Sensor fault detection and diagnosis for autonomous vehicles
Abstract:
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.
Año de publicación:
2015
Keywords:
Fuente:
Tipo de documento:
Conference Object
Estado:
Acceso abierto
Áreas de conocimiento:
- Ciencias de la computación
Áreas temáticas:
- Otras ramas de la ingeniería