Vehicle-mounted HUD ambient light adaptive brightness adjustment system

The vehicle-mounted HUD brightness adjustment system, which works in collaboration with multiple modules, achieves accurate perception and dynamic adjustment of ambient light, solving the problem of inaccurate perception in complex lighting environments of existing systems and improving the driver's visual comfort and safety.

CN121148342BActive Publication Date: 2026-07-24HANSITONG OPTOELECTRONICS (ZHEJIANG) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HANSITONG OPTOELECTRONICS (ZHEJIANG) CO LTD
Filing Date
2025-10-29
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing vehicle HUD brightness adjustment systems struggle to accurately detect ambient light conditions, resulting in a mismatch between brightness and ambient light, which negatively impacts the driver's visual experience and safety.

Method used

The system employs a multi-module collaborative approach, including modules for light acquisition, parameter analysis, model building, brightness calculation, error assessment, calibration correction, and feedback optimization, to achieve accurate perception of ambient light and dynamic brightness adjustment.

Benefits of technology

It significantly improves the HUD display effect and driving safety, ensures the accuracy and timeliness of brightness adjustment, avoids the problem of adjustment lag or over-adjustment caused by fixed parameters in traditional systems, and provides a safer and more comfortable driving experience.

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Abstract

The present application relates to the technical field of vehicle display, and discloses a brightness adjustment system for vehicle HUD ambient light adaptation, which comprises illumination collection, parameter analysis, model construction, brightness calculation, error evaluation, calibration correction, threshold setting, result output, feedback optimization and system regulation modules. The illumination collection module analyzes the stability and interference difference of illumination parameters to generate illumination perception state values; the parameter analysis module selects the optimal brightness and light intensity combination; the model construction module establishes a brightness and light intensity relationship model by training samples; the brightness calculation module generates brightness threshold values by combining real-time illumination data mapping; the error evaluation and calibration correction module optimizes the calculation rules; and the feedback optimization module adjusts parameters through running feedback to finally generate an ambient light adaptive brightness adjustment scheme. The system realizes precise dynamic adjustment of the brightness of the vehicle HUD, effectively adapts to changes in ambient light, improves display effect and driving safety, and has the characteristics of self-learning and self-optimization.
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