Headlamp Light Distribution Plausibility Check via Camera
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Solution Overview
Problem
Current methods for checking the plausibility of light distributions in headlamps of motor vehicles are inadequate in ensuring accurate alignment and uniformity of light characteristics, particularly in dynamic environments.
Innovation Solution
A method and system that utilize a camera and processor to irradiate a scene, capture images, dynamically identify initial optical features, extract further features from local surroundings, and apply a learned algorithm to check the plausibility of feature arrangements, enabling adaptive adjustment of the headlamp for correct light distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to check light distribution plausibility, then the checking process is simple, but the measurement precision and reliability of detected features are insufficient
Solution Approach 1:
The image processing is divided into multiple stages: initial optical feature detection, local surroundings extraction, and plausibility checking. This segmentation allows each stage to focus on specific tasks, improving overall measurement precision while managing system complexity through modular processing steps.
Solution Approach 2:
The camera serves as an intermediary between the headlamp light distribution and the analysis system. By capturing the light distribution as an image, the system can apply sophisticated image processing algorithms to detect optical features with high precision without requiring direct physical measurement devices.
2Adaptability or versatility
If static checking methods are used, then the system is simple to operate, but the adaptability to dynamic environments and varying light distributions is poor
Solution Approach 1:
The system dynamically adapts to different light distributions by using image processing algorithms that can detect and analyze varying optical features in real-time. The plausibility checking mechanism adjusts its criteria based on the detected initial optical features and their local surroundings, enabling the system to handle diverse and dynamic lighting conditions.
Solution Approach 2:
The plausibility checking mechanism provides feedback on the detected optical features by comparing them against expected patterns and relationships. This feedback loop allows the system to automatically adjust and refine its detection and analysis processes, improving adaptability while maintaining ease of operation through automated correction.
3Reliability
If comprehensive plausibility checking is performed, then the reliability of light distribution verification is improved, but the checking time and processing duration increase
Solution Approach 1:
The system performs preliminary detection of initial optical features and extracts their local surroundings before conducting the full plausibility check. This preliminary action prepares the data in advance, allowing the comprehensive plausibility verification to proceed more efficiently by working with pre-processed information rather than raw images.
Solution Approach 2:
The system extracts only the relevant local surroundings of initial optical features rather than analyzing the entire image in detail. By taking out and focusing on specific regions of interest, the system maintains high reliability in plausibility checking while reducing the overall processing time and computational burden.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures accurate determination and adaptation of light distributions, improving the quality and uniformity of headlamp illumination by comparing actual and intended patterns, thereby enhancing the overall lighting performance.
Implementation Method 1
A headlamp for a motor vehicle which, for example, is embodied as a matrix headlamp comprises a multiplicity of light-emitting diodes arranged in the shape of a matrix
Implementation Method 2
capturing, by a camera of the motor vehicle, the irradiated scene in an image
Data Source
AI summary
A method for checking the plausibility of detected features of a light distribution of a headlamp of a motor vehicle includes irradiating, by the headlamp, a scene in surroundings of the motor vehicle; capturing, by a camera of the motor vehicle, the irradiated scene in an image; dynamically seeking and identifying at least one initial optical feature in the image, adaptively producing and analyzing local surroundings of the at least one initial optical feature; dynamically extracting at least one further optical feature from the local surroundings; and carrying out, using a learned algorithm and on the basis of the at least one initial optical feature and the at least one further optical feature, an adaptive check as to whether the at least one initial optical feature and the at least one further optical feature are plausibly arranged in the local surroundings.