Simulation of High-Definition Pixel-Headlights

Waldner, Mirko; Bertram, Torsten

doi:10.1007/978-3-030-64556-4_45

Cited by 2 publications

(1 citation statement)

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“…The matrix headlight is simulated in real time [16] using Compressed Sparse Row (CSR) sparse matrix vector multiplication with CUDA [17,18] on a graphic card (GPU) and controlled using the Super Sampling Control (SSC) approach [6,19]. SSC computes the optimal utilization of all pixels starting from 3D target objects called primitives, e.g.…”

Section: Selective 3d Illumination Of Objectsmentioning

confidence: 99%

Energy-Efficient Illumination by Matrix Headlamps for Nighttime Automated Object Detection

Waldner

Müller

Bertram

2022

IJECER

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The contribution at hand presents a novel approach to generate dynamic energy-optimized illumination by matrix headlamps designed for automated driving. The approach consists of a novel basic minimal illumination adapted to the current road environment with minimum brightness and a light pixel control strategy to adjust the illumination of potential objects uniformly and selectively only. The approach was developed and optimized by considering the impact of other lighting functions such as Glare-Free High Beam and marker light on the quality of object detection and possible alternatives such as symbol projection with structured light. The concept achieves a similar quality of object detection as conventional high beam, but requires only around 16% of the energy. This shows the energy saving potential of automated vehicles in combination with novel headlight control strategies.

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Section: Selective 3d Illumination Of Objectsmentioning

confidence: 99%