Show simple item record

dc.contributor.authorMatute-Peaspan, Jose A.
dc.contributor.authorMarcano, Mauricio
dc.contributor.authorDiaz, Sergio
dc.contributor.authorZubizarreta, Asier
dc.contributor.authorPerez, Joshue
dc.date.accessioned2020-10-22T10:19:36Z
dc.date.available2020-10-22T10:19:36Z
dc.date.issued2020-10-13
dc.identifier.citationMatute-Peaspan, Jose A., Mauricio Marcano, Sergio Diaz, Asier Zubizarreta, and Joshue Perez. “Lateral-Acceleration-Based Vehicle-Models-Blending for Automated Driving Controllers.” Electronics 9, no. 10 (October 13, 2020): 1674en
dc.identifier.urihttp://hdl.handle.net/11556/1005
dc.description.abstractModel-based trajectory tracking has become a widely used technique for automated driving system applications. A critical design decision is the proper selection of a vehicle model that achieves the best trade-off between real-time capability and robustness. Blending different types of vehicle models is a recent practice to increase the operating range of model-based trajectory tracking control applications. However, current approaches focus on the use of longitudinal speed as the blending parameter, with a formal procedure to tune and select its parameters still lacking. This work presents a novel approach based on lateral accelerations, along with a formal procedure and criteria to tune and select blending parameters, for its use on model-based predictive controllers for autonomous driving. An electric passenger bus traveling at different speeds over urban routes is proposed as a case study. Results demonstrate that the lateral acceleration, which is proportional to the lateral forces that differentiate kinematic and dynamic models, is a more appropriate model-switching enabler than the currently used longitudinal velocity. Moreover, the advanced procedure to define blending parameters is shown to be effective. Finally, a smooth blending method offers better tracking results versus sudden model switching ones and non-blending techniquesen
dc.description.sponsorshipThis research was funded by AUTODRIVE within the Electronic Components and Systems for European Leadership Joint Undertaking (ECSEL JU) in collaboration with the European Union’s H2020 Framework Program (H2020/2014-2020) and National Authorities, under Grant No. 737469en
dc.language.isoengen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleLateral-Acceleration-Based Vehicle-Models-Blending for Automated Driving Controllersen
dc.typejournal articleen
dc.identifier.doi10.3390/electronics9101674en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/737469/EU/Advancing fail-aware, fail-safe, and fail-operational electronic components, systems, and architectures for fully automated driving to make future mobility safer, affordable, and end-user acceptable/AUTODRIVEen
dc.rights.accessRightsopen accessen
dc.subject.keywordsVehicle-model blendingen
dc.subject.keywordsTrajectory trackingen
dc.subject.keywordsModel predictive controlen
dc.subject.keywordsAutomated drivingen
dc.subject.keywordsVehicle controlen
dc.identifier.essn2079-9292en
dc.issue.number10en
dc.journal.titleElectronicsen
dc.page.initial1674en
dc.volume.number9en


Files in this item

Thumbnail

    Show simple item record

    Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International