My Comfort is your Safety - Head-Up Displays in Automotive Design

Optical Solutions Editorial Team

Jan 27, 2025 / 4 min read

Head-Up Displays (HUDs) have revolutionized the automotive industry by enhancing driver safety and convenience. By projecting essential information onto the windshield, HUDs allow drivers to maintain focus on the road without having to glance down at the instrument cluster. CODE V and LucidShape CAA V5 Based are used to design, simulate, and visualize HUDs, ensuring optimal performance and driver satisfaction.


Motivation and Advantages of HUDs

The primary goal of a Head-Up Display (HUD) is to project information onto the windshield as a virtual image a few meters in front of the car. This technology offers significant advantages over traditional instrument cluster displays. Firstly, it allows drivers to keep their heads up and their eyes on the road, reducing the risk of accidents caused by distraction. Secondly, the virtual image requires less accommodation from the eye, reducing stress and fatigue during long drives. By enhancing the driver's field of view with crucial information, HUDs contribute to a safer and more comfortable driving experience.

Example of a Head-Up Display (HUD) on a windshield | Synopsys

Example of a Head-Up Display (HUD) on a windshield

Designing and Optimizing HUDs with Synopsys Solutions

HUD Design with CODE V

CODE V is a sequential ray tracing software that plays a crucial role in the optical design of HUDs. It defines the ray path as a sequence of surfaces, making it ideal for designing imaging optics. In the context of HUDs, CODE V is primarily used for mirror design. The software allows for the optimization of freeform mirrors by defining various variables and minimizing aberrations. Additionally, CODE V provides essential analysis tools, such as distortion grids, point spread functions, and spot diagrams, to ensure the highest quality of the optical system.

Use CODE V to model and optimize an imaging system that includes freeform mirrors | Synopsys

Use CODE V to model and optimize an imaging system that includes freeform mirrors

While CODE V excels in many areas, for more advanced stray light analysis and ghost image simulation, Synopsys offers LucidShape CAA V5 Based. This tool allows for comprehensive path definition and incorporates scattering properties, providing enhanced simulation and testing capabilities.

Simulation and Testing with LucidShape CAA V5 Based

LucidShape CAA V5 Based is a non-sequential ray tracing software that complements CODE V by offering comprehensive simulation capabilities. It uses a Monte Carlo algorithm to simulate all paths at once, allowing for more accurate and detailed analysis. This software is particularly useful for designing and testing the housing of HUDs, which can be added in CATIA. One of the standout features of LucidShape is its backward simulation capability, where rays are launched from the luminance camera sensor to the Picture Generation Unit (PGU), ensuring precise and much faster results.

LucidShape CAA V5 Based offers advanced non-sequential raytracing with Monte Carlo algorithms, simultaneous path simulation, CATIA housing integration, backward simulation from luminance camera to PGU, and GPU simulation support. | Synopsys

LucidShape CAA V5 Based offers advanced non-sequential raytracing with Monte Carlo algorithms, simultaneous path simulation, CATIA housing integration, backward simulation from luminance camera to PGU, and GPU simulation support

LucidShape also excels in homogeneity checks and ghost image simulations. Advanced analysis tools allow for custom measurement areas and various calculations to ensure uniformity across the display. Additionally, the software can simulate chromatic homogeneity and compare results against regulatory standards. 

Ghost images and chromatic homogeneity can also be evaluated in LucidShape CAA V5 Based | Synopsys

Ghost images and chromatic homogeneity can also be evaluated in LucidShape CAA V5 Based

Realistic Rendering (Visualization) in LucidShape CAA V5 Based

For realistic rendering, LucidShape CAA V5 Based uses HDR files to create environment light sources, providing photorealistic visualizations that help designers evaluate the final product under different lighting conditions.

Photorealistic render of a light source superimposed on an outside environment in LucidShape CAA V5 Based | Synopsys

Photorealistic render of a light source superimposed on an outside environment
in LucidShape CAA V5 Based

PGU (Picture Generation Unit) and environment light sources can be superimposed and controlled individually to change either environmental conditions, or the HUD brightness. Human Eye Vision Image (HEVI) permits to visualize a simulation result as if we would be looking at it with our own eyes: scale is adapted to fit the eyes’ dynamic, and some physiological effects can be added, like the glare, when a bright light source is observed in a dark environment.

The HEVI (Human Eye Vision Image) tool in LucidShape CAA V5 Based shows a photorealistic rendering. | Synopsys

Photorealistic render of a light source superimposed on an outside environment
in LucidShape CAA V5 Based

With panoramas, you are able to simulate different driver’s positions at once, as if the driver’s eye would be moving inside the defined eyebox. That permits to analyze effects like vignetting.

From the original Luminance Camera Sensor, a panorama can be created in LucidShape CAA V5 Based | Synopsys

From the original Luminance Camera Sensor, a panorama can be created in LucidShape CAA V5 Based

HEVI Scale, without glare, some vignetting in some areas of the eyebox. | Synopsys

HEVI Scale, without glare, some vignetting in some areas of the eyebox

Conclusion

Synopsys solutions, including CODE V and LucidShape CAA V5 Based, provide a comprehensive suite of tools for designing, simulating, and visualizing Head-Up Displays in automotive design. By leveraging these advanced technologies, automotive engineers can create HUDs that enhance driver safety, reduce fatigue, and improve the overall driving experience. 

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