Vehicle Image Map Updating With Conditional Camera Processing
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Solution Overview
Problem
Current vehicle systems require substantial computational resources to process continuous images from multiple cameras, which is inefficient and costly, especially since typical driving scenarios do not necessitate a mobile photo studio but rather situational awareness for the driver.
Innovation Solution
An update image map method is implemented, which involves receiving vehicle information and capturing images from cameras, processing these images based on lens characteristics and vehicle information, and writing the processed images to a corresponding location on an image map, only updating when specific conditions such as vehicle displacement or speed thresholds are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous images from multiple cameras are processed at high resolution and frame rate, then situational awareness quality is improved, but computational resource consumption increases substantially
Solution Approach 1:
The system implements periodic action by updating the image map only at specific intervals or when change conditions are met (such as vehicle movement thresholds), rather than continuously processing every captured frame. This selective updating approach maintains situational awareness quality while dramatically reducing computational resource consumption by processing images periodically based on meaningful change events.
2Area of stationary object
If multiple cameras with high resolution capture continuous images, then visual coverage of blind spots is improved, but processing complexity increases
Solution Approach 1:
The system extracts and processes only the essential visual information needed for situational awareness by writing processed images to a synthesized image map representing the vehicle's surrounding environment. This extraction approach maintains comprehensive visual coverage from multiple cameras while reducing processing complexity by focusing on key environmental features rather than processing all image data in full detail.
3Loss of time
If image map is updated continuously, then situational awareness freshness is improved, but computational overhead increases
Solution Approach 1:
The system implements periodic action by updating the image map only when specific conditions are met (such as vehicle movement exceeding thresholds or elapsed time intervals), rather than continuously. This maintains situational awareness freshness by updating at meaningful intervals while significantly reducing computational overhead by avoiding redundant processing during stable conditions.
Solution Approach 2:
The system uses feedback mechanisms to determine when image map updates are necessary, monitoring conditions such as vehicle movement, camera changes, or time intervals. This feedback-driven approach ensures the image map is updated only when actual changes warrant refreshment, maintaining awareness freshness while minimizing unnecessary computational overhead from continuous updating.
Data Source
AI summary
The disclosure provides an update image map method applied to a vehicle, which comprising the following steps of: receiving a message used to determine whether conditions for updating an image map are met; determining whether the conditions for updating the image map are met according to the message; when it is determined that the conditions for updating the image map are met, receiving a vehicle information and capturing images from one or more cameras; processing the images based on lens characteristics of the one or more cameras and the vehicle information; and writing the processed images to a corresponding location on the image map based on the received vehicle information.