Automotive Lighting Control via Luminance Map Object Classification
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Solution Overview
Problem
Automotive lighting devices face challenges in low visibility conditions, where increased light is needed to identify objects, but can cause self-glaring or dazzling to other vehicles, necessitating a solution to enhance visibility without introducing new visibility problems.
Innovation Solution
A method for controlling automotive lighting devices by projecting a light pattern, capturing images, obtaining luminance maps, identifying reliable and non-reliable objects, and modifying light intensity in zones to improve visibility, using a luminance camera or standard camera with software processing, and employing machine learning for object classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If light intensity is increased to improve visibility in low visibility conditions, then object identification capability is improved, but self-glaring and dazzling to other vehicles occurs
Solution Approach 1:
The patent applies local quality by differentiating light intensity across different spatial zones. The lighting device projects light patterns with varying luminous intensity tailored to specific regions: higher intensity toward dark non-reliable objects that need illumination, and lower or zero intensity toward overexposed non-reliable objects and areas where glare would be harmful. This spatially differentiated approach resolves the contradiction by making the lighting system adaptive to local conditions rather than uniformly illuminating all areas.
Solution Approach 2:
The patent implements dynamics by continuously adapting the light pattern based on real-time environmental conditions. The control unit receives image data, generates luminance maps, identifies reliable and non-reliable objects, and dynamically adjusts the light intensity distribution accordingly. This dynamic adaptation allows the system to respond to changing visibility conditions, object positions, and glare risks, resolving the contradiction between improving visibility and avoiding harmful glare effects.
2Illumination intensity
If uniform light distribution is used to illuminate the road, then overall visibility is improved, but dark objects remain underexposed and overexposed objects become washed out
Solution Approach 1:
The patent resolves this contradiction by applying local quality through zonal light intensity control. Instead of uniform illumination, the system divides the road area into zones based on luminance map analysis and object reliability classification. Each zone receives customized light intensity: dark non-reliable objects receive enhanced illumination, overexposed non-reliable objects receive reduced or no additional light, and reliable objects maintain appropriate lighting. This localized approach ensures optimal recognition accuracy for different object types while maintaining overall visibility.
Data Source
AI summary
A method for controlling an automotive lighting device. The method includes projecting a first light pattern, capturing an image of a region in front of the lighting device, obtaining a luminance map from the captured image, identifying objects in the luminance map and classify them as reliable or not reliable, according to at least one reliability criterion and modifying the first light pattern to modify the luminous intensity in at least one zone intended to project light on a non-reliable object.