Smart Headlights with Coaxial Integration of LiDAR and Radar Sensing

Increasing complexity of driving environments requires advanced sensing technologies to enhance vehicle safety and automation. Our study presents the design and implementation of a smart car headlight demonstrator that integrates LiDAR and radar sensing modules in a compact, coaxial configuration alongside low- and adaptive driving beam functionalities. The lighting modules are based on maskless double-sided microlens arrays, which provide a compact yet efficient solution capable of achieving the required beam brightness despite losses incurred by the combiners. By embedding the sensing path coaxially with the lighting beams, we aim to streamline overall design and improve overall system compactness and efficiency while allowing for high design freedom in the aesthetic appearance of the headlight. The integration is achieved using a dichroic combiner that effectively overlaps visible and near-infrared light beam paths, allowing for seamless operation of the LiDAR system in conjunction with lighting functions. Furthermore, a second combiner is employed to coaxially overlap fields of view of LiDAR and visible light with the radar's microwave radiation. A wavelength range of four orders of magnitude (nm to mm) must be covered. Two methods have been researched: an anti-reflective thin film coating with a transparent conductive oxide as high-refractive index component, and a laser structured opaque silver coating. In both cases a high transparency for visible and infrared light as well as a high reflectivity for microwave radiation has been achieved. Our design adheres to aesthetic and functional automotive standards. The successful integration of these sensing technologies into a single headlight unit represents a significant step forward in automotive design, offering potential pathways for future research and development in smart vehicle systems. This work highlights the potential of integrating multiple sensing technologies within a constrained space, paving the way for enhanced vehicle intelligence and improved safety features in autonomous driving applications.