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dc.contributor.authorGonzález, Leonardo
dc.contributor.authorMartí, Enrique
dc.contributor.authorCalvo, Isidro
dc.contributor.authorRuiz, Alejandra
dc.contributor.authorPérez, Joshue
dc.date.accessioned2018-10-17T13:25:24Z
dc.date.available2018-10-17T13:25:24Z
dc.date.issued2018
dc.identifier.citationGonzález, Leonardo, Enrique Martí, Isidro Calvo, Alejandra Ruiz, and Joshue Pérez. “Towards Risk Estimation in Automated Vehicles Using Fuzzy Logic.” Lecture Notes in Computer Science (2018): 278–289. doi:10.1007/978-3-319-99229-7_24.en
dc.identifier.isbn978-331999228-0en
dc.identifier.issn0302-9743en
dc.identifier.urihttp://hdl.handle.net/11556/627
dc.description.abstractAs vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen.en
dc.description.sponsorshipThis work was supported by the AMASS project (H2020- ECSEL) with grant agreement number 692474.en
dc.language.isoengen
dc.publisherSpringer Verlagen
dc.titleTowards Risk Estimation in Automated Vehicles Using Fuzzy Logicen
dc.typeconferenceObjecten
dc.identifier.doi10.1007/978-3-319-99229-7_24en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/692474/EU/Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems/AMASSen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsAutomated vehiclesen
dc.subject.keywordsCollision avoidanceen
dc.subject.keywordsFuzzy logicen
dc.subject.keywordsTime-to-collisionen
dc.subject.keywordsDriving behavioren
dc.identifier.essn1611-3349en
dc.journal.titleLecture Notes in Computer Scienceen
dc.page.final289en
dc.page.initial278en
dc.volume.number11094en
dc.identifier.esbn978-3-319-99229-7en
dc.conference.titleASSURE, DECSoS, SASSUR, STRIVE, and WAISE 2018 co-located with 37th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2018; Västerås; Sweden; 18 September 2018 through 21 September 2018en


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