Vehicle Image Sensor Parameter Control for Changing Lighting
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Solution Overview
Problem
Self-driving vehicles face challenges in accurately adjusting image sensor settings to handle varying lighting conditions, leading to sensing latency and reduced ability to quickly identify objects, which can impact safety and efficiency.
Innovation Solution
A signal processing system that adjusts image sensor parameters based on determined geographic locations, using data such as lighting characteristics, weather, and time of day to proactively set optimal settings before changes occur, reducing latency and improving image processing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image sensor settings are adjusted manually or reactively to changing lighting conditions, then the system can adapt to different environments, but sensing latency increases and the ability to quickly identify objects is reduced
Solution Approach 1:
The system proactively adjusts image sensor parameters based on predicted future lighting conditions at the vehicle's location. By using geographic location data and environmental models to predict upcoming lighting changes, the system prepares sensor settings in advance before the actual lighting transition occurs, eliminating the reactive delay and reducing sensing latency while maintaining adaptability to changing conditions
Solution Approach 2:
The system continuously monitors the vehicle's geographic location, current lighting conditions, and sensor performance to dynamically adjust image sensor parameters. This closed-loop feedback mechanism uses real-time data from GPS, environmental sensors, and image quality metrics to automatically optimize sensor settings, balancing adaptability with rapid response time by learning from past adjustments and predicting future needs
2Measurement precision
If image sensor parameters are adjusted frequently to maintain accuracy in changing conditions, then image processing accuracy improves, but system complexity and computational load increase
Solution Approach 1:
The system adjusts specific image sensor parameters (exposure time, gain, white balance) based on predicted lighting conditions without redesigning the entire sensor system. By selectively modifying only the necessary parameters rather than overhauling the complete imaging pipeline, the system maintains high image processing accuracy while limiting the increase in system complexity to manageable parameter adjustments
Solution Approach 2:
The system introduces a parameter adjustment module that acts as an intermediary between the image sensor and the main processing system. This intermediary layer handles the complexity of parameter optimization, translating complex lighting predictions into simple sensor configuration changes, thereby improving accuracy while isolating the complexity from the core imaging and processing systems
3Measurement precision
If the system uses multiple data sources (lighting characteristics, weather, time of day) to adjust sensor settings, then the accuracy of parameter adjustment improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system divides the complex task of parameter adjustment into separate modules, each handling a specific data source (lighting characteristics, weather conditions, time of day). Each module independently processes its designated data type and contributes to the overall parameter adjustment decision. This segmentation reduces the difficulty of detecting and measuring by breaking down the integrated data processing into manageable, specialized components while maintaining high adjustment accuracy through the combined input of multiple specialized modules
Data Source
AI summary
Provided are methods for location based parameters for an image sensor, which can include determining the geographic location of the vehicle, adjusting the parameters of the image sensor of the vehicle from a first setting to a second setting based on the geographic location of the vehicle, receiving sensor data associated with the image sensor based on the second setting, and processing the sensor data to generate an image. Systems and computer program products are also provided.