Veiling Glare Detection on Vehicle Optical Surfaces
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Solution Overview
Problem
Veiling glare caused by degraded optical surfaces in vehicles reduces the effectiveness of camera imaging systems and other sensors, particularly in automotive applications, leading to decreased image contrast and increased noise, which affects object detection and perception in various driving environments.
Innovation Solution
The system detects veiling glare by analyzing the relationship between the optical surface and the angle of incidence of light, using sensors and image processing to quantify obstructions such as dust or scratches, and activates remediation actions like windshield cleaning or modifying ADAS/AV algorithms to mitigate its effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the optical surface is exposed to outdoor environments for extended periods, then the vehicle can operate in various driving conditions, but dust and materials accumulate on the optical surface causing veiling glare
Solution Approach 1:
The system performs preliminary detection of optical surface degradation by analyzing veiling glare characteristics before they significantly impact sensor performance. The controller continuously monitors image quality metrics and identifies early signs of dust accumulation or surface contamination, enabling proactive remediation through windshield cleaning system activation or algorithmic compensation before the degradation becomes severe enough to compromise safety-critical object detection.
2Object-affected harmful factors
If windshield cleaning is activated to remove obstructions, then veiling glare is reduced, but the cleaning process may not fully restore optical performance if scratches or permanent degradation are present
Solution Approach 1:
The system implements a closed-loop feedback mechanism where the controller continuously monitors veiling glare levels before, during, and after cleaning operations. By analyzing changes in image contrast, noise characteristics, and overall image quality metrics, the system determines whether cleaning has successfully remediated the degradation. If permanent damage such as scratches is detected that prevents full restoration, the system adapts by adjusting sensor parameters, modifying image processing algorithms, or triggering alerts to notify the driver of reduced optical performance.
3Reliability
If image processing algorithms are modified to compensate for veiling glare, then object detection capability is maintained, but the complexity of the perception system increases
Solution Approach 1:
The system dynamically adjusts image processing parameters based on detected veiling glare characteristics. When degradation is detected, the controller modifies exposure times, gain settings, or applies adaptive histogram equalization specifically targeted at restoring contrast in affected regions. These parameter changes are automatically tuned based on the severity and spatial distribution of veiling glare, allowing the system to maintain object detection accuracy without requiring permanently complex algorithms, as the complexity is only activated when needed and adapted to specific degradation scenarios.
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 solution effectively reduces the impact of veiling glare by improving image contrast and sensor performance, enabling better object detection and perception, even in challenging environments like tunnels or at night, by accurately identifying and addressing optical surface degradations.
Implementation Method 1
Veiling glare is defined as light that has been reflected or scattered out of an image forming beam
Implementation Method 2
Veiling glare is defined as light that has been reflected or scattered out of an image forming beam
Data Source
AI summary
Optical surface degradation detection and remediation systems, devices, and methods are provided herein. An example method includes tracking a first object within images of an area of interest obtained over a period of time by an image sensor of a vehicle during vehicle movement; tracking a light source within the area of interest; determining a change in relative reflective intensity of the first object using the images, based on a light source angle formed between the light source and an optical plane of an optical surface the vehicle, the change in relative reflective intensity being indicative of veiling glare of the optical surface; and activating a remediating measure in response to the veiling glare.