Name
Abstract | ||
|---|---|---|
Autonomous Vehicles should transform the urban transport scenario. However, to be able to navigate completely autonomously, they also need to deal with faults that its components are subject to. Therefore, Health Monitoring System, is a component of the autonomous system which constantly monitor the integrity of those components, so that safety measures are taken as soon as an abnormal condition is detected. This paper presents a Health Monitoring System using Component-based Hierarchical approach and Hybrid Bayesian Networks with Residue Evidence for Fault Detection and Diagnosis in lateral and longitudinal controllers, and also in the GPS sensor. Finally, the results demonstrated the reliability of the proposed methods for Fault Detection and Diagnosis, and also highlighted the importance of safety protocols for Autonomous Vehicles. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICAR46387.2019.8981565 | 2019 19th International Conference on Advanced Robotics (ICAR) |
Keywords | Field | DocType |
hybrid Bayesian network,autonomous vehicle,urban transport scenario,health monitoring system,autonomous system,fault detection,component-based hierarchical approach,residue evidence,fault diagnosis,longitudinal controllers,GPS sensor,safety protocols | Monitoring system,Fault detection and isolation,Real-time computing,Atmospheric sciences,Bayesian network,Global Positioning System,Autonomous system (mathematics),Physics | Conference |
ISBN | Citations | PageRank |
978-1-7281-2468-1 | 0 | 0.34 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iago Pachêco Gomes | 1 | 0 | 0.34 |
| Denis Fernando Wolf | 2 | 47 | 9.86 |