Driver Display Sharpness Control for Gaze-Based Distraction Mitigation
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Solution Overview
Problem
Existing methods for reducing driving distractions do not effectively optimize cognitive resources by blurring or softening image regions/lines in the periphery of a driver's visual field, leading to inefficient use of metabolic resources during mission-critical tasks.
Innovation Solution
A driver monitor system using in-cabin video cameras and processing circuitry to monitor eye gaze direction, gradually soften image regions and lines outside the focus vision area, and sharpen them when the driver's eyes move towards a new focus area, ensuring full sharpness by the time the driver's eyes shift, thereby reallocating cognitive resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If image regions and lines in the periphery of the visual field are kept sharp, then the driver can perceive all display information clearly, but cognitive resources are inefficiently used due to unnecessary neural engagement processing sharp edges and lines in the periphery
Solution Approach 1:
The patent applies different image processing qualities to different spatial regions of the display. The central focus vision area maintains full sharpness for critical information, while peripheral regions gradually transition to softened/blurred states. This local differentiation allows the driver to perceive necessary information without the brain expending metabolic resources processing sharp edges and lines in non-critical peripheral areas, thus resolving the contradiction between information perception and cognitive resource efficiency.
Solution Approach 2:
The display is segmented into multiple zones based on the driver's eye gaze direction: a sharp central focus area and progressively softer peripheral areas. The system divides the visual field into regions requiring different levels of detail, with the sharpness transition occurring at defined boundaries. This segmentation enables selective allocation of cognitive resources to only those regions where detailed perception is necessary for safe driving.
2Use of energy by moving object
If the system blurs peripheral image regions to save cognitive resources, then metabolic resource efficiency improves, but the driver may miss important peripheral information
Solution Approach 1:
The system performs preliminary actions by detecting eye gaze direction and pre-sharpening peripheral image regions before the driver's eyes actually move to those areas. The eye tracking system anticipates potential gaze shifts and proactively restores sharpness to regions that will become the new focus, ensuring that when the driver looks at peripheral information, it is already in optimal viewing quality without requiring abrupt processing changes.
Solution Approach 2:
The sharpness of peripheral regions is dynamically adjusted based on real-time eye tracking data. As the driver's gaze moves, the system continuously updates which peripheral regions should be sharp versus blurred, creating a dynamic sharpness mask that follows the eye movements. This dynamic adaptation ensures that reliability is maintained for currently viewed information while preserving metabolic efficiency for non-viewed peripheral areas.
3Use of energy by moving object
If the system gradually softens peripheral regions, then cognitive resource allocation optimizes, but the transition may cause visual discomfort or distraction
Solution Approach 1:
The system carefully controls the parameter of sharpness transition, using gradual changes rather than abrupt shifts between sharp and blurred states. The softening parameter is adjusted incrementally across peripheral regions, creating smooth gradients that avoid sudden visual contrasts. This controlled parameter change minimizes visual discomfort and distraction while still achieving the cognitive resource optimization benefits of peripheral blurring.
Data Source
AI summary
A driver monitor system and method of optimizing use of cognitive resources of a user in a vehicle is disclosed. The system includes in-cabin video cameras, a display device, and processing circuitry. The method performed by the processing circuitry includes monitoring eye gaze direction using images from the in-cabin video cameras, gradually softening image regions and lines displayed in the display device that are outside a first vision area of the user of the vehicle, and using the eye gaze direction to predict whether the user is transitioning into a new focus vision area that had been outside the first vision area. When the user's eyes begin to move, begin sharpening softened image regions and lines such that by the time eyes have shifted into the new focus vision area, the image regions and lines in the new focus vision area reach full sharpness.