Title
PlatoonSAFE: An Integrated Simulation Tool for Evaluating Platoon Safetyxmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
https://ror.org/033vfbz75Version
http://purl.org/coar/version/c_970fb48d4fbd8a85
Rights
© 2023 The AuthorsAccess
http://purl.org/coar/access_right/c_abf2Publisher’s version
https://doi.org/10.1109/OJITS.2023.3271608Published at
IEEE Open Journal of Intelligent Transportation SystemsOpen Access Vol. 4xmlui.dri2xhtml.METS-1.0.item-publicationfirstpage
325xmlui.dri2xhtml.METS-1.0.item-publicationlastpage
347Publisher
IEEEKeywords
Safety
transient analysis
fault tolerant systems
predictive model ... [+]
transient analysis
fault tolerant systems
predictive model ... [+]
Safety
transient analysis
fault tolerant systems
predictive model
cooperative systems
connected vehicles
discrete-event systems
Machine learning [-]
transient analysis
fault tolerant systems
predictive model
cooperative systems
connected vehicles
discrete-event systems
Machine learning [-]
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 pla ... [+]
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. [-]
xmlui.dri2xhtml.METS-1.0.item-oaire-funderName
Comisión EuropeaGobierno Vasco
Gobierno Vasco
xmlui.dri2xhtml.METS-1.0.item-oaire-fundingStream
H2020Ikertalde Convocatoria 2022-2023
Elkartek 2021
xmlui.dri2xhtml.METS-1.0.item-oaire-awardNumber
764951IT1451-22
KK-2021-00123
xmlui.dri2xhtml.METS-1.0.item-oaire-awardURI
https://doi.org/10.3030/764951Sin información
Sin información
xmlui.dri2xhtml.METS-1.0.item-oaire-awardTitle
Immersive Visual Technologies for Safety-critical Applications (ImmerSAFE)Sin información
Evolución tecnológica para la automatización multivehicular y evaluación de funciones de conducción altamente automatizadas (AUTOEV@L)
Collections
- Articles - Engineering [684]
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