Vehicle Lighting Calibration Using Coded Reference Body
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Solution Overview
Problem
Existing lighting driver assistance systems in vehicles require complex and error-prone calibration processes, often necessitating specialized personnel and nighttime checks to ensure correct functioning, which can lead to glare issues for other road users.
Innovation Solution
A method involving a vehicle with a lamp and image capturing unit positioned in front of a planar surface, where the lamp is pivoted through defined angles to record brightness distributions, allowing for the calculation of angular offsets and correction values to ensure proper illumination, enabling standardized checks without specialized training or nighttime operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex calibration methods are used to ensure accurate lighting alignment, then lighting precision is improved, but the complexity of the checking process increases and requires specialized personnel
Solution Approach 1:
A planar reference body with a coded pattern serves as an intermediary between the lighting system and the camera. This reference body provides known geometric features that simplify the calibration process by enabling automatic feature detection and coordinate transformation, eliminating the need for complex manual alignment procedures while maintaining high precision.
Solution Approach 2:
The reference body creates a known light pattern projection that can be captured and analyzed. By capturing the projected pattern at multiple angular positions and comparing it with the known reference pattern, the system automatically determines calibration parameters without requiring specialized personnel or complex procedures.
2Reliability
If manual checking methods are used, then specialized expertise is required, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system performs self-calibration by automatically capturing images at multiple angular positions, processing the images to detect the reference pattern, calculating calibration parameters, and storing the results. This automated self-service approach eliminates the need for manual intervention, reducing both time and potential human errors while maintaining high reliability.
Solution Approach 2:
The system captures images at defined angular positions, compares the captured reference pattern with the known reference pattern, and uses the detected deviations to calculate correction values. This feedback loop ensures accurate calibration while automating the process, reducing checking time without sacrificing reliability.
3Reliability
If nighttime driving checks are performed to verify system interaction, then real-world performance is validated, but the checking process becomes complex and cannot be standardized
Solution Approach 1:
The system performs calibration checks in advance using a controlled reference body and standardized imaging process. By pre-determining calibration parameters through automated image capture and processing at defined angular positions, the system validates the lighting-camera interaction without requiring nighttime driving tests, enabling standardization while maintaining reliability.
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 method simplifies the checking of lighting driver assistance systems, allowing for error-free adjustments and ensuring correct functioning without manual errors, enabling standardized service activities and improved road safety.
Implementation Method 1
The light emanating from the lamp impinging on the body... an image of the brightness distribution obtained on the surface of the body is recorded by the image acquisition unit
Data Source
Figure 1
Figure 2
Figure 3a~3b
AI summary
The invention relates to a method and an apparatus for checking a lighting driving assistance system of vehicles. In this case, a vehicle (1) is positioned in front of a body (4) and a light (3) of the vehicle (1) is aimed at this body (4). Brightness distributions (6, 6', 6'') are obtained by adjusting the light (3) in the horizontal and vertical directions in a plurality of angular positions and are recorded by an image capture unit (7). The recorded brightness distributions (6, 6', 6'') are used to calculate the distance and angular offset as well as the position of the body (4) and actual values of the angular positions. These actual values are compared with preset desired values, and recommended settings for minimizing a difference between desired and actual values are output.