Vehicle Surroundings Display Visibility Classification
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Solution Overview
Problem
Existing vehicle surveillance systems overwhelm drivers with excessive information, making it difficult to correlate displayed objects with real surroundings, especially at night or in low visibility conditions, due to differences in aperture angles and the inability to accurately represent spatial relationships between visible and invisible objects.
Innovation Solution
A method and device that automatically recognize objects using multiple sensors, classify them as visible or invisible based on visibility criteria, and display them from the occupant's perspective, ensuring geometrical relationships are accurately represented to enhance driver understanding and reduce information overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all detected objects are displayed on the screen, then the information completeness is improved, but the driver's ability to perceive and process information deteriorates due to information overload
Solution Approach 1:
The patent segments the detected objects into two distinct categories: visible objects (displayed in original appearance) and invisible objects (displayed as symbolic representations). This segmentation allows the system to maintain information completeness by displaying all objects while preserving driver perception ability by using different display modes that prevent cognitive overload. The segmentation is based on visibility criteria that evaluate whether the driver can actually see the detected objects.
Solution Approach 2:
The patent applies local quality by using different display qualities for different types of objects. Visible objects are displayed with full visual detail (original images), while invisible objects are displayed with simplified symbolic representations. This differential display quality ensures that the driver receives appropriate information for each object type without being overwhelmed by excessive visual data, thereby maintaining both information completeness and perceptual ease.
2Measurement precision
If objects are highlighted to improve visibility, then the detection precision is improved, but the correlation with real surroundings deteriorates
Solution Approach 1:
Instead of highlighting invisible objects to make them visible, the patent inverts the approach by highlighting visible objects and representing invisible objects symbolically. This inversion maintains the spatial relationships of visible objects in their natural positions while using symbols for invisible objects, preserving the correlation with real surroundings while still providing detection precision for all objects.
Solution Approach 2:
The patent uses symbolic representations (pictograms) as copies of invisible objects rather than displaying their actual images. These symbols convey the essential information about the object's presence and type while maintaining the correct spatial position, thus preserving the correlation with real surroundings while providing precise detection information.
3Measurement precision
If multiple sensors are used to detect objects, then the detection precision is improved, but the device complexity increases
Solution Approach 1:
The patent implements a multi-functional evaluation system that assesses multiple criteria (visibility, lighting conditions, object position, driver attention) to determine how to display detected objects. This universal evaluation mechanism handles various object types and conditions through a single integrated system, reducing the need for separate specialized systems for each detection scenario while maintaining high detection precision through multiple sensor inputs.
Data Source
AI summary
A method represents objects of varying visibility surrounding a vehicle for a driver on a display device. The surroundings are automatically recognized by object recognition devices. For recognized objects, it is determined whether the respective object is a first object classified to be visible, or a second object classified to be invisible to the occupant. For a number of recognized objects including at least one first object and second object, respective positions of the objects are determined for the display, in the case of which the geometrical relationships between the number of objects correspond essentially to the real geometrical relationships.