e8gne (France)","institution_ids":["https://openalex.org/I102516824","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"386","last_page":"391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","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/T12814","display_name":"Gaussian Processes and Bayesian Inference","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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9958000183105469,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9930999875068665,"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/collision","display_name":"Collision","score":0.7567808628082275},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7161628007888794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6593160629272461},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.6203271746635437},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47972622513771057},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4141732454299927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2750694453716278},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13402444124221802}],"concepts":[{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.7567808628082275},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7161628007888794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593160629272461},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.6203271746635437},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47972622513771057},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4141732454299927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2750694453716278},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13402444124221802},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2014.6957721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2014.6957721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"17th International IEEE Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1746819321","https://openalex.org/W1974042363","https://openalex.org/W2055556996","https://openalex.org/W2069544315","https://openalex.org/W2079150870","https://openalex.org/W2080803848","https://openalex.org/W2084835622","https://openalex.org/W2116565126","https://openalex.org/W2119862366","https://openalex.org/W2151910862","https://openalex.org/W2167293612","https://openalex.org/W4211049957","https://openalex.org/W6629804754"],"related_works":["https://openalex.org/W4317634134","https://openalex.org/W2981729160","https://openalex.org/W4310743282","https://openalex.org/W2743212448","https://openalex.org/W2889566344","https://openalex.org/W1819938260","https://openalex.org/W2340892746","https://openalex.org/W3163022373","https://openalex.org/W3005999311","https://openalex.org/W2357101623"],"abstract_inverted_index":{"Collision":[0],"Avoidance":[1],"Systems":[2],"need":[3],"to":[4,13,28,42,86,100,137,160,213,222,225],"perform":[5],"scene":[6,25,220],"analysis":[7,26],"and":[8,168,221,237],"risk":[9,52,140,204],"assessment":[10],"in":[11],"order":[12],"react":[14,223],"conveniently.":[15],"Based":[16],"on":[17,55,103],"the":[18,22,30,33,38,43,47,51,56,104,114,120,124,132,139,144,162,165,169,184,200,203,211,219,226,238],"information":[19],"provided":[20],"by":[21,127],"perception":[23],"system,":[24],"has":[27,99,231],"predict":[29],"evolution":[31],"of":[32,46,53,80,119,123,131,141,143,183,202,205,218,240],"current":[34,121],"driving":[35],"situation":[36],"for":[37],"near":[39],"future.":[40],"Thanks":[41],"predicted":[44,66,93,106,133],"trajectories":[45],"relevant":[48],"traffic":[49],"participants,":[50],"collision":[54,142,173,193,206],"ego":[57,125,145,166],"vehicle":[58,126,146,167],"can":[59],"be":[60,101],"calculated.":[61],"In":[62],"many":[63],"cases,":[64],"a":[65,78,87,110,148,156,175,191,197,215],"trajectory":[67,94],"is":[68,75,188,207,242],"not":[69],"defined":[70],"with":[71,147,234],"explicit":[72],"equations":[73],"but":[74],"given":[76,176],"as":[77,190],"set":[79],"sampled":[81],"poses,":[82],"each":[83],"one":[84],"corresponding":[85],"different":[88],"future":[89,177],"time":[90,178,182,194],"instant.":[91,179],"A":[92],"being":[95],"always":[96],"uncertain,":[97],"confidence":[98],"estimated":[102],"so":[105,195],"poses.":[107],"We":[108],"present":[109],"method":[111],"that":[112,164,196],"propagates":[113],"known":[115],"error":[116],"covariance":[117],"matrix":[118],"pose":[122],"considering":[128],"local":[129],"approximations":[130],"trajectory.":[134],"This":[135,209],"allows":[136,210],"estimate":[138],"considered":[149,189],"target":[150],"object.":[151],"The":[152,228],"proposed":[153],"approach":[154,230],"uses":[155],"Monte":[157],"Carlo":[158],"simulation":[159],"approximate":[161],"probability":[163],"object":[170],"come":[171],"into":[172],"at":[174],"Each":[180],"sample":[181],"whole":[185],"prediction":[186],"horizon":[187],"potential":[192],"curve":[198],"describing":[199],"variation":[201],"obtained.":[208],"system":[212],"have":[214],"better":[216],"comprehension":[217],"proportionally":[224],"threat.":[227],"overall":[229],"been":[232],"tested":[233],"simulated":[235],"data":[236],"consistency":[239],"results":[241],"shown.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}