Vehicle HUD AR Object Positioning via Acceleration Prediction
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Solution Overview
Problem
Existing head-up display (HUD) systems face challenges in accurately providing augmented reality (AR) objects to users, particularly due to limited space and the difficulty in achieving a large representation image and wide field of view, which can result in inaccurate positioning of 3D AR objects when the user's position changes, such as during vehicle acceleration or road conditions.
Innovation Solution
A method that determines a user's eye information and vehicle acceleration using an inertial measurement unit, predicts the user's target position after a preset time, and generates a panel image by rendering left and right images based on this prediction, ensuring accurate AR object placement through a HUD system, even during vehicle movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the HUD system uses a fixed rendering method without considering vehicle acceleration, then the system complexity is reduced, but the positioning accuracy of AR objects deteriorates when the user's position changes
Solution Approach 1:
The system performs preliminary actions by measuring vehicle acceleration using an inertial measurement unit (IMU) and predicting the user's target position before rendering the AR objects. This prediction is based on the acceleration data and eye information, allowing the system to pre-calculate where the AR objects should be positioned to account for upcoming vehicle movement, thereby maintaining positioning accuracy without requiring complex real-time adjustments during rendering
Solution Approach 2:
The system implements feedback by continuously monitoring vehicle acceleration through the IMU and using this information to adjust the predicted user position and AR object rendering. The acceleration data provides feedback about vehicle motion state, which is fed back into the rendering pipeline to dynamically adjust AR object positions, ensuring accuracy while maintaining a manageable system architecture through structured information flow
2Reliability
If the system renders AR objects without predicting user position changes, then the processing time is reduced, but the visibility and accuracy of AR information deteriorates during vehicle acceleration
Solution Approach 1:
The system performs preliminary position prediction by calculating the user's target position based on measured acceleration and eye information before the actual rendering occurs. This advance calculation ensures that when the AR objects are rendered, they are already positioned correctly for the predicted user location, maintaining high visibility and accuracy without requiring time-consuming post-rendering adjustments
Solution Approach 2:
The system applies dynamics by making the AR object positioning adaptive and dynamic rather than static. The rendering process dynamically adjusts AR object positions based on real-time acceleration data and predicted user movement, allowing the system to respond to changing vehicle conditions while maintaining a processing pipeline that is efficient enough for real-time application
3Measurement precision
If the HUD system does not account for acceleration-induced position changes, then the ease of operation is improved, but the accuracy of 3D AR object placement deteriorates
Solution Approach 1:
The system applies self-service by automatically measuring acceleration, predicting user position changes, and adjusting AR object placement without requiring manual intervention. The inertial measurement unit continuously monitors vehicle acceleration and the system automatically uses this data to recalculate and reposition AR objects, maintaining high placement accuracy while keeping the operation simple and automated
Solution Approach 2:
The system replaces complex mechanical adjustment mechanisms with sensor-based detection and computational prediction. Instead of using mechanical systems to physically adjust AR object positions based on vehicle movement, the system uses an IMU to detect acceleration and computationally predicts where objects should be placed, substituting physical adjustment mechanisms with a more elegant sensor-computation approach that maintains accuracy without adding operational complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate and stable provision of 3D AR objects to users, minimizing cross-talk and ensuring clear visibility of AR information, even when the user's position changes due to vehicle acceleration or other factors, thereby enhancing driving safety and usability.
Implementation Method 1
measuring an acceleration of the vehicle using an inertial measurement unit
Data Source
AI summary
A method for providing an augmented reality (AR) object to a user includes determining a left image and a right image to provide an AR object to a user of a vehicle; generating eye information of the user based on an image of the user that is obtained; measuring an acceleration of the vehicle using an inertial measurement unit; predicting a target position of the user a preset time period after the image of the user is obtained, based on the acceleration and the eye information; generating a panel image by rendering the left image and the right image based on the predicted target position; and providing the AR object to the user by outputting the panel image through a head-up display (HUD) system of the vehicle.