  We describe an open-source simulator that creates sensor irradiance and
sensor images of typical automotive scenes in urban settings. The purpose of
the system is to support camera design and testing for automotive applications.
The user can specify scene parameters (e.g., scene type, road type, traffic
density, time of day) to assemble a large number of random scenes from graphics
assets stored in a database. The sensor irradiance is generated using
quantitative computer graphics methods, and the sensor images are created using
image systems sensor simulation. The synthetic sensor images have pixel level
annotations; hence, they can be used to train and evaluate neural networks for
imaging tasks, such as object detection and classification. The end-to-end
simulation system supports quantitative assessment, from scene to camera to
network accuracy, for automotive applications.
