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:

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    scopusscopus

    Tipo de documento:

    Conference Object

    Estado:

    Acceso abierto

    Áreas de conocimiento:

    • Ciencias de la computación

    Áreas temáticas:

    • Otras ramas de la ingeniería