Vehicle Camera Control Module Dynamic Parameter Adjustment
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Solution Overview
Problem
Current automotive camera systems lack effective image stabilization and lighting compensation, leading to suboptimal image quality during vehicle operation, especially in varying lighting conditions and motion.
Innovation Solution
A camera control module that adjusts camera parameters such as ISO, shutter speed, F-stop, and frame rate based on vehicle movement and light level data from sensors, including ambient light, GPS, and road preview information, to enhance image stabilization and lighting compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If camera parameters are kept fixed for simplicity, then device complexity is reduced, but image quality deteriorates under varying lighting and motion conditions
Solution Approach 1:
The patent implements dynamic adjustment of camera parameters (shutter speed, ISO, aperture) based on real-time sensor data about vehicle motion and ambient lighting conditions. The system transitions from static fixed parameters to dynamic adaptive parameters, allowing the camera to optimize image quality continuously as driving conditions change.
Solution Approach 2:
The system incorporates feedback loops where sensors continuously monitor vehicle acceleration, GPS location, and ambient light levels, and this information feeds back to the camera control module which adjusts parameters accordingly. This closed-loop control ensures image quality is maintained through continuous adaptation to changing conditions.
2Stability of the object's composition
If shutter speed is increased to reduce camera shake, then image stabilization improves, but motion blur increases for moving subjects
Solution Approach 1:
The system dynamically changes the shutter speed parameter based on vehicle motion data from accelerometers and GPS. When vehicle motion is detected, the shutter speed is adjusted to balance freeze-motion requirements with camera shake reduction, optimizing the parameter in real-time rather than using a fixed value.
Solution Approach 2:
The shutter speed transitions from a static setting to a dynamic parameter that adapts continuously based on vehicle acceleration and motion detection, allowing the system to respond to changing driving conditions and optimize the balance between stabilization and motion capture.
3Illumination intensity
If ISO is increased to improve low-light performance, then image brightness improves, but image noise increases
Solution Approach 1:
The system dynamically adjusts the ISO parameter based on ambient light level sensor data. In low-light conditions, ISO is increased to maintain adequate image brightness, while in well-lit conditions, ISO is reduced to minimize noise. This dynamic parameter adjustment optimizes the brightness-quality tradeoff continuously.
4Adaptability or versatility
If multiple sensors are added to gather comprehensive vehicle data, then adaptability to driving conditions improves, but device complexity increases
Solution Approach 1:
The system utilizes existing multi-functional sensors already present in modern vehicles (accelerometers for safety systems, GPS for navigation, ambient light sensors for interior lighting) and repurposes them for camera parameter control. This approach achieves high adaptability without adding dedicated sensors, reducing overall system complexity.
Data Source
AI summary
A camera control system of a vehicle comprises a plurality of sensors configured to determine vehicle data and a camera control module configured to receive the vehicle data from the plurality of sensors. The camera control module is further configured to one of: i) adjust at least one operating parameter of the camera based on vehicle movement data received from the plurality of sensors; or ii) adjust at least one operating parameter of the camera based on light level data received from the plurality of sensors.