About: Fault Injection, Detection and Treatment in Simulated Autonomous Vehicles

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Fault Injection, Detection and Treatment in Simulated Autonomous Vehicles
Creator	Frias, Roberto Castro, Daniel Ferreira, Leonardo Garrido, Daniel Jacob, João
Source	PMC
abstract	In the last few years autonomous vehicles have been on the rise. This increase in popularity lead by new technology advancements and availability to the regular consumer has put them in a position where safety must now be a top priority. With the objective of increasing the reliability and safety of these vehicles, fault detection and treatment modules for autonomous vehicles were developed for an existing multi-agent platform that coordinates them to perform high-level missions. Additionally, a fault injection tool was also developed to facilitate the study of said modules alongside a fault categorization system to help the treatment module select the best course of action. The results obtained show the potential of the developed work, with it being able to detect all the injected faults during the tests in a small enough time frame to be able to adequately treat these faults.
has issue date	2020-05-26(xsd:dateTime)
bibo:doi	10.1007/978-3-030-50371-0_35
has license	no-cc
sha1sum (hex)	2f3310a7ec57c5d9c3845e91a2adf25ab563964f
schema:url	https://doi.org/10.1007/978-3-030-50371-0_35
resource representing a document's title	Fault Injection, Detection and Treatment in Simulated Autonomous Vehicles
has PubMed Central identifier	PMC7302236
schema:publication	Computational Science - ICCS 2020
resource representing a document's body	covid:2f3310a7ec57c5d9c3845e91a2adf25ab563964f#body_text
is schema:about of	named entity 'position' named entity 'This' named entity 'availability' named entity 'Treatment' named entity 'tool' named entity 'reliability' named entity 'time' named entity 'Fault' named entity 'flight simulator' named entity 'FSX' named entity 'FlightGear' named entity 'FSX' named entity 'client-server' named entity 'FSX' named entity 'UAV' named entity 'Aerial Vehicles' named entity 'probability' named entity 'UAV' named entity 'flight simulator' named entity 'intermittent fault' named entity 'landing gear' named entity 'fault injection' named entity 'FSX' named entity 'simple mission' named entity 'UAVs' named entity 'Central Processing Unit' named entity 'fault injection' named entity 'change detection' named entity 'sensor' named entity 'aileron' named entity 'asphalt' named entity 'strange behaviour' named entity 'UAV' named entity 'CPU time' named entity 'graphical interface' named entity 'fault injection' named entity 'Neural Networks' named entity 'analyse the data' named entity 'clustering methods' named entity 'Beechcraft Baron' named entity 'fault injection' named entity 'fault injection' named entity 'UAVs' named entity 'fault injection' named entity 'UAVs' named entity 'UAVs' named entity 'Flight Simulator' named entity 'fault injection' named entity 'United States Air Force' named entity 'UAVs' named entity 'machine learning methods' named entity 'FSX' named entity 'FSX' named entity 'FSX' named entity 'computing' named entity 'FSX' named entity 'make model' named entity 'CPU time' named entity 'solid base' named entity 'UAVs' named entity 'fault injection' named entity 'reaction time' named entity 'fault injection' named entity 'UAV' named entity 'UAV' named entity 'Flight Simulator X' named entity 'UAV' named entity 'reaction time' named entity 'FSX' named entity 'Air Traffic Controller' named entity 'UAVs' named entity 'clustering methods' named entity 'wingspan' named entity 'INJECTION' named entity 'TESTS' named entity 'Fault Injection' covid:arg/2f3310a7ec57c5d9c3845e91a2adf25ab563964f named entity 'VEHICLES' named entity 'TREATMENT'

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