Vehicle Image Sensor Debris Detection and Cleaning
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Solution Overview
Problem
Autonomous vehicles face challenges in detecting and addressing debris on exterior image sensors, such as dust, salt, and insects, which obstruct the view and reduce image quality, as human drivers cannot easily clean these sensors in autonomous operations.
Innovation Solution
A debris detection system utilizing a vehicle computer with a processor and memory to compare captured images of a predetermined object to a target image, quantify noise characteristics, and initiate cleaning by outputting control signals to a sensor cleaning system when noise thresholds are exceeded, using methods like cropping, normalization, and activating cleaning mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a debris detection system is implemented to detect debris on image sensors, then image quality can be maintained, but the device complexity increases
Solution Approach 1:
The system uses the image sensor itself to detect debris on its own lens by comparing captured images against reference images or analyzing noise patterns. This self-diagnosis capability eliminates the need for separate detection sensors, maintaining image quality while minimizing additional system complexity.
Solution Approach 2:
The system continuously monitors image quality metrics (noise levels, signal-to-noise ratio) and provides feedback to the cleaning system. When debris is detected, the feedback loop triggers automatic cleaning, ensuring image quality is maintained through closed-loop control without requiring complex manual intervention systems.
2Reliability
If automatic cleaning is initiated when debris is detected, then image quality is preserved, but the loss of time for cleaning operations increases
Solution Approach 1:
The system performs preliminary detection of debris using image analysis before significant degradation occurs. By detecting debris early through noise characteristic analysis, the system can initiate cleaning at optimal moments (e.g., during vehicle pauses or low-speed operation), minimizing disruption to autonomous vehicle operations while preserving image quality.
Solution Approach 2:
The debris detection and cleaning process operates periodically rather than continuously, with the system monitoring image quality at scheduled intervals or triggered by specific conditions. This periodic operation reduces overall cleaning time while maintaining image quality through timely intervention.
3Measurement precision
If multiple noise characteristics are analyzed to detect debris, then detection precision is improved, but the loss of time for processing increases
Solution Approach 1:
The system analyzes multiple noise characteristics (signal-to-noise ratio, peak signal-to-noise ratio, root mean squared error, mean absolute error) but applies them selectively based on detection needs. By evaluating several metrics simultaneously rather than sequentially, the system achieves high detection precision while minimizing processing time through parallel computation of noise characteristics.
Data Source
AI summary
A vehicle computer includes a memory and a processor programmed to execute instructions stored in the memory. The instructions include comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image, comparing the first noise characteristic to a first predetermined threshold, and detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold.