Windshield HUD Alignment Using Road Gradient Estimation
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Solution Overview
Problem
Existing in-vehicle display systems face challenges in achieving accurate positioning of images on head-up displays due to varying road gradients, leading to misalignment when driving on inclined roads.
Innovation Solution
An in-vehicle display system that utilizes a camera, radar sensor, gyroscope sensor, and electronic control unit to recognize preceding vehicles, estimate angles and distances, calculate vehicle heights, and adjust image positions on the head-up display based on road gradients, ensuring accurate superimposition of images on the landscape.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image position on head-up display is fixed without gradient compensation, then device complexity is reduced, but position accuracy deteriorates on inclined roads
Solution Approach 1:
The patent uses the preceding vehicle as an intermediary reference object to estimate road gradient. Instead of directly measuring road inclination, the system observes the apparent height changes of a known reference vehicle to infer gradient information, which then compensates for image position on the head-up display.
Solution Approach 2:
The patent replaces direct mechanical or sensor-based gradient measurement systems with a vision-based estimation approach. By using camera images and computational algorithms to analyze vehicle height changes, the system substitutes complex physical gradient sensing with image processing and geometric calculations.
2Measurement precision
If gradient estimation is performed using multiple sensors and calculations, then position accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes the camera system multi-functional by using it for both preceding vehicle recognition and gradient estimation. The same image processing pipeline serves dual purposes: identifying target vehicles and extracting height information for gradient calculation, thereby reducing the need for separate dedicated sensors.
Solution Approach 2:
The system uses readily available data from existing sensors (camera and basic vehicle sensors) to perform gradient estimation, rather than requiring dedicated gradient measurement hardware. The calculation unit leverages data already being collected for other functions (vehicle detection, distance measurement) to derive gradient information.
Data Source
AI summary
An in-vehicle display system includes: an angle estimation unit that estimates, based on an image captured by a camera, an angle provided by a straight line connecting an own vehicle and a preceding vehicle with respect to a front-rear direction of the own vehicle; an inter-vehicle distance estimation unit that estimates an inter-vehicle distance between the own vehicle and the preceding vehicle based on a detection result obtained by a radar sensor of the own vehicle; a height calculation unit that calculates a height of the preceding vehicle based on the angle and the inter-vehicle distance; a gradient estimation unit that estimates a gradient of a road ahead of the own vehicle based on a temporal change of the height of the preceding vehicle; and a display control unit that displays an icon on a windshield so that the icon is superimposed on a landscape ahead of the own vehicle.