dc.rights.license | Attribution 4.0 International | * |
dc.contributor.author | Gorospe, Joseba | |
dc.contributor.author | Alonso Gómez, Arrate | |
dc.contributor.other | Hasan, Shahriar | |
dc.contributor.other | Girs, Svetlana | |
dc.contributor.other | Uhlemann, Elisabeth | |
dc.date.accessioned | 2024-10-21T08:31:57Z | |
dc.date.available | 2024-10-21T08:31:57Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 2687-7813 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=172977 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/6673 | |
dc.description.abstract | Platooning is highly tractable for enabling fuel savings for autonomous and semi-autonomous cars and trucks. Safety concerns are one of the main impediments that need to be overcome before vehicle platoons can be deployed on ordinary roads despite their readily available technical feasibility. Simulation studies remain vital for evaluating platoon safety applications primarily due to the high cost of field tests. To this end, we present PlatoonSAFE, an open-source simulation tool that promotes the simulation studies of fault tolerance in platooning by enabling the monitoring of transient communication outages during runtime and assigning an appropriate performance level as a function of the instantaneous communication quality. In addition, PlatoonSAFE facilitates the simulation of several emergency braking strategies to evaluate their efficacy in transitioning a platoon to a fail-safe state. Furthermore, two Machine Learning (ML) models are integrated into PlatoonSAFE that can be employed as an onboard prediction tool in the platooning vehicles to facilitate online training of ML models and real-time prediction of communication, network, and traffic parameters. In this paper, we present the PlatoonSAFE structure, its features and implementation details, configuration parameters, and evaluation metrics required to evaluate the fault tolerance of platoon safety applications. | en |
dc.language.iso | eng | en |
dc.publisher | IEEE | en |
dc.rights | © 2023 The Authors | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Safety | en |
dc.subject | transient analysis | en |
dc.subject | fault tolerant systems | en |
dc.subject | predictive model | en |
dc.subject | cooperative systems | en |
dc.subject | connected vehicles | en |
dc.subject | discrete-event systems | en |
dc.subject | Machine learning | en |
dc.title | PlatoonSAFE: An Integrated Simulation Tool for Evaluating Platoon Safety | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | IEEE Open Journal of Intelligent Transportation SystemsOpen Access | en |
local.contributor.group | Teoría de la señal y comunicaciones | es |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 325 | en |
local.description.publicationlastpage | 347 | en |
local.identifier.doi | https://doi.org/10.1109/OJITS.2023.3271608 | en |
local.contributor.otherinstitution | https://ror.org/033vfbz75 | |
local.source.details | Vol. 4 | |
oaire.format.mimetype | application/pdf | en |
oaire.file | $DSPACE\assetstore | en |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | en |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | en |
oaire.funderName | Comisión Europea | en |
oaire.funderName | Gobierno Vasco | en |
oaire.funderName | Gobierno Vasco | en |
oaire.funderIdentifier | https://ror.org/00k4n6c32 / http://data.crossref.org/fundingdata/funder/10.13039/501100000780 | en |
oaire.funderIdentifier | https://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086 | en |
oaire.funderIdentifier | https://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086 | en |
oaire.fundingStream | H2020 | en |
oaire.fundingStream | Ikertalde Convocatoria 2022-2023 | en |
oaire.fundingStream | Elkartek 2021 | en |
oaire.awardNumber | 764951 | en |
oaire.awardNumber | IT1451-22 | en |
oaire.awardNumber | KK-2021-00123 | en |
oaire.awardTitle | Immersive Visual Technologies for Safety-critical Applications (ImmerSAFE) | en |
oaire.awardTitle | Sin información | en |
oaire.awardTitle | Evolución tecnológica para la automatización multivehicular y evaluación de funciones de conducción altamente automatizadas (AUTOEV@L) | en |
oaire.awardURI | https://doi.org/10.3030/764951 | en |
oaire.awardURI | Sin información | en |
oaire.awardURI | Sin información | en |