Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29785
DC FieldValueLanguage
dc.contributor.authorBifulco, Gennaro Nicola-
dc.contributor.authorCoppola, Angelo-
dc.contributor.authorLoizou, Savvas-
dc.contributor.authorPetrillo, Alberto-
dc.contributor.authorSantini, Stefania-
dc.date.accessioned2023-07-11T10:58:28Z-
dc.date.available2023-07-11T10:58:28Z-
dc.date.issued2021-09-07-
dc.identifier.citation21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021, Bari, 7 - 10 September 2021en_US
dc.identifier.isbn9781665436120-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/29785-
dc.description.abstractThis paper addresses the problem of computing an eco-driving speed profile for an autonomous electric vehicle traveling along curvy roads while ensuring path following/car following functionalities w.r.t. possible preceding vehicles ahead. To solve it, we propose a double-layer control architecture combining the classical Adaptive Cruise Control with a Nonlinear Model Predictive Control. This latter is designed so to drive the autonomous vehicle along a predefined path while guaranteeing the maintenance of a safe distance w.r.t. a predecessor vehicle ahead and ensuring energy-saving consumption. The appraised control-oriented design model is non-linear and the energy consumption one explicitly accounts for the cornering effects. Numerical results confirm the effectiveness of the proposed control architecture and disclose its ability in guaranteeing energy saving.en_US
dc.language.isoenen_US
dc.rights© Elsevier B.V.en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAutonomous Vehicleen_US
dc.subjectEco-Drivingen_US
dc.subjectElectric Vehicleen_US
dc.subjectModel Predictive Controlen_US
dc.subjectPath Followingen_US
dc.titleCombined Energy-oriented Path following and Collision Avoidance approach for Autonomous Electric Vehicles via Nonlinear Model Predictive Controlen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Naples Federico IIen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryItalyen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.relation.conference21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021en_US
dc.identifier.doi10.1109/EEEIC/ICPSEurope51590.2021.9584501en_US
dc.identifier.scopus2-s2.0-85126432761-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85126432761-
cut.common.academicyear2021-2022en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Mechanical Engineering and Materials Science and Engineering-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4083-9946-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
CORE Recommender
Show simple item record

SCOPUSTM   
Citations

5
checked on Nov 6, 2023

Page view(s)

135
Last Week
0
Last month
0
checked on Nov 6, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons