Dynamic Matrix Filter for Vehicle Sensor Light Saturation
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Solution Overview
Problem
Autonomous vehicle image sensors often have insufficient dynamic range, leading to inaccurate image capture in bright or dark environments, which can result in downstream processing failures, such as misinterpreting traffic signals due to light saturation.
Innovation Solution
A dynamic matrix filter with adjustable optical density elements is positioned in front of the image sensor to selectively obscure regions of the field of view, blocking bright sources of light and allowing the sensor to capture images without saturation, thereby improving dynamic range and aiding downstream processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the image sensor captures images in bright environments without a dynamic matrix filter, then the field of view remains unobstructed, but light saturation occurs causing loss of image data accuracy
Solution Approach 1:
A dynamic matrix filter is introduced as an intermediary component between the bright light source and the image sensor. The filter selectively blocks excessive light in specific regions of the field of view while allowing other regions to remain unobstructed, thereby preventing light saturation without completely blocking the view. This mediator approach resolves the contradiction by filtering harmful light while preserving the imaging function.
Solution Approach 2:
The dynamic matrix filter applies different optical properties to different regions of the field of view. Specifically, certain regions experiencing light saturation are assigned high optical density to block light, while other regions maintain low optical density to allow light transmission. This local differentiation resolves the contradiction by applying light blocking only where necessary rather than uniformly across the entire field of view.
2Measurement precision
If a dynamic matrix filter is used to block bright light sources, then light saturation is reduced improving image accuracy, but the device complexity increases
Solution Approach 1:
The filter system employs dynamic control where the optical density of different matrix elements can be adjusted in real-time based on detected light conditions. Rather than using a static filter, the system dynamically modulates light blocking properties of individual matrix elements, allowing adaptive response to varying light environments while maintaining a relatively simple overall device structure.
Solution Approach 2:
The filter is divided into multiple independently controllable matrix elements arranged in a grid pattern. Each element can be controlled separately to block or transmit light based on local lighting conditions. This segmentation allows the complex function of selective light blocking to be achieved through simple, identical repeating units, reducing overall system complexity.
3Reliability
If regions of the field of view are obscured by the dynamic matrix filter, then bright light sources are blocked preventing saturation, but the quantity of light reaching the sensor is reduced
Solution Approach 1:
The dynamic matrix filter applies high optical density (light blocking) only to specific matrix elements corresponding to regions with bright light sources that would cause saturation. Other matrix elements maintain low optical density to allow maximum light transmission. This local quality approach ensures that light quantity is reduced only where necessary to prevent saturation, while preserving light quantity in regions where it is needed for proper imaging.
Solution Approach 2:
The filter acts as a selective intermediary that modulates light transmission on an element-by-element basis. Rather than uniformly blocking light, each matrix element independently mediates the light transmission based on local conditions, allowing the system to maintain reliable downstream processing by preventing saturation while preserving sufficient light quantity in unobscured regions.
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
The dynamic matrix filter enhances the image sensor's ability to capture and process images in high-contrast environments, improving the accuracy of autonomous vehicle navigation by reducing light-induced saturation and allowing for better detection of critical visual cues like traffic signals.
Implementation Method 1
each of which has an adjustable optical density. That is, the optical density of an individual element in the array of elements may be increased to cause the element to become opaque to block out a region of the field of view
Data Source
AI summary
Aspects of the present disclosure include systems, methods, and devices use a controllable matrix filter to selectively obscure regions of an image sensor's field of view. The controllable matrix filter is a physical component that may be placed in front of an image sensor and, in certain situations, one or more regions of the otherwise transparent matrix filter may be selectively configured to have an increased optical density such that the one or more regions become opaque thereby blocking out certain regions of the image sensor's field of view. In this way, the controllable matrix filter may be used to mask out certain regions in an image sensor's field of view that may present processing difficulties for downstream systems that utilize information from the image sensor.