Material-Based Illumination Optimization for Computer Vision in Automated Driving

The contribution at hand presents and evaluates a novel matrix headlamp lighting distribution optimized for computer vision and energy consumption, thus enhancing automated vehicles' safety through an improved perception. The light distribution considers the materials of the environment to illuminate each material selectively with a different intensity. The simulative results show that today's real light distributions are inefficient for automated driving and that the proposed material-based illumination can enhance the detection quality by over 80% while saving energy simultaneously, outperforming real and homogenous light distributions.