A Fault Tolerant Architecture for Data Fusion Targeting Hardware and Software Faults

Bader, Kaci; Lussier, Benjamin; Schön, Walter

doi:10.1109/prdc.2014.9

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…The most common strategy for error detection in the sensor inputs of autonomous vehicles is based on duplication and comparison approaches and the use of belief functions, as defined by Smets in his Transferable Belief Model (TMB) [ 27 ]; i.e., assembling redundant localization algorithms aiming to compare the different outputs and expose the failing sensor or algorithm. Examples of such approaches can be found in [ 28 , 29 ], where redundant information is used to detect corrupted or erroneous data and obtain control signals that are further fused in a Kalman filter. Self-assessing Bayesian filters have also been proposed to merge different information sources and improve the robustness, as they implement an error detection system [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

A Reconfigurable Framework for Vehicle Localization in Urban Areas

Viana¹,

Díez²

2022

Sensors

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Accurate localization for autonomous vehicle operations is essential in dense urban areas. In order to ensure safety, positioning algorithms should implement fault detection and fallback strategies. While many strategies stop the vehicle once a failure is detected, in this work a new framework is proposed that includes an improved reconfiguration module to evaluate the failure scenario and offer alternative positioning strategies, allowing continued driving in degraded mode until a critical failure is detected. Furthermore, as many failures in sensors can be temporary, such as GPS signal interruption, the proposed approach allows the return to a non-fault state while resetting the alternative algorithms used in the temporary failure scenario. The proposed localization framework is validated in a series of experiments carried out in a simulation environment. Results demonstrate proper localization for the driving task even in the presence of sensor failure, only stopping the vehicle when a fully degraded state is achieved. Moreover, reconfiguration strategies have proven to consistently reset the accumulated drift of the alternative positioning algorithms, improving the overall performance and bounding the mean error.

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Section: Introductionmentioning

confidence: 99%

A Reconfigurable Framework for Vehicle Localization in Urban Areas

Viana¹,

Díez²

2022

Sensors

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“…Estos modelos consisten en diseñar una estructura con módulos de localización redundantes que comparan entre sí sus estimaciones para desenmascarar posibles errores, y poder así discriminarlos para evitar una propagación del error en el posicionamiento. [7] y [9] ofrecen ejemplos de aplicación para estos modelos, donde se usa información redundante para detectar fuentes erróneas antes de fusionarlas en un filtro de Kalman. Aun así, estos enfoques suelen centrarse solamente en la detección de errores, y en contadas ocasiones abordan la problemática de desarrollar alternativas de posicionamiento realmente precisas.…”

Section: Introductionunclassified

Fusión de sensores para la localización robusta de vehículos autónomos en áreas urbanas

Viana¹,

Díez²

2021

Xlii Jornadas De Automática : Libro De Actas

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El posicionamiento por GPS en zonas urbanas densamente pobladas puede ser un reto, principalmente debido al bloqueo de señales por edificios o túneles. Es por ello que los vehículos autónomos necesitan implementar alternativas para estas situaciones mediante una estructura de localización tolerante a fallos. Este es un área de gran interés en la que predominan el uso de técnicas de duplicación-comparación en combinación con las belief function, además de técnicas de localización alternativas. Este trabajo propone una estructura de localización para zonas urbanas densamente pobladas que incluye tanto un algoritmo robusto de detección de errores, capaz de evaluar el rango de confianza de cada estimación, como una precisa técnica de localización alternativa basada en un algoritmo de map matching de bajo coste computacional. La validación en un entorno simulado ha verificado la funcionalidad de la propuesta.

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“…Each observer is driven by all inputs and all but one output to diagnose a sensor fault. Additionally, in the very recent work from [21][22][23], the EKF is used to calculate the measurement probability distribution of the intelligent vehicle position for nonlinear models driven by Gaussian noise. Using the probability distribution of innovation obtained from EKF, it is possible to test if the measured data are fit with the models.…”

Section: Introductionmentioning

confidence: 99%

Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

Huang

2015

International Journal of Navigation and Observation

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This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with advanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information about the vehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed FDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies a generalized observer scheme (GOS). In the GOS, there is bank of extended Kalman filters (EKFs), each excited by all except one sensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults but one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The designed FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with diagnosing individual sensor faults and outputting fault-free vehicle states.

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A Fault Tolerant Architecture for Data Fusion Targeting Hardware and Software Faults

Cited by 5 publications

References 24 publications

A Reconfigurable Framework for Vehicle Localization in Urban Areas

A Reconfigurable Framework for Vehicle Localization in Urban Areas

Fusión de sensores para la localización robusta de vehículos autónomos en áreas urbanas

Design of a Fault Detection and Isolation System for Intelligent Vehicle Navigation System

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