MATEC Web of Conferences
Volume 30, 20152015 the 4th International Conference on Material Science and Engineering Technology (ICMSET 2015)
|Number of page(s)||6|
|Section||Mechanical design and manufacturing|
|Published online||04 November 2015|
Sensor Fault Detection and Diagnosis for autonomous vehicles
1 Intelligent Control Systems Laboratory, Griffith University, Brisbane Australia
2 CIDIS - FIEC, Escuela Superior Politecnica del Litoral, Guayaquil, Ecuador
a Corresponding author: email@example.com
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.
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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