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In automotive safety, lighting systems play a crucial role. Adaptive Driving Beam (ADB) headlights are at the forefront of this innovation, enhancing visibility for drivers while minimizing glare for oncoming traffic. This article provides an overview of the design and simulation workflows for ADB headlights, specifically how we support virtual design, simulation, analysis, and validation activities for ADB and pixel light headlamps.
Adaptive Driving Beam (ADB) headlights are engineered to dynamically adjust the light distribution to optimize road illumination while avoiding glare for other road users. This technology not only improves road safety but also enhances driver comfort. Designing such advanced systems requires specialized tools and methodologies.
An expanded design toolset is required for the development of ADB or pixel light systems
Synopsys Pixel Light Workflows
Conceptual Pixel Light Driving Simulation
The first workflow shown illustrates the conceptual pixel light driving simulation. This method involves calculating shadow masks based on the bounding boxes of vehicles in a driving simulation. As vehicles move, these bounding boxes change, which requires the light distribution to be dynamically adjusted in real-time.
In LucidDrive, bounding boxes of other motorist stencil masks are calculated, both for the left hand and right-hand lamps. This effectively reduces the intensity within the idealized masked zones to zero.
This approach is excellent for gathering initial requirements and testing basic aspects of pixel light systems. It allows for quick studies on the impact of different angular resolutions and can be simulated on standard computer hardware. However, the accuracy is reduced because it assumes ideal masking, making it unsuitable for final validation.
Masked zones (see aiming wall) are illuminated by one or two lamps, or if both lamps are masked, have no illumination.
Physics-Based Pixel Light Driving Simulation
In contrast, the physics-based pixel light driving simulation offers a more detailed and accurate approach. This method considers each individual source pixel during the driving simulation, providing a precise prediction of optical performance. It is particularly useful for verifying the optical system type and evaluating whether multiple lenses are required.
The simulated light distribution for each individual source pixel is used during the driving simulation. The masked region shown on the aiming wall is not entirely dark anymore. Instead, you can see some illumination caused by Fresnel reflections, aberrations, stray light effects, ghost images from your optical system, impact of coatings, etc.
This level of detail does come with increased demands on computer hardware, often requiring multi-gigabyte memory, a modern CPU and GPU. Despite these challenges, the benefits of accuracy make it well worth it, given that a precise performance prediction becomes possible. Depending on the computer hardware and number of pixels, resolution, etc., the processing of light distributions has been optimized in LucidDrive so that real-time performance suitable for a detailed system validation is still possible.
Designing the Optical System
Field of View and Effective Focal Length
Designing an ADB headlight system starts with defining the field of view and calculating the effective focal length. For instance, using an OSRAM Smartrix HD setup, we can cover a total field of view of 32 degrees horizontally and 8 degrees vertically using two modules. The effective focal length and F-number are critical parameters that influence the light collection efficiency and imaging performance.
Using the OSRAM Smartrix HD Setup (ImageJ. Trommer, T. Feil, D. Weissenberger, R. Fiederling, und M. Rayer, ¡°New Possibilities with ?AFS modules - The Path to High-Resolution Full-Matrix Headlamps,¡± in Proceedings of the 12th International Symposium on Automotive Lighting (ISAL), Vol. 17, 2017, p. 335.) as pixel light source.
Optimization in CODE V
Once the initial parameters are set, the next step involves optimizing the lens design in CODE V. This process includes setting variables, specifying an error function, and defining constraints such as effective focal length and lens thickness. The goal is to achieve the best possible imaging system performance, balancing imaging quality across the entire field of view.
Before and after optimization in CODE V
Simulation in LucidShape
Importing and Setting Up the Model
After designing the optical imaging system in CODE V, the model was imported into LucidShape for illumination simulation. While not automated, this process is straightforward and allows for the creation of materials that match the CODE V definitions. The pixel light source design feature in LucidShape significantly reduces the overhead of defining thousands of light sources individually.
Running the Simulation
The Monte Carlo simulation in LucidShape provides a three-dimensional array of light distributions, containing a layer for each source pixel, capturing non-ideal behaviors such as aberrations and stray light. This detailed simulation allows for early identification of potential design issues, enabling corrective measures before hardware development.
Physics-Based Pixel Light Simulation in LucidShape and pixel resolved illumination distribution.
Example: FMVSS ADB Headlight Glare Evaluation
To demonstrate the practical application of these workflows, we conducted an FMVSS ADB headlight glare evaluation. This involved defining a test track with specific sensor positions and running a dynamic driving simulation in LucidDrive. The sensor capabilities in LucidDrive allowed for quantitative assessment of illumination, ensuring compliance with regulatory requirements.
LucidDrive recently introduced a sensor capability that makes it possible to assess the illumination quantitatively now also during or after a driving simulation. Here, various sensors are recording the illumination of the respective sensors over time. This is done to assess glare for the FMVSS 108 ADB test.
Conclusion
Designing ADB headlights is a complex task that requires a combination of advanced tools and methodologies. From initial conceptual simulations to detailed physics-based analyses, each step is crucial for developing a safe and effective lighting system. By leveraging tools like CODE V, LucidShape, and LucidDrive, engineers can design, analyze, and validate ADB systems with high precision.
In conclusion, the workflows and tools discussed in this article offer a comprehensive approach to designing adaptive driving beam headlights, contributing to safer roads and enhanced driver experience.
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