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RGB cameras are one of the most relevant sensors for autonomous drivingapplications. It is undeniable that failures of vehicle cameras may compromisethe autonomous driving task, possibly leading to unsafe behaviors when imagesthat are subsequently processed by the driving system are altered. To supportthe definition of safe and robust vehicle architectures and intelligentsystems, in this paper we define the failure modes of a vehicle camera,together with an analysis of effects and known mitigations. Further, we build asoftware library for the generation of the corresponding failed images and wefeed them to six object detectors for mono and stereo cameras and to theself-driving agent of an autonomous driving simulator. The resultingmisbehaviors with respect to operating with clean images allow a betterunderstanding of failures effects and the related safety risks in image-basedapplications.

RGB cameras failures and their effects in autonomous driving applications