Sensor Fault Detection and Diagnosis for autonomous vehicles
In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long te...
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2015-01-01
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Online Access: | http://dx.doi.org/10.1051/matecconf/20153004003 |
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doaj-39b548d703f74d8db2629a24f8e1b7372021-02-02T02:19:57ZengEDP SciencesMATEC Web of Conferences2261-236X2015-01-01300400310.1051/matecconf/20153004003matecconf_icmset2015_04003Sensor Fault Detection and Diagnosis for autonomous vehiclesRealpe MiguelVintimilla Boris0Vlacic Ljubo1CIDIS - FIEC, Escuela Superior Politecnica del LitoralIntelligent Control Systems Laboratory, Griffith UniversityIn recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.http://dx.doi.org/10.1051/matecconf/20153004003 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Realpe Miguel Vintimilla Boris Vlacic Ljubo |
spellingShingle |
Realpe Miguel Vintimilla Boris Vlacic Ljubo Sensor Fault Detection and Diagnosis for autonomous vehicles MATEC Web of Conferences |
author_facet |
Realpe Miguel Vintimilla Boris Vlacic Ljubo |
author_sort |
Realpe Miguel |
title |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
title_short |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
title_full |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
title_fullStr |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
title_full_unstemmed |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
title_sort |
sensor fault detection and diagnosis for autonomous vehicles |
publisher |
EDP Sciences |
series |
MATEC Web of Conferences |
issn |
2261-236X |
publishDate |
2015-01-01 |
description |
In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor. |
url |
http://dx.doi.org/10.1051/matecconf/20153004003 |
work_keys_str_mv |
AT realpemiguel sensorfaultdetectionanddiagnosisforautonomousvehicles AT vintimillaboris sensorfaultdetectionanddiagnosisforautonomousvehicles AT vlacicljubo sensorfaultdetectionanddiagnosisforautonomousvehicles |
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