SOLAS: Superpositioning an Optical Lens in Automotive Simulation
Journal:
arXiv
Published Date:
Jan 16, 2025
Abstract
Automotive Simulation is a potentially cost-effective strategy to identify
and test corner case scenarios in automotive perception. Recent work has shown
a significant shift in creating realistic synthetic data for road traffic
scenarios using a video graphics engine. However, a gap exists in modeling
realistic optical aberrations associated with cameras in automotive simulation.
This paper builds on the concept from existing literature to model optical
degradations in simulated environments using the Python-based ray-tracing
library KrakenOS. As a novel pipeline, we degrade automotive fisheye simulation
using an optical doublet with +/-2 deg Field of View (FOV), introducing
realistic optical artifacts into two simulation images from SynWoodscape and
Parallel Domain Woodscape. We evaluate KrakenOS by calculating the Root Mean
Square Error (RMSE), which averaged around 0.023 across the RGB light spectrum
compared to Ansys Zemax OpticStudio, an industrial benchmark for optical design
and simulation. Lastly, we measure the image sharpness of the degraded
simulation using the ISO12233:2023 Slanted Edge Method and show how both
qualitative and measured results indicate the extent of the spatial variation
in image sharpness from the periphery to the center of the degradations.
