Vehicle Head-Up Display Depth-of-Field Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern vehicle head-up displays overwhelm drivers with information, particularly at night, due to the large amount of data being presented, which can lead to distraction and reduced ability to perceive critical information sharply.
Innovation Solution
A method and device for a head-up display unit that adjusts the image based on the driver's pupil size and depth of field, using a camera to determine the pupil size and generate signaling signals to adapt the image's sharpness, brightness, and transparency, ensuring the driver focuses on essential information without being overwhelmed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large amount of visual information is displayed on the head-up display, then the driver receives comprehensive information, but the driver becomes overwhelmed and distracted, reducing ability to perceive critical information sharply
Solution Approach 1:
The patent applies local quality by adjusting image parameters (sharpness, brightness, transparency) specifically for critical information elements based on their importance and the driver's current depth of field, rather than uniformly adjusting the entire display. This allows critical information to stand out while maintaining overall information availability.
Solution Approach 2:
The system dynamically changes image parameters (sharpness, brightness, transparency) based on the driver's pupil size and depth of field conditions. When the driver's depth of field is shallow (e.g., at night with dilated pupils), the system increases sharpness and adjusts brightness for critical information elements to ensure they remain perceptible.
2Loss of information
If the head-up display shows detailed information, then the driver gains comprehensive data, but the image becomes less sharp and clear for the driver to perceive
Solution Approach 1:
Different regions and elements of the display are assigned different quality levels. Critical information elements receive enhanced sharpness and clarity through parameter adjustment, while less critical information maintains standard display quality, ensuring overall information completeness with localized precision enhancement.
Solution Approach 2:
The display system dynamically adjusts image parameters in real-time based on detected driver eye state (pupil size, depth of field). The sharpness and clarity of displayed information adapt dynamically to the driver's visual conditions, maintaining optimal perceptibility across varying information density.
3Reliability
If the head-up display adapts to the driver's depth of field, then the driver's perception of critical information improves, but the device complexity increases due to eye tracking and real-time adjustment mechanisms
Solution Approach 1:
The system uses the driver's own eye characteristics (pupil size, depth of field) as the basis for adaptation, eliminating the need for complex external measurement devices. The driver's physiological response naturally provides the feedback needed for automatic parameter adjustment, simplifying the overall system architecture.
Solution Approach 2:
The system implements feedback by continuously monitoring the driver's eye state through the camera and using this information to automatically adjust display parameters. This closed-loop feedback mechanism enables adaptive optimization of information presentation without requiring complex manual intervention or overly sophisticated control systems.
4Adaptability or versatility
If the head-up display uses a camera to determine pupil size and adjust images, then the image adaptation to driver's depth of field improves, but the loss of time for processing and analyzing image data increases
Solution Approach 1:
The system performs preliminary action by continuously monitoring the driver's eye state in advance and maintaining readiness to adjust display parameters. The camera continuously captures eye images and the system pre-processes this data to detect pupil size changes, enabling rapid response when adaptation is needed without waiting for explicit trigger conditions.
Solution Approach 2:
The system implements efficient processing by skipping unnecessary analysis steps and focusing directly on extracting pupil size information from camera images. The processing algorithm is optimized to quickly identify relevant features (pupil boundaries, size) without performing exhaustive image analysis, reducing processing time while maintaining accuracy.
Data Source
Figure 1~2
Figure 3~4
AI summary
The invention relates to a method and a device for operating a heads-up display unit of a vehicle, wherein the heads-up display unit generates an image which is visible to a vehicle driver as a virtual image from a specified viewing window on a windshield of the vehicle. In the process, a depth of field value (SW) is ascertained which represents an estimated current depth of field of an eye of the driver. Furthermore, an indication signal is generated in order to generate the image dependent on the ascertained depth of field value (SW).