Automotive Lighting Luminance Mapping for Adaptive Beam Projection
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Solution Overview
Problem
Existing digital automotive lighting devices struggle to dynamically adapt light patterns to account for various environmental and situational factors, including reflections and refractions caused by climate conditions and other vehicles, leading to suboptimal lighting.
Innovation Solution
A method utilizing a control unit trained with machine learning algorithms to transform image data into a luminance map and calculate an adapted light pattern, considering road and environmental conditions, projected by a matrix arrangement of solid-state light sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed light pattern is projected without environmental adaptation, then the lighting device structure remains simple, but the lighting effectiveness and safety are suboptimal due to inability to account for reflections and refractions from climate conditions and other vehicles
Solution Approach 1:
The system captures images of the working zone, transforms them into luminance maps, and uses these maps to calculate adapted light patterns that account for environmental factors like reflections and refractions. This feedback loop continuously adjusts the light pattern based on real-time conditions, improving lighting effectiveness while managing system complexity through algorithmic processing.
Solution Approach 2:
The patent replaces complex mechanical or optical adaptive systems with a computational approach using image processing algorithms and machine learning. The control unit processes images and calculates adapted light patterns through software, avoiding the need for complex mechanical adjustment mechanisms while achieving adaptive lighting.
2Adaptability or versatility
If environmental factors and climate conditions are considered in light pattern calculation, then the lighting adaptability improves, but the processing time and computational complexity increase
Solution Approach 1:
The system pre-calculates and stores adaptation parameters in lookup tables during the off-line training phase. During real-time operation, the control unit only needs to retrieve pre-computed values based on current luminance maps, significantly reducing processing time while maintaining high adaptability to environmental conditions.
Solution Approach 2:
The system uses a dynamic approach where the light pattern adapts in real-time to changing environmental conditions. The control unit continuously updates the light pattern based on current luminance maps, allowing the system to respond dynamically to climate changes, reflections, and refractions without requiring excessive processing time.
3Measurement precision
If image data acquisition and luminance map transformation are performed continuously, then the lighting adaptation accuracy improves, but the energy consumption and computational load increase
Solution Approach 1:
The system performs image acquisition and luminance map transformation at periodic intervals rather than continuously. The control unit updates the light pattern at specific time intervals, reducing computational load and energy consumption while maintaining sufficient measurement precision for effective lighting adaptation.
Solution Approach 2:
The system processes only the necessary portions of the image data required for lighting adaptation. The control unit focuses on extracting relevant luminance information from the working zone without processing the entire image in full detail, reducing computational load while maintaining adequate precision for the lighting application.
Data Source
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AI summary
This invention provides a method for operating an automotive lighting device (1) comprising a plurality of solid-state light sources (2). This method comprises the steps of acquiring image data of a working zone in front of the automotive lighting device, transforming the image data into a luminance map, providing a desired light pattern, calculating an adapted light pattern which provides the desired light pattern when projected over the luminance map and projecting the adapted light pattern (5).