Vehicle Light Color Calculation for Nighttime Image Data Quality
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Solution Overview
Problem
Modern driver assistance systems in vehicles face challenges in evaluating data captured by cameras, particularly at night, due to the dependency on lighting conditions, which affects the accuracy of image data used for object and road marking identification.
Innovation Solution
A control device and method that utilize an image capturing device to capture data from an illuminated area in front of the vehicle, with a calculation device determining the light color emitted by the vehicle's lights, allowing driver assistance systems to optimize object and road marking identification by accounting for the lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If image capturing devices are used to capture surroundings of the vehicle, then information about the environment can be obtained, but the image data becomes highly dependent on lighting conditions especially at night
Solution Approach 1:
The control device captures image data with the image capturing device, calculates the actual light color from this image data, and feeds this information back to adjust the evaluation of the image data. This feedback loop allows the system to adapt to varying lighting conditions dynamically, improving both image data quality and evaluation reliability at night.
Solution Approach 2:
The system changes the evaluation parameters of image data based on the calculated light color. By adjusting how image data is processed and interpreted according to the actual lighting conditions (different light colors), the system maintains reliable object and road marking identification despite varying nighttime lighting.
2Extent of automation
If driver assistance systems use camera data for object and road marking identification, then automated driving functions can be implemented, but identification accuracy decreases under varying lighting conditions
Solution Approach 1:
The calculated light color information is fed back to the driver assistance system to adjust its object and road marking identification algorithms. This feedback enables the automated functions to compensate for lighting variations, maintaining identification accuracy across different nighttime conditions.
Solution Approach 2:
The system dynamically adjusts the identification parameters and algorithms based on the calculated light color. Instead of using fixed identification thresholds, the system adapts its detection criteria in real-time according to the actual lighting conditions, thereby maintaining high identification accuracy under varying nighttime illumination.
Data Source
AI summary
A control device and method for a vehicle with a light which is designed to illuminate an area in front of the vehicle, including an image capturing device, which is designed to capture image data for an area in front of the vehicle which is illuminated by the light in a switched-on state, and to output the image data, and including a calculation device, which is coupled to the image capturing device and is designed to calculate from the image data a light color that the light emits, and output it.