A python library that aims to simulate failures that may occur in a camera during the acquisition/processing phase.

To support the definition of safe and robust vehicle architectures and intelligent systems, we define the failures model of a vehicle camera, together with an analysis of effects and known mitigations. As a natural consequence, here we present a software library for the generation of the corresponding failed images. These images are then fed the trained agent of an autonomous driving simulator: the misbehavior of the trained agent allows a better understanding of failures effects and especially of the resulting safety risk. 

Some examples of the failures injected:

Github is available at: https://github.com/francescosecci/Python_Image_Failures

More information:

• Thesis of Francesco Secci, "On failures of RGB cameras and their effects in autonomous driving applications", Master Thesis at the University of Florence, Italy (in Italian only), July 2020. Supervisor: Andrea Ceccarelli (link to thesis page)
• Paper: Francesco Secci, Andrea Ceccarelli, "On failures of RGB cameras and their effects in autonomous driving applications", in press -- to appear at the 31st International Symposium on Software Reliability Engineering (ISSRE 2020), available on arXiv