Vehicle Camera Brightness Control Using Dead-Zone Interpolation
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Solution Overview
Problem
Conventional vehicle camera brightness control systems, such as those using PID control, face challenges in adapting quickly to varying light conditions without overshooting or oscillating, and require complex parameter selection for optimal performance.
Innovation Solution
The system employs a brightness control method that interpolates towards a set point by calculating a set of three brightness values from previous frame coefficients, allowing for adaptive adjustment of coefficients based on error, using a function of the difference between actual and expected brightness, and optionally incorporating a dead-zone for stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional PID control is used for brightness adjustment, then the system can maintain stability, but the response speed to varying light conditions is slow and requires complex parameter selection
Solution Approach 1:
The patent changes the control parameter from traditional PID coefficients to a dead-zone parameter with linear interpolation. This simplifies parameter selection to primarily the dead-zone threshold, eliminating the need to tune multiple PID parameters while improving response speed through direct error-based adjustment.
Solution Approach 2:
The patent extracts and removes the integral and derivative components from the traditional PID controller, retaining only a simplified proportional control with dead-zone filtering. This reduction eliminates complex parameter interactions while maintaining essential brightness stabilization functionality.
2Speed
If aggressive brightness adjustment is applied to respond quickly to light changes, then response speed improves, but overshooting and oscillation occur
Solution Approach 1:
The patent implements a dead-zone parameter that acts as a cushion before brightness adjustment begins. By requiring the error to exceed the dead-zone threshold before triggering adjustment, the system prevents unnecessary oscillations and overshooting while maintaining rapid response to significant light changes.
Solution Approach 2:
The patent introduces dynamic adaptation where the dead-zone parameter can be adjusted based on current lighting conditions and error magnitude. This allows the system to be more aggressive when far from target brightness and more conservative when approaching it, optimizing both speed and stability.
3Manufacturing precision
If traditional control methods are used, then the system structure remains simple, but the convergence to expected brightness is slow and requires extensive tuning
Solution Approach 1:
The patent implements a self-adjusting brightness control system that automatically adapts to different lighting conditions without requiring manual tuning. The linear interpolation method with dead-zone automatically converges to the expected brightness based on real-time error calculation, eliminating the need for extensive manual parameter optimization.
Solution Approach 2:
The patent employs continuous feedback by calculating the error between actual and expected brightness for each frame and using this error to drive the next brightness adjustment. This closed-loop control ensures precise convergence while the simplified parameter structure eliminates tuning requirements.
Data Source
AI summary
A vision system for a vehicle includes a camera disposed at a vehicle and having a field of view exterior of the vehicle. A brightness control, responsive to processing of a frame of image data captured by the camera, interpolates towards an expected brightness for a next frame of captured image data by calculating a set of at least three brightness values using three different control coefficients derived from a previous frame of image data captured by said camera. The brightness control interpolates toward the expected brightness of the next frame of captured image data using the current expected brightness value and two of the three brightness values derived from the three control coefficients derived from the previous frame of captured image data.